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Linköping University | Department of Management and Engineering
Master’s Thesis, 30 credits | Sustainability Engineering and Management
Spring 2020 | ISRN LIU-IEI-TEK-A--20/03881—SE
Sustainable Manufacturing: Green
Factory – A case study of a tool
manufacturing company
Rohan Surendra Jagtap (Linköping University)
Smruti Smarak Mohanty (Uppsala University)
Supervisor LiU: Simon Johnsson
Supervisor Sandvik Coromant: Peter J. Jonsson
Examiner: Bahram Moshfegh
Copyright
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© Rohan Surendra Jagtap
© Smruti Smarak Mohanty
Popular Scientific Summary
Sustainable development is a hot topic trending across the world in the 21st century. It is
important to grasp the definition of ‘Sustainable Development’. One popular definition of
sustainable development is from the United National World Commission on environment and
Development is “Development that meets the needs of the present without compromising the
ability of future generations to meet their own needs”. In the 4th industrial revolution the whole
world is moving in a sustainable direction in the three domains - environmental, economic and
social. The term Sustainable Manufacturing refers to the integration of processes and systems
capable to produce high quality products and services using less and more sustainable resources
(energy and materials), being safer for employees, customers and communities surrounding,
being able to mitigate environmental and social impacts throughout its whole life cycle.
The thesis report presents a method to track energy use in the production line for a product
family i.e. turning tools. This is done by carrying out a bottom-up energy audit and creating a
map of the energy use in the entire production process by implementing the Value Stream
Mapping (VSM) method. This analysis of the energy use will help developing an energy cost
tool which quantifies the carbon footprints from the manufacturing of tools as well as from the
facility. Another outlook of the study is to develop new Energy Performance Indicators (EnPIs)
for the production and support processes. The EnPIs presents an opportunity to monitor the
energy use closely by integrating them into the energy software. Finally, another purpose of
the thesis study is to study the social sustainability dimension wherein the working environment
is analysed and discussed.
The case study result presents a huge potential in achieving higher sustainability in tool
manufacturing industries. By implementing sustainable manufacturing, the organizations could
achieve efficient productivity, such as higher quality of manufacturing, waste elimination from
the production line, re-use of the essential resources and product durability improvement
resulting in less carbon footprint. This thesis work could serve as a base for future sustainability
projects for the tool manufacturing industries.
Foreword
This Master Thesis has been written in collaboration with Linköping University. The work has
been jointly developed by Rohan Surendra Jagtap (Linköping University) and Smruti Smarak
Mohanty (Uppsala University) with the help of AB Sandvik Coromant. We both authors have
worked in most of the areas prioritized to our field of studies. In this study, I have focused on
the energy audit, energy cost tool and energy performance indicators aspect whereas Smruti
has focused on the Sustainable Value Stream Mapping and social sustainability. Both the report
shares about 80% to 90% similarity and might differ in terms of formatting and overall
structuring.
I’d like to thank Simon Johnsson my supervisor for the thesis at Linköping University who is
working as a Research Engineer in the Department of Management and Engineering (IEI)
within the Division of Energy Systems. He has helped me whenever I have faced difficulties
throughout the thesis as he has a thorough experience working with energy auditing and related
research work. While also read proofing my entire thesis report, thus making it much better in
terms of the language as well as structuring. I’d also like to thank Ines Julia Khadri, Ph.D.
student at the Department of Engineering Sciences, Industrial Engineering & Management in
Uppsala University who supervised Smruti and has indirectly also helped me with the thesis.
I would like to thank Sandvik Coromant, Gimo for their assistance in the collection of data
including all the respondents and managers that took part in our study and gave us the
opportunity to interview them with thorough input and full support. I would further like to
thank my manager at the company Peter J. Jonsson and my supervisors at company Martin
Kolseth, Lovisa Svarvare and Peter P. Andersen for their unwavering support and guidance.
I would like to appreciate all my course instructors within the Sustainability Engineering and
Management program at IEI Department at Linköping University. I am truly grateful for the
knowledge gained throughout the last two years which has complemented me in doing this
thesis work. The thesis completes my master’s studies and I have enjoyed my time at
Linköping University.
In truth, I could not have achieved my current level of success without a strong support group.
I am thankful to my parents and friends who have constantly provided me with the emotional
support and motivation especially during the Covid-19 pandemic.
Abstract
Efficient use of resources and utility is the key to reduce the price of the commodities produced
in any industry. This in turn would lead to reduced price of the commodity which is the key to
success. Sustainability involves integration of all the three dimensions: environmental,
economic and social. Sustainable manufacturing involves the use of sustainable processes and
systems to produce better sustainable products. These products will be more attractive, and the
industry will know more about the climate impact from their production.
Manufacturing companies use a considerable amount of energy in their production processes.
One important area to understand the sustainability level at these types of industries is to study
this energy use. The present work studies energy use in a large-scale tool manufacturing
company in Sweden. Value Stream Mapping method is implemented for the purpose of
mapping the energy use in the different operations. To complement this, an energy audit has
been conducted, which is a method that include a study and analysis of a facility, indicating
possible areas of improvements by reducing energy use and saving energy costs. This presents
an opportunity for the company to implement energy efficiency measures, thus generating
positive impacts through budget savings. Less energy use is also good for the environment
resulting in less greenhouse gas emissions level. This also helps in long-term strategic planning
and initiatives to assess the required needs and stabilize energy use for the long run. Social
sustainability completes the triad along with environmental and economic sustainability. In this
study, the social sustainability is reflected with the company’s relationship with its working
professionals by conducting a survey. The sustainable manufacturing potential found in the
case study indicates that significant progress can be made in the three sustainability
dimensions. Although, the scope of the thesis is limited to a tool manufacturing company,
several of the findings could be implemented in other tool companies as well as industries
belonging to other sectors.
Key words: energy audit, energy efficiency, Value Stream Mapping
Table of Contents 1. Introduction ........................................................................................................................ 1
1.1. Problematization.......................................................................................................... 2
1.2. Need of sustainable manufacturing in tool manufacturing industries ......................... 3
1.3. Objective and Research questions ............................................................................... 4
1.4. Delimitation ................................................................................................................. 5
1.5. Case Company description .......................................................................................... 5
1.5.1. About Sandvik Group .......................................................................................... 5
1.5.2. About Sandvik Coromant .................................................................................... 6
2. Theoretical framework ....................................................................................................... 7
2.1. Sustainable Manufacturing .......................................................................................... 7
2.2. Energy Auditing .......................................................................................................... 8
2.3. Energy Efficiency ...................................................................................................... 10
2.4. Value Stream Mapping.............................................................................................. 11
2.5. Cost tool in manufacturing ........................................................................................ 11
2.6. Energy Performance Indicators ................................................................................. 12
2.7. Social Sustainability .................................................................................................. 13
3. Literature Review............................................................................................................. 14
3.1. Sustainable Manufacturing ........................................................................................ 15
3.2. Energy Audit ............................................................................................................. 15
3.3. Energy Efficiency ...................................................................................................... 16
3.4. Energy Management ................................................................................................. 16
3.5. Value Stream Mapping.............................................................................................. 17
3.6. Energy Performance Indicators ................................................................................. 18
3.7. Social sustainability................................................................................................... 19
4. Methodology .................................................................................................................... 19
4.1. Literature review ....................................................................................................... 20
4.2. Research design ......................................................................................................... 20
4.3. Research approach..................................................................................................... 21
4.4. Empirical case data collection approach ................................................................... 22
4.4.1. Data collection for Bottom-up audit .................................................................. 23
4.4.2. Data collection for Sus-VSM ............................................................................. 24
4.4.3. Data collection for Energy cost tool .................................................................. 26
4.4.4. Data collection for Energy Performance Indicators........................................... 27
4.4.5. Data collection for Social sustainability ............................................................ 27
4.5. Motivation of Research Methodology....................................................................... 28
4.6. Ethical and legal consideration ................................................................................. 29
4.1. Limitations ................................................................................................................ 29
5. Result and analysis ........................................................................................................... 30
5.1. Audit .......................................................................................................................... 30
5.1.1. Survey ................................................................................................................ 30
5.1.2. Energy Analysis ................................................................................................. 31
5.1.3. Energy Efficiency Measures .............................................................................. 37
5.2. Sustainable Value Stream Mapping .......................................................................... 45
5.3. Energy Cost Tool ...................................................................................................... 48
5.4. Energy Performance Indicators (EnPIs) .................................................................... 53
5.5. Interpretation of Social Sustainability ....................................................................... 55
6. Discussion ........................................................................................................................ 59
7. Conclusion ....................................................................................................................... 62
8. Future Scope .................................................................................................................... 63
References ................................................................................................................................ 65
Appendix .................................................................................................................................. 72
Appendix 1. PI System Explorer ......................................................................................... 72
Appendix 2. Semi-structured interview template ................................................................ 73
Appendix 3. Social sustainability survey template .............................................................. 74
Appendix 4. VSM Calculation ............................................................................................. 75
List of Figures
Figure 1 The three dimensions of sustainability (Sonnemann, et al., 2015) .............................. 1
Figure 2 Different divisions of Sandvik group .......................................................................... 6
Figure 3 Classification of sustainable manufacturing, Bonvoisin et al. (2017) ......................... 8
Figure 4 Energy Audit process developed by (Rosenqvist, et al., 2012) ................................. 10
Figure 5 Concept of energy performance indicators (EnPI) in baseline period and
implemented period (ISO, 2020) ............................................................................................. 12
Figure 6 Funneling structure for literature review ................................................................... 14
Figure 7 Mixed research methods adopted for thesis study ..................................................... 21
Figure 8 Data Collection .......................................................................................................... 22
Figure 9 Iterative process for industrial audit, (Rosenqvist, et al., 2012) ................................ 23
Figure 10 System Boundaries for study ................................................................................... 29
Figure 11 Production flow for the products ............................................................................. 31
Figure 12 Active power sum L1-L3 (10m) for 2018 ............................................................... 31
Figure 13 Active power sum L1-L3 (10m) for 2019 ............................................................... 32
Figure 14 Unit Processes of GVP3, Heat Treatment and Packaging ....................................... 33
Figure 15 Sankey diagram: Product A ..................................................................................... 34
Figure 16 Sankey diagram: Product B .................................................................................... 34
Figure 17 Sankey diagram: Product C .................................................................................... 35
Figure 18 Sankey diagram: Product D .................................................................................... 35
Figure 19 Percent energy recycled from compressors ............................................................. 36
Figure 20 Percentage of energy going to the ventilation and preheating the incoming air ..... 37
Figure 21 Percentage of total instantaneous electricity of compressors .................................. 37
Figure 22 Working week total energy use in STAMA cells .................................................... 38
Figure 23 Non-working week total energy use in STAMA cells ............................................ 38
Figure 24 Organizational structure of Energy Management .................................................... 39
Figure 25 Energy Pyramid at Volvo CE (Thollander, et al., 2020) ......................................... 40
Figure 26 Procedure for implementation of energy efficiency measures (Hessian Ministry of
Economics, Transport, Urban and Regional Development, 2011) .......................................... 41
Figure 27 Pump energy use during production week in STAMA cells ................................... 42
Figure 28 Pump energy use during non-production week in STAMA cells............................ 43
Figure 29 VSM diagram for Product A ................................................................................... 46
Figure 30 VSM diagram for Product B.................................................................................... 46
Figure 31 VSM diagram for Product C.................................................................................... 47
Figure 32 VSM diagram for Product D ................................................................................... 47
Figure 33 Energy Cost Tool: Tool Sheet ................................................................................. 50
Figure 34 Energy Cost Tool: Data Sheet ................................................................................. 51
Figure 35 Output Report Sheet ................................................................................................ 52
List of Tables
Table 1 Structure of unit processes categorization (SÖDERSTRÖM, 1996) ............................ 9
Table 2 Comparison of Traditional VSM and Sus-VSM (Bown, et al., 2014) ........................ 11
Table 3 Set of templates to measure energy efficiency (Schmidt, et al., 2016) ....................... 19
Table 4 Example of losses in a compressed-air system, (Falkner & Slade, 2009) .................. 44
Table 5 Reference Chart for the Tool sheet ............................................................................. 49
Table 6 List of current EnPIs used in STAMA cells ............................................................... 53
Table 7 List of suggested new EnPIs which can be developed through available data in
STAMA cells ........................................................................................................................... 53
Table 8 List of suggested new EnPIs in STAMA cells ........................................................... 54
Table 9 List of suggested new EnPIs for support processes for the industry .......................... 55
Table 10 Results of social sustainability survey ...................................................................... 56
Table 11 Social Sustainability score matrix............................................................................. 57
Table 12 Improvement suggestions in social sustainability survey ......................................... 58
Table 13 Material removal ....................................................................................................... 75
Table 14 Operation and lead time ............................................................................................ 76
Abbreviations
SM Sustainable Manufacturing
VSM Value Stream Mapping
SUS-VSM Sustainable Value Stream Mapping
IEA International Energy Agency
PA Packaging
EnPI Energy Performance Indicator
FSSD Framework for Strategic Sustainable Development
SSD Strategic Sustainable Development
IPCC Intergovernmental Panel on Climate Change
GHG Green House Gas
KPI Key performance Indicator
EEM Energy Efficiency Measures
EE Energy Efficiency
EB Energy Baseline
EHS Environmental Health and Safety
1
1. Introduction
The report by UN Intergovernmental Panel on Climate Change (IPCC) has highlighted about
the fact that the increase in global greenhouse gas emissions is rapidly altering the climate. It
states that the average global temperature will reach the threshold of 1.5 ℃ above pre-industrial
levels by 2030. Thus, causing various problems like desertification, increasing sea levels,
reducing food production etc. Energy demand reductions, decarbonization of electricity and
other fuels, electrification of energy end use etc. are some of the mitigation pathways. The
demand of low energy and land- and GHG-intensive use goods contribute towards limiting the
warming to as close to 1.5 ℃ (IPCC, 2018). The tool manufacturing industry, mining and
quarrying industries use about 49,081 GWh, while the total electricity use is 171,862 GWh
(SCB, 2018). This is about 28% of the total use, thus turning out to be a significant contribution
and a considerable share of the energy supplied worldwide.
Sweden is on track to meet its energy target to reduce the energy intensity of the economy by
at least 20% from 2008 to 2020 (International Energy Agency, 2019). The target of a reduction
of 50% by 2030 also seems to be feasible albeit further improvements are required to achieve
it (Ibid.). The energy intensity depends on the structure of the economy and the structural
changes in energy-intensive industries can potentially have a large impact on a country’s
performance (Ibid.).
Sustainable development is a hot topic trending across the world in the 21st century. One
popular definition of sustainable development is from the United National World Commission
on environment and Development is “Development that meets the needs of the present without
compromising the ability of future generations to meet their own needs” (Brundtland
Commission , 1987). This definition is based on two key concepts: “needs” which refers to the
essential needs of the world’s poor, to which overriding priority should be given; and
“limitations” which refers to the restrictions imposed by technologies and socio-economic
factors on the ability of the environment to meet the needs of present and future generations.
Figure 1 The three dimensions of sustainability (Sonnemann, et al., 2015)
2
To achieve long-lasting sustainable development in an organization, there is a need to balance
environmental, economic and social sustainability factors in equal. The three dimensions of
sustainability are defined as follows.
• Environmental Sustainability:
Environmental sustainability means that we are bounded within the means of our
natural resource. To achieve true environmental sustainability, there is a need to ensure
that the use of natural resources like materials, energy fuels, land, water etc. are at a
sustainable rate or by circularity. There is a need to consider material scarcity, the
damage to environment from extraction of these materials and if the resource can be
kept within circular economy principles (Circular Ecology, 2020).
• Economic Sustainability:
Economic sustainability refers to the need for a business or country to use its resources
efficiently and responsibly in order to operate in a sustainable manner to consistently
produce an operational profit. Without the operational profits, businesses cannot sustain
its activities. Without responsible acting and efficient use of resources, a company will
not be able to sustain its operations in the long run (Ibid.). Being economically
sustainable would help to build long lasting economic models.
• Social Sustainability:
Social sustainability refers to the ability of society or any social system to persistently
achieve a good well-being. Achieving social sustainability would ensure the social
well-being of a country, an organization or a community can be maintained in the long
run (Ibid.). From a business perspective, it is about understanding the impacts of
corporations on people and society (ADEC Innovations, 2020).
The thesis primarily focuses on the environmental sustainability and economic sustainability
dimensions which is in relation to energy use tracking and how it can be made more efficient.
The tracking helps the case company to evaluate its greenhouse gas emissions and potentially
reduce it in the future through energy efficiency or other sustainability improvements. This will
in turn present an opportunity to generate operational profits in the long term while also
incorporate sustainable values, thus maintaining the interests of stakeholders and customers.
While the social sustainability dimension is briefly touched upon which reflects the well-being
of employees working in the organization. The bottom-line of the thesis is to present a case
study of a tool manufacturing company linking the three topics. The following chapters present
the problematization of thesis, objectives and research questions, delimitation set by authors
and case company background.
1.1. Problematization
Minimization of environmental impact is getting progressively significant inside
manufacturing sector as customer, suppliers and customers demand that manufacturers
minimize any negative environmental effects of their products and their respective operations
(Klassen, 2000). Managers play an imperative part in deciding the environmental effect of
assembling manufacturing operations through decisions of crude materials utilized, energy
used, toxins radiated, and wastes generated (Ibid.). In the course of recent decades, theoretical
thinking on environmental issues have gradually extended from a restricted spotlight on
3
contamination control to incorporate a huge arrangement of the board choices, projects and
technologies. In this 4th industrial revolution most of the organizations want to increase the
productivity, while the environmental burdens are the major challenges for them. Increasing
rate of carbon footprint in the production facility and other supply process involved in the
complete manufacturing process is a major problem. Structural industrial changes hold quite a
lot of potential for industrial manufacturing companies in their pursuits of becoming more
sustainable. Decreased energy use and increased energy efficiency are two possible ways to
achieve increased sustainability. Sustainable manufacturing in the tool manufacturing industry
could offer a potential solution to achieve this goal.
1.2. Need of sustainable manufacturing in tool manufacturing industries
Manufacturing is experiencing a significant progress period. The presentation of applied
autonomy and robotics, 3D printing, and a changing worldwide economy have created
tremendous changes in the business, and these progressions give no indication of easing back
down (Pivot International, 2020). There is another area where manufacturing is encountering
changes, i.e. sustainability. While sustainability in manufacturing industry has been a subject
of enthusiasm for the area for a considerable length of time, as of late makers have started
looking unquestionably more truly at how to manufacture in an increasingly productive,
environmentally-friendly manner (Pivot International, 2020). Many industries consider
“sustainability” as an important aspect in their operations for increasing growth, global
competitiveness and brand awareness (Gray, 2020). Apart from that some key benefits to
sustainable manufacturing are:
• Improve operational efficiency
• Cost and waste reduction from the production process
• Long haul business feasibility and achievement
• Lower administrative consistence costs
• Improved deals and brand acknowledgment leading to more prominent access to
financing and capital
Sustainability implies working with an eye toward what's to come. Manufacturing in a
sustainable manner is a way to indicate that less environmental harm results from the
manufacturing procedure, and that is consistently something worth being thankful for (Pivot
International, 2020). Sustainability is actually very basic: If you utilize less assets today, the
industry will have more for tomorrow - regardless of whether "tomorrow" signifies quite a
while from now. It's simple for most of the manufacturing industry to think about "the
environment" as a theoretical formulation, however manufacturers know better, managing as
they do in crude materials. As assets become rare, costs go up (Ibid). Sometimes, manufacturers
need to begin utilizing substitution materials (Ibid). These issues can make logistical issues,
also an expansion in costs - and these issues can rapidly swell into significant issues for your
organization (Ibid). As the Harvard Business Review reports, organizations that focus on
sustainability early will end up in front of the pack (Nidumolu, et al., 2009). Sticking to the
strictest environmental consistence guidelines instead of the most indulgent, for instance, can
permit an organization to discharge feasible items a few item cycles in front of their rivals. This
makes an undeniable upper hand, setting the up the manufacturer to remain in front of those
competitors for quite a long time to come (Ibid).
4
1.3. Objective and Research questions
The purpose of this thesis is to understand what affects the energy use most in the
manufacturing processes such as the use of compressed air and cutting fluid as well as machine
and method choices for a tool manufacturing company. This will facilitate a prioritization of
improvement areas in the future. There is also a need to study social aspects to understand the
conditions for implementing new sustainability measures within the case company. Since
sustainability stands on three different pillars, where one of them is concerned with the social
aspect. Primarily this study is focused on five main objectives i.e. to do a study of energy use
in a modern engineering industry (from a sustainability perspective); mapping energy use in
the tool manufacturing plant, to create comparable measurement figures for the various energy
sources of the machines; to develop a model for how to calculate the total energy cost for
manufacturing a certain product item in a product from a sustainability perspective; and to look
into the social sustainability point of view (Sandvik Coromant, 2019).
To address the problem, an investigation around the following research questions will be
presented in this Master thesis:
RQ 1. How can energy use be studied, mapped and its efficiency be improved in a tool
manufacturing industry?
RQ 2. How can EnPIs and energy cost tool be developed and implemented in a tool
manufacturing industry?
RQ 3. How can social sustainability be measured and improved in a tool manufacturing
company?
The research questions will be answered in the following way:
Regarding RQ 1, a bottom-up energy audit along with Sus-VSM is implemented in this study.
The first phase of the audit is survey, followed by energy analysis and energy efficiency
measures. The audit helps to study the energy use as well as leads to the suggestion of energy
efficiency measures based on current use. While Sus-VSM complements the audit to map the
energy use of different energy carriers for four prioritized products in production line. This
reflects the environmental sustainability as it would help the case company to reduce energy
use and equivalent GHG emissions in the future.
RQ 2 involves the development of new EnPIs and an energy cost tool. The proposed EnPIs for
the support and production processes helps to support energy related decision making or future
investments. The energy cost tool incorporates the production and facility in its calculation of
cost of manufacturing, energy use and GHG emissions. The two aspects eventually reflect the
economic sustainability as well as supports environmental sustainability.
With regards to RQ 3, it involves conducting a survey with ten explicit statements to study the
working environment of case company. The statements present an opportunity to investigate
and suggest improvements in their respective areas if required. This research question reflects
the social sustainability viewpoint, thus completing the triad.
As this research is focusing on the three parameters of sustainability, the research questions
were designed accordingly. The 1st research question covers the environmental perspective.
The 2nd research question supports environmental as well as economic perspectives. The 3rd
5
research question satisfies the social perspective of sustainability. The focus of the study has
been more on strategizing than on tools and techniques that facilitate implementation of energy
intensity-reducing measures.
1.4. Delimitation
Sustainable manufacturing is a broad concept which has different aspects to it like
manufacturing technologies, product lifecycles, value creation networks and global
manufacturing impacts (Bonvoisin, et al., 2017). The researchers in this study have confined
the scope only till manufacturing technologies perspective and briefly touched upon the value
creation networks. The Sus-VSM, energy audit, EnPIs fall under the category of the prior while
the social sustainability falls under the category of the latter. The delimitations were considered
based on the objectives and purpose described by the case company. Apart from this, no
specific or direct limitation was set by the researchers on the study.
1.5. Case Company description
This chapter is an empirical contextualization of a progressively tight investigation of the case
company AB Sandvik Coromant, Gimo. This sections briefs about the Sandvik Groups’
structure, glorious history (Both Sandvik Group and Sandvik Coromant), Sandvik Coromant’s
sustainable work, sustainable objectives, current and future sustainable challenges in the
manufacturing area. This also includes a basic analysis of Sandvik Coromant’s annual and
sustainable historical reports. This empirical study background study concludes with a detailed
analysis of the need of sustainable manufacturing in Sandvik Coromant and the tool
manufacturing companies.
1.5.1. About Sandvik Group
The Sandvik Group was established in 1862 by Göran Fredrik Göransson, who was first on the
planet to prevail with regards to utilizing the Bessemer strategy for steel creation on a modern
scale (Sandvik, 2020). At a beginning period, tasks concentrated on high caliber and included
worth, interests in R&D, close contact with clients, and fares. This is a methodology that has
stayed unaltered as the years progressed. As ahead of schedule as the 1860s, the item run
included drill steel for rock-penetrating (Ibid). The organization's posting on the Stockholm
Stock Exchange occurred in 1901. The manufacturing of hardened steel started in 1921 and
cemented carbide in 1942. Manufacturing of cemented carbide apparatuses started during the
1950s in Gimo, Sweden. Sandvik Group has three major business areas such as Sandvik
Machining Solutions (SMS), Sandvik Mining and Rock Technology (SMRT) and Sandvik
Materials Technology (SMT) (Ibid).
Sandvik has persuaded that sustainability is a genuine business advantage and a driver that
upgrades Sandvik's competitiveness. Most of the clients need to work with feasible providers.
Investors and Shareholders are setting sustainable guidelines to put resources into
organizations. By aligning the presentation of Sandvik's new financial objectives with its
sustainability objectives the organization needed to underline the significance of long-term
sustainable goals. Sandvik takes a comprehensive perspective on the sustainability objectives.
It thinks about its operations, supply chain and customer offerings with specific targets for each
6
of them that complement each other, and the organization continually attempting to see the full
picture and have the greatest constructive outcome.
Figure 2 Different divisions of Sandvik group
Sandvik Machining Solutions fabricates all types of tools and tooling frameworks for cutting
edge metal cutting (Sandvik, 2020). The business zone involves a few brands that offer their
own items and administrations, for example, Sandvik Coromant, Seco Tools, Dormer Pramet
and Walter (Ibid).
Sandvik Mining and Rock Technology supplies gear, devices, administration and backing for
the mining and development ventures (Sandvik, 2020). The major business areas of SMRT is
rock penetrating and cutting, crushing and screening, loading and hauling,
burrowing/tunneling, quarrying and demolition work (Ibid).
Sandvik Materials Technology creates and makes items produced using propelled hardened
steels and uncommon alloys, including cylindrical items, metal powder, strip and items for
mechanical warming (Sandvik, 2020).
1.5.2. About Sandvik Coromant
The tool manufacturing company in the present study is AB Sandvik Coromant in Gimo,
Sweden. It was established in 1942. The company is a world leader in manufacturing cemented
carbide tools like turning, milling and drilling in metallic materials (Sandvik Coromant, 2020).
It has around 1500 employee, making it a large-scale enterprise. There are various industrial
solutions in the following sectors: Aerospace, Automotive, Die & mould, Medical, Oil and gas,
Power Generation and Wind Power (Ibid).
Sustainable business is one of its primary focus. The company intends to have customers to cut
faster or use the tools longer than in the past (Sandvik, 2019). It continues to improve circularity
for customers through recycling and buy-back programs for the used tools. Another focus is on
raw materials and the packaging which will reduce CO2 emissions and increase circularity. The
commitment has led to 80% circularity through the buy-back program (Sandvik Coromant,
7
2020). It implements green factory and sustainable facilities concept where the efforts lead to
reduction in cost, energy and CO2 emissions. The emissions have been consistently monitored
over the past few years which has led to 20% reduction overall (Ibid.).
The production in Gimo is divided into two factories – manufacturing of cemented carbide
inserts and tool holders. Sandvik Coromant’s biggest customers are the metal, automotive and
aerospace industries. The plant works with cutting edge technology for the manufacturing of
products. Hence, there is a constant need to adapt to new technologies and to find more efficient
ways to produce the tools.
2. Theoretical framework This chapter presents the theoretical fundamentals covered in the thesis study. It consists of
sub-chapters for each theme relevant to the study.
2.1. Sustainable Manufacturing
Sustainable manufacturing is defined as “the integration of processes and systems capable to
produce high quality products and services using less and more sustainable resources (energy
and materials), being safer for employees, customers and communities surrounding, being able
to mitigate environmental and social impacts throughout its whole life cycle (Machado, et al.,
2019). Various definitions have been proposed to characterize the word ‘sustainability’. For
example, sustainability has been characterized by previous Prime Minister of Norway Gro
Harlem Bruntland as the casing work where in the necessities of the present age are met without
trading off the capacity of people in the future in meeting their prerequisites (Jawahir, 2008).
Some of the reasons companies are pursuing sustainability in manufacturing are: to increase
operational efficiency by reducing costs and waste; to respond to or reach new customers and
increase competitive advantage; to protect and strengthen brand and reputation and build public
trust; to build long-term business viability and success; to respond to regulatory constraints and
opportunities (EPA, 2018).
It is imperative to discuss about the overall context about Sustainable Manufacturing in general
to get a wider perspective. Bonvoisin et al. (2017) defined sustainable manufacturing solutions
in four dimensions with overlapping scopes which they identify in literature as “layers”. They
discuss the layers as follows.
8
Figure 3 Classification of sustainable manufacturing, Bonvoisin et al. (2017)
Based on the above classification of layers, it can be said the focus of this thesis falls somewhat
under the first category of “Manufacturing technologies” and also briefly under “value creation
network”. This is since the core theme in the case study is about tracking energy use in the
production line and suggestions to improve energy efficiency while also analyzing social
sustainability dimension.
2.2. Energy Auditing
Abdelaziz et al. (2011) defined energy audit as “an inspection, survey and analysis of energy
flows for energy conservation to reduce the amount of energy input into the system without
negatively affecting the output”. It is a method which helps in proposing possibilities to reduce
energy expenses and carbon footprints, thus becoming a key point in the area of energy
management. The energy audit, for an organization, helps to understand, quantify and analyze
the utilization of energy. The detection of waste takes place as well as it identifies critical points
and discovers opportunities where the energy use can be potentially reduced. Through the
means of eco-efficient and feasible practices as well as energy conservation methods, overall
energy efficiency of the organization will be more profitable. This in turn would lead to reduced
energy costs (Saidur, 2010).
According to Vogt PE et al. (2003), there are two distinct and fundamental approaches to model
a facility’s energy use: top-down and bottom-up. The requirements of bottom-up model are
metering installation and an exhaustive inventory of all facility equipment, as well as the energy
use pattern of each facility device. It is necessary to sum the energy use of all facility’s
equipment in order to determine a facility’s total energy use. While the top-down model uses
the high-level information that a facility regularly collects regarding its activities and
performance and further associating that data with the corresponding energy use. Sathaye and
Sanstad (2004) state that the fundamental difference between the two audit methods is the
perspective taken by each on consumer and firm behavior and the performance of markets for
energy efficiency.
Manufacturing technologies
• How things are manufactured
• Where the research is oriented based on processes and equipment, development of new or improved manufacturing processes, maintenance of equipment, determination of process resource use, process simulations and energy efficiency of building.
Product lifecycles
• What is to be produced
• Where the research is primarily based on product (good or service).
• The linked discipline is product design aspects like product lifecycle management, intelligent product, product sustainability assessment.
Value creation networks
• Organization context
• Where the research is oriented based on companies or manufacturing networks.
• Examples of the approaches include resource efficient supply chain planning, industrial ecology.
Global manufacturing impact
• Mechanism context
• Where the research exceeds the conventional scope of engineering.
• Examples of approaches include development of sustainability assessment methods, education and competence development, development of standards.
9
While performing an energy audit, it is important to identify unit processes. Unit processes are
used to divide the energy use of an industry into smaller parts. They are defined by the energy
service to be performed and are further divided into two categories: Production processes and
support processes (Rosenqvist, et al., 2012). The unit processes are general for all industries,
thereby provides an opportunity for comparison of a given unit process between different
industries or businesses. Sommarin et al. (2014) put forward two approaches in order to
perform a bottom-up energy audit, first one being ‘The Unit Process-approach’ and the second
being ‘The KPI-approach’. The latter approach is divided into three different levels.
• Overall figures like MWh/ton, kWh/m2, MWh/turnover etc.
• Support process-specific figures like ventilation, compressed air etc.
• Production process-specific figures such as melting, moulding etc.
The Unit Process-approach for bottom-up audit is adopted for the thesis. The first part of an
audit is setting up an energy balance diagram (Sommarin, et al., 2014). Using the unit process
categorization method, a general way of structuring data is obtained. A unit process is based
on the purpose of a given industrial process for example cooling, drying, internal transport etc.
(see Table 1) (Ibid.). There are three parts of an audit: Energy survey, Energy analysis and
Suggested measures (see Figure 4) (Rosenqvist, et al., 2012). Energy survey phase defines the
system boundary, identifies unit processes, quantifies energy supply and allocates energy to
unit processes. Energy analysis phase identifies problems within systems, idling, outdated
technologies, assesses potential for energy efficiency. Suggested measures identify possible
solutions to the problems, calculates impact of the solutions by analysis and evaluates
economic impact (Ibid.).
Table 1 Structure of unit processes categorization (SÖDERSTRÖM, 1996)
Production process
Disintegrating
Support process
Ventilation
Disjointing Space heating
Mixing Lighting
Jointing Pumping
Coating Tap water heating
Moulding Internal Transport
Heating Cooling
Melting Steam
Drying Administration
Cooling/freezing
Packing
10
Figure 4 Energy Audit process developed by (Rosenqvist, et al., 2012)
2.3. Energy Efficiency
Energy efficiency is defined as “the ratio of useful energy or energy services or other useful
physical outputs obtained from a system, conversion process, transmission or storage activity
to the input of energy” (IPCC, 2018). The 2012 Energy Efficiency Directive (2012/27/EU) set
of binding measures for the European Union to reach 2020 energy efficiency target. The target
here is defined as “20% reduction of energy use (in primary and final energy) compared to the
business-as-usual projections”. There was further increase in the target which proposed to
target 32.5% energy savings compared to a reference case, with a clause for an upwards
revision by 2023. The EED Article 8 states “large enterprises in all EU member countries must
conduct energy audits every four years, starting from December 2015”. This was established
in Sweden in 2014, through the law on Energy Auditing of Large Companies (2014:266). It
states the first audit should be done in the four-year period 2016-19. The Swedish government
introduced “Energisteget” (the Energy Step) which is a programme to support implementation
of energy efficiency measures. The large companies that have carried energy audits in
accordance with EED requirements may apply for financial support to invest in energy
efficiency measures. The total budget for the program is around SEK 125 million for the years
2018-20 (International Energy Agency, 2019).
Sorrell et al. (2000) and Palm and Thollander (2010) discussed about the barriers for the
adoption of cost-effective energy efficiency measures in industry which can be categorized into
three factors: economic, behavioral and organizational. Cagno et al. (2013) have extended this
categorization and further divided the barriers into technology-related, organizational,
information, economic, behavioral, market, competence, awareness and government/policies.
There has also been attempts to categorize the driving forces for improved energy efficiency.
Thollander and Ottosson (2008) in their research, categorized driving forces into market
related, current and potential policy instruments, and organizational and behavioral factors.
Thollander et al. (2013) categorized these driving forces into financial, informational,
organizational and external and organizational and behavioral factors. Trianni et al. (2017)
further conducted a recent study where they classified the driving forces according to the type
of action the driving force represents, for instance, regulatory, economic, informative and
vocational training.
11
2.4. Value Stream Mapping
Value Stream mapping (VSM) is an important technique used in lean manufacturing to identify
waste, by adapting, as necessary, for green and sustainable manufacturing (Faulkner &
Badurdeen, 2014). A value stream is defined as “all the actions, both value added and non-
value added, currently required to bring a product through the main flows essential to every
product: the production flow from raw material into the arms of the customer, and the design
flow from concept to launch” (Rother & Shook, 1999). Value stream mapping can be utilized
to improve any procedure where there are repeatable advances. They would then be able to
stop the line to take care of that issue and get the procedure streaming once more (Mukherjee,
2019). Table 2 presents a comparison of criteria considered in traditional VSM and Sus-VSM.
Table 2 Comparison of Traditional VSM and Sus-VSM (Bown, et al., 2014)
Type of waste/issue Traditional VSM Sus-VSM Metric type
Time waste + + Economic
Raw material waste - + Environmental
Process water waste - + Environmental
Energy waste - + Environmental
Job hazards - + Societal
Ergonomics - + Societal
Note: + sign indicates inclusion and - sign indicates exclusion.
Lean manufacturing instruments don't think about environmental and societal benefits
advantages. The prosaic value stream mapping (VSM) system looks at the financial matters of
an assembling line, a large portion of which are with respect to time (process duration, lead
time, change-out time, and so on.) (Hartini, et al., 2018). Consolidating the capacity to catch
environmental and societal execution outwardly through VSMs will build its handiness as an
apparatus that can be utilized to evaluate producing tasks from a sustainability viewpoint.
Various investigations have tended to the augmentation of VSM to fuse extra rules. Majority
share of these endeavors have concentrated on adding vitality related measurements to VSMs,
while a few different examinations allude to 'practical' VSM by remembering natural execution
for ordinary VSMs (Hartini, et al., 2018) . This examination has built up a technique for VSM
coordinated with condition metric and social measurement for ensuring sustainable
manufacture (Ibid).
Sustainable VSM recently created has a general arrangement of measurements that will have
wide application across numerous enterprises. In any case, further customization might be
expected to evaluate explicit parts of different organization (Ibid). In general, the sustainable
VSM (Sus-VSM) is normally used to evaluate economic, environmental and social
sustainability performance in manufacturing industry. In order to evaluate the, existing
measurements for sustainable manufacturing execution appraisal are analyzed to recognize
basic rules and measurements to be included for the Sus-VSM (Faulkner & Badurdeen, 2014).
2.5. Cost tool in manufacturing
According to Nord et al. (2015), in order to develop a cost model for an optimized
manufacturing company, the operation time, type of operations and carrier used should be
considered. Since it might have incredible impact on energy use in the production unit. Along
these lines, it is essential to dissect energy use in the production unit for an appropriate analysis.
12
To empower simple energy planning, leasing, and structure, it is important to have accessible
tools and techniques for energy use prediction based on the driving factors. In that manner, a
production company could budget the energy cost and plan various operations for different
products. For instance, guideline part examination is utilized to recognize significant factors of
vitality use in low energy utilization tasks. Basic direct relapses between day by day or month
to month vitality use and total energy use show great fitting outcomes solid for a further
examination (Ibid).
2.6. Energy Performance Indicators
When it comes to Energy Performance Indicators (EnPIs), it is important to know what it
implies. “Energy Performance Indicator (EnPIs) is a measure of energy intensity used to gauge
the effectiveness of your energy management efforts” (50001 Store, 2020). EnPIs are used to
understand energy performance corresponding to energy use and energy efficiency (EE) (ISO,
2020). Thus, playing a vital role in evaluating efficiency as well as effectiveness of Energy
Efficiency Measures (EEM). The implementation and monitoring of EnPIs is imperative to
support energy related decision making. EnPI and energy baseline (EB) represent two key
interlinked elements enabling measurements pertaining to EE, use and performance. EnB forms
the basis to quantify the energy performance before and after the implementation of
improvement actions. Figure 5 represents the relation between EnPI, EnB, energy target and
measurement of performance before and after implementation (Ibid.).
Figure 5 Concept of energy performance indicators (EnPI) in baseline period and implemented period (ISO, 2020)
Based on characteristics, there are four types of EnPIs according to ISO 50006 and IEA reports:
energy use, simple ratio, statistical modeling and simulation modeling used for EE
improvement (ISO, 2020; Shim & Lee, 2018). Energy use is “using the total energy use over a
period of time” for instance kWh, GJ etc. (Ibid.). Energy intensity is an example of single ratio
which is defined as “rate of energy use per unit activity data” like specific energy use (SEC),
energy use (kWh) per production (ton) (ISO, 2020; Shim & Lee, 2018; Lawrence, et al., 2019).
A statistical model could be a linear regression model or a non-linear regression model (Shim
& Lee, 2018). A simulation model can be applied over each boundary to measure the
improvements in EE as well as energy performance (Ibid.). There are three primary EnPI
boundary levels according to ISO 50006: individual, system and organizational (ISO, 2020).
Organizational level represents major interactions between departments, total energy use,
related expenses and overall performance (Schmidt, et al., 2016). System level refers to the
evaluation of process line level where a comparison can be drawn with similar processes if
possible. EnPIs on individual level are usually done for a detailed assessment of energy use
13
and related cost per manufacturing step or equipment level (Ibid.). One other categorization
according to REF divides into three explicit levels: overall figures, support process-specific
figures and production process-specific figures (Thollander, et al., 2014).
2.7. Social Sustainability
Social Sustainability is about identifying and managing business impacts considering both
positive and negative impacts on people (United Nations Global Compact, 2020). The quality
of a company’s relationship along with engagement with its stakeholders is deemed to be
critical (Ibid.). Whether directly or indirectly, companies affect what happens to its employees,
working professionals in the value chain, customers and local communities. And it is
imperative to manage these impacts proactively (Ibid.).
According to Woodcraft (2015), social sustainability is another strand of talk on sustainable
development. It has created over various years because of the predominance of ecological
concerns and technological arrangements in urban turn of events and the absence of progress
in handling social issues in urban areas, for example, disparity, displacement, livability and the
expanding requirement for reasonable housing (Ibid.). Even though the Sustainable
Communities strategy plan was presented in the UK a decade prior, the social elements of
sustainability have been to a great extent ignored in discussions, arrangement and practice
around sustainable urbanism. There is a developing enthusiasm for comprehension and
estimating the social results of recovery and urban advancement in the UK and globally. A
little, however developing, development of engineers, organizers, designers, lodging
affiliations and neighborhood specialists pushing an increasingly 'social' way to deal with
arranging, building and overseeing urban communities. This is a piece of a global enthusiasm
for social sustainability, an idea that is progressively being utilized by governments, open
offices, arrangement producers, NGOs and organizations to outline choices about urban turn
of events, recovery and lodging, as a feature of an expanding strategy talk on the supportability
and strength of urban areas (Ibid).
There is an increasing awareness among customers and stakeholders of organizations to think
about the product as well as process from a sustainable perspective right from the early stages
of manufacturing (Digalwar, et al., 2020). This global demand from the businesses and
customers initiates the need to develop methodology for sustainability assessment for
manufacturing organizations (Ibid.). Scientists argue that organizations are important actors for
creating wellbeing for the society as well as environment (Fobbe, et al., 2016). The roles of
organizations are evident when looking at the impacts of financial crisis on society. For
instance, the financial crisis of 2008 lead to austerity programs, thus affecting the social
element of communities. Thus, employment, income levels, quality of life and work
determined by the companies have an impact on social framework even beyond the economy
(Ibid.).
One of the most real and predictable drivers for industry is sustainability. This theme opens at
various issues as per the three manageability columns: condition, monetary, and social. With
respect to last one, there is a need for strategies and instruments (Papetti, et al., 2018). As the
fourth industrial revolution is progressing, so this is a second test for ventures that should be
serious decreasing their opportunity to showcase coordinating new advancements on their
creation destinations. From these points of view, the social sustainability in a workplace is
14
planned for featuring the job of the people under the Industry 4.0 worldview. Another
transdisciplinary technique to support the sustainable manufacturing is social sustainability. It
permits structuring an associated domain (IoT system) planned for estimating and advancing
social sustainability on creation destinations. The work additionally comments the connection
between social sustainability and productivity. In fact, streamlining the human works grants to
improve the nature of the working conditions while improving proficiency of the production
work. The contextual investigation was performed at an Italian sole maker. The objective of
the investigation was to improve and enhance the completing zone of the plant from a social
perspective with the point of view of computerized producing (Ibid).
3. Literature Review
This chapter intends to look further at the bodies of literature that have emerged around the key
theoretical concepts. It gives a picture of what is sustainable manufacturing and for what reason
is it significant for organizations. Likewise, brief overview of different factors and practices
utilized for this study has been introduced. To conduct the thesis successfully, it was important
to carry out a literature review of the topics mentioned in the previous chapter. The literature
review chapter consists of existing theories in the following order: sustainable manufacturing,
energy auditing, energy efficiency, Value Stream Mapping (VSM), energy cost tool, social
sustainability and energy performance indicator (EnPIs). By implementing this, the focus of
the research was specified keeping the project objectives as a reference. The following are parts
that describe the approach, the methods for data collection, the structure and the quality of the
report.
Figure 6 Funneling structure for literature review
15
3.1. Sustainable Manufacturing
The environmental concerns have become exponentially inferable from the expanding
utilization of characteristic assets and contamination. Subsequently, to address the previously
mentioned concerns it gets essential to effectively execute the sustainable manufacturing
frameworks (Zindani, et al., 2020). Successful evaluation can be made by giving the necessary
qualitative and quantitative data. Particular divisions arranged to sustainability must be worked
inside an association to advance the improvement of sustainable culture (Ibid.). Procedures
must be set up to guarantee the utilization of the methodologies and the targets for sustainable
association.
Cherrafi et al. (2016) reviewed and analyzed several literatures to integrate three management
systems in a model i.e. lean manufacturing, Six sigma and sustainability. ‘Sustainable
manufacturing’ and ‘Lean Sustainable Manufacturing’ were used as keywords in their searches
among others. They identified seven major gaps relevant in this direction: “the need to develop
an integrated metrics and measurement system to measure lean/Six Sigma and sustainability
performance; the need to develop an integrated model applicable to many industries and
functions; the need to focus more on the context of SMEs to assist them to successfully
implement lean/Six Sigma and sustainability; the need to investigate the applicability of
lean/Six Sigma and sustainability to the service industry; the need to study the human side in a
more comprehensive manner, the need to study how to extend the implementation of lean/Six
Sigma and sustainability to emerging and underdeveloped countries, and the need to cover the
pre-implementation phase” (Ibid.).
A systematic review was done by (Machado, et al., 2019) which was intended to identify how
sustainable manufacturing is contributing towards the development of Industry 4.0 agenda and
to gain a broad understanding about the links between the two. Their research suggests that
concepts of sustainable manufacturing can support the implementation of Industry 4.0 in the
following aspects: “developing sustainable business models; sustainable and circular
production systems; sustainable supply chains; sustainable product design; and policy
development to ensure the achievement of the sustainable goals in the Industry 4.0 agenda”
(Ibid.).
3.2. Energy Audit
Vogt PE et al. (2009) discussed the advantages and disadvantages of top-down and bottom-up
energy modelling techniques. The results from their research showed that the top-down model
is preferred on the “basis of cost, time to construct, model operation, model maintenance effort,
accuracy etc.” (Ibid.). They suggested that accuracy of either model is about the same (plus/
minus 5%) where the errors using the bottom-up model could appear from: “the estimates
required by numerous small loads not justifying metering; meter malfunctions; meter reading;
data collection and entry and unknown unlisted equipment additions and deletions”.
Backlund and Thollander (2015) examined the suggested and implemented energy efficiency
measures from energy audits conducted within the Swedish energy audit program. Their
research found that the largest potential for energy efficiency improvements found in audit
reports is in the support processes such as space heating and ventilation. This was applicable
to manufacturing as well as non-manufacturing firms. They also found that the implementation
rate of the suggested energy efficiency improvement measures is 53% while 47% being the
16
implementation gap (Ibid.). Andersson et al. (2016) presented a literature review of the then
present incomparability between energy audit policy programs due to differences. They
concluded that important elements such as the free-rider effect and harmonized energy end-use
data should be defined and included in the evaluation studies. They also concluded more
consistency is needed in how categorizations of EEMs are made (Ibid.).
3.3. Energy Efficiency
The Energy Policies of IEA Countries for Sweden (2019) report recommends that the
government could complement the adopted targets with a different metric to better capture
improvements in energy efficiency in the final use. It also further states the energy efficiency
targets should be aligned with Sweden’s climate targets ensuring with actions that energy
efficiency effectively helps reduce emissions. The government also should regularly assess the
contribution of taxation on energy efficiency improvements and ensure it is sufficient to
incentivize energy efficiency further in order to fulfil the energy savings requirements for 2030
(International Energy Agency, 2019).
Energy efficiency for a machine tool, is affected by intrinsic characteristics and processing
conditions (Zhou, et al., 2016). The energy efficiency for energy losses such as motor loss,
mechanical loss and hydraulic system etc. if affected by intrinsic characteristics. While from
the perspective of machining process of machine tools, reactive power losses affect energy
efficiency mainly for real output like standby energy use, air cutting energy use, reactive power
use of acceleration and deceleration etc. that are related to inertia force. (Zhou, et al., 2016)
categorized the existing energy use models into three: 1) the linear type of cutting energy use
model based on Material Remove Rate (MRR), detailed parameter of cutting energy use
correlation models and 3) process-oriented machining energy use model. They drew two major
conclusions for future study: 1) through introduction of correlation analysis of machine tools,
parts, tools and processing conditions, accuracy of current energy use models could be
improved, 2) more scientific evaluation system is required for the assessment and test of
machining tools energy efficiency.
Mert et al. (2015) presented how services can improve the energy efficiency of a machine tool
based on a case of machine tool manufacturer. They identified existing and potential services
to increase the energy efficiency of machine tools. The existing services are: Process
consulting, training, condition monitoring, retrofit; the potential services are commissioning,
training, hotline service, maintenance agreement, spare part supply, retrofit.
3.4. Energy Management
To have a successful in-house energy management practice, Johansson and Thollander (2018)
outlined ten factors. The factors included are:
• Top-management support;
• Long-term energy strategy;
• A two-step energy plan;
• An energy manager position;
• Correct energy cost allocation;
• Clear KPIs (Key Performance Indicators);
17
• Energy controllers among floor-level staff;
• Education for employees;
• Visualization and Energy competition.
They state these factors should not be a replacement for energy management standards but as
a method or tool to achieve the outlined factors for success. Their paper was carried out in
terms of Swedish context, it remains to be seen if these factors could be generalized to other
countries except Sweden. Paramonova and Thollander (2016) discussed the possibilities for
participation of industries in industrial energy-efficiency networks (IEENs) to overcome
typical industrial energy-efficiency barriers in small and medium enterprises (SMEs). They
suggest that participating in energy-efficiency networks can shift companies’ attention to
behavioral aspects as IEENs contribute towards changing attitudes and behavior by allowing
companies to learn from their own and others’ experiences. While this may be applicable to
most of the cases, but there might be instances where the companies tend to just “green wash”.
It might be so that the companies would participate in these IEENs just for the sake of it while
having no actual implementation on ground. With regards to the change of attitude and
behavior, the top-level management might turn out to be too stubborn and rigid. Thus, refusing
to accept any kind of changes in their working structure. This calls for a need where the data
could be quantified as to how many SMEs participating in the IEENs contribute to meaningful
implementation of measures. It remains to be seen if the suggested IEENs would be applicable
for large scale enterprises and not only SMEs.
3.5. Value Stream Mapping
Value stream mapping is a venture improvement device to help in envisioning the whole
production process, speaking to both material, information and other carrier stream.
Characterized value stream as assortment of all exercises value included just as non-value
added that are required to bring a productor a group of products that utilization similar assets
through the primary streams, from raw material to the end clients (Agarwal & Katiyar, 2018).
Value stream mapping empowers to more likely comprehend what these means are, the place
the worth is included, where it's not, and most critically, how to enhance the aggregate
procedure. Value stream mapping (VSM) furnishes the user with an organized representation
of the key advances and relating information expected to comprehend and wisely make
upgrades that improve the whole procedure, not only one segment to the detriment of another
(Plutora, 2020).
The thesis concentrates on VSM as it identifies which include improvement for big business
programming arrangements using a rearranged cascade system. The thesis alludes to
programming highlights as the "product" being created right now. Unlike procedure maps, or
flowcharts, that show just the means associated with the procedure, a VSM shows essentially
more data and utilizations a totally different, progressively straight configuration (Ibid.).
The way to create basic VSM is all around archived and generally utilized in industry (Rother
& Shook, 1999). Endless articles exist on the utilization of ordinary VSM the survey of which
isn't the focal point of this paper. This approach inspects endeavors to stretch out ordinary VSM
to catch supportability execution. These endeavors can be partitioned into two general classes
(Rother & Shook, 1999):
18
• Studies which are delegated environmental/energy VSM, where the centre is joining
environmental/energy appraisal in VSM.
• Concentrates that are characterized 'sustainable' VSM.
Torres and Gati (2009) broadened the EPA lean and environmental toolkit, which they call
environmental VSM (E-VSM) and approved the technique with a contextual analysis in the
Brazilian liquor and sugar manufacturing industry. The essential center is water utilization at a
definite level by partitioning water misfortunes into inactive, genuine, inherent, utilitarian, and
genuine useful misfortunes. In any case, the visual ID of water squander inside the procedure
through the progression line approach proposed isn't clear. Recognizing the absence of
accentuation on vitality utilization in VSMs, the US EPA therefore made another toolbox for
lean and energy mapping (US EPA, 2007). The utilization of visuals, for example, a vitality
dashboard to imagine if vitality objectives are met is empowered here.
Simons and Mason (2002) proposed a technique called sustainable VSM (SVSM) to upgrade
sustainability in manufacturing by breaking down GHG gas discharges. Even though it is
alluded to as a sustainable VSM, the structure doesn't legitimately consolidate cultural
measurements; they are thought to be fused in a roundabout way by excellence of following
financial or environmental benefits being joined by social benefits. Fearne and Norton (2009)
consolidated the SVSM made by Simons and Mason (2002) with sustainability metrics made
by Norton (2007) to make a reasonable worth chain map (SVCM) method by putting
accentuation on connections and data streams between nourishment retailers and nourishment
producers in the UK. Essential environmental performance indicators (EPI) set by UK
Department of Environment, Food, and Rural Affairs (DEFRA) are to be remembered for the
SVCM while other EPI's are to be chosen by the client dependent on the given procedure and
industry (Norton, 2007).
This approach considered a wide exhibit of environmental metrics, for example, vitality
utilization during the procedure, transportation, and any capacity stages just as water utilization
and material use. The SVCM technique was approved through a contextual analysis of sourcing
and pressing of cherry tomatoes over a year time span; as surveying vitality utilization was
troublesome undertaking, they replace that measurement with information from LCA directed
by Guinee (2002). Likewise, with numerous different examinations, this SVCM, as well,
doesn't consolidate any social metrics; the strategies to quantify the diverse Environmental
Performance Indicators (EPIs) or clear visualization of chosen EPI's isn't addressed.
3.6. Energy Performance Indicators
Kanchiralla et. al (2019) developed a taxonomy for the categorization of EEU and emissions
for the processes as well as identified the intensive processes through analysis of EEU and CO2
emissions in the engineering industry. They presented several potential EnPIs based on system
boundaries like organization, system, process levels for the engineering industry. The study
could not confirm if the results could be extended and generalized to engineering industries
beyond Sweden. Johnsson et al. (2019) investigated potential energy key performance
indicators (KPIs) where the scope of the research was the Swedish wood industry. They
presented currently applied energy KPIs along with their magnitudes while also proposed new
innovative energy KPIs. The authors suggest the findings of their study could be extended to
other countries apart from Sweden which possess prominent wood industry. A framework was
19
proposed by Assad et. al (2019) which predicts energy KPIs of manufacturing systems at early
design and prior to the physical product. This framework was based on implementing virtual
models to predict energy KPIs at three explicit levels: production line, individual workstations
and components as individual energy use units (ECU) (Ibid.). These energy KPIs assist the
system designers in process engineering as well as component selection by having productivity
and sustainability as a reference. A generalized calculation methodology was proposed with a
set of templates to measure energy efficiency of manufacturing activities based on three levels:
factory, process and product (Schmidt, et al., 2016). The study presented a set of templates for
five KPIs:
Table 3 Set of templates to measure energy efficiency (Schmidt, et al., 2016)
Type 1 Energy […] per […]
Type 2 Site energy […]
Type 3 On-site energy efficiency or efficiency
increase
Type 4 Improvement or savings of energy […]
Type 5 Total value of energy […]
Andersson and Thollander (2019) discussed about the barriers and drivers in the utilization on
energy KPIs. The authors ranked the drivers for the development of energy KPIs in their study.
The top 4 ranked drivers are: monitoring energy end-use, energy targets, evaluation of energy
efficiency measures, identification of energy efficiency potential. While they ranked the
barriers of energy KPIs in the following manner: lack of resources, not prioritized, lack of
skills, lack of information, lack of relevant KPIs and too much available data (Ibid.). Their
study was applied in the context of Swedish pulp and paper industry.
3.7. Social sustainability
Schönborn et al. (2018) examined a correlation between corporate social sustainability (CSR)
culture and the financial success of a company. They conducted this study by examining
through a multiple regression analysis of two contrasting European polls, examining items
indicating CSR culture and financial outcomes. Their research showed that there are four
specific success-related social sustainability dimensions of corporate culture which are
predictors of a company being classified as financially successful. These four are:
“Sustainability strategy and leadership; Mission, communication and learning; Social care and
work life; and Loyalty and identification” (Ibid.).
4. Methodology This chapter gives an overview of the methodology adopted for the thesis study. It describes
the research design chosen, research approach undertaken, case data collection approach,
motivation of research methodology and states limitations of the study. The authors tried to
find journal articles which established a relationship between an audit process, VSM and social
sustainability aspect. After analyzing the studied journal articles, the gap in the literature was
identified. To be specific, there was no research found regarding the bottom-up energy audit
approach with Sus-Value Stream Mapping (Sus-VSM) and working environment study of
organization. The ethical and legal considerations are also covered in this chapter.
20
4.1. Literature review
The topic names were used as the keywords for searching the literature. Several academic
journals which were relevant to the topics were searched and analyzed. Science Direct was
primarily used as the database to search the journal articles, while a few articles were searched
in Springer database and Taylor & Francis database. The relevant materials included: official
websites, books, journal articles, reports and conference proceedings. Funneling process was
used which refers to the process of narrowing possible ideas into specific research question or
purpose (Shields , 2014). This helps to narrow down a big picture into manageable research
project (see Figure 6). By implementing this, the focus of the research was specified keeping
the project objectives as a reference.
The Figure 6 represents the theoretical research methodology, where the design of the chapters
with the overall study methodology can be linked to a funnel method at the first stage of the
study. The theoretical research methodology begins with the introduction which includes the
scope of this study and the structure. After that many literatures have been identified and
categorized then the three-research questions were developed.
4.2. Research design
This is a general case study approach. A case study is a research approach that is utilized to
create an inside and out, multi-faceted comprehension of an intricate issue in its genuine setting
(Crowe, et al., 2011).
This research will be done as a single case study. That is, after intensive thought the researchers
locate that a case study would be the most fit research structure. To respond to the research
questions while the researchers can focus and increase profound information inside one explicit
association. In this way a case study is generally appropriate for this study. The outcome of
this study may be not only useful for the tool manufacturing industry but also for the other
manufacturing sector.
As this study was covering a wide area, so there was a continuous data collection process was
going on through meetings, repetitive discussion with the operators and the responsible
managers. The design of the chapters with the overall study methodology can be linked to a
funnel method at the first stage of the study. The following are parts that describe the approach,
the methods for data collection, the structure and the quality of the report. The data collection
phase is concluded for both, energy audit, social sustainability and VSM.
21
4.3. Research approach
Figure 7 Mixed research methods adopted for thesis study
The methodology utilized in this study is abductive, which is more towards deductive
methodology than inductive as this study has significantly been impacted by past investigation
and research. The Figure 7 represents the methodological approach used in this thesis. There
are two sorts of strategies accessible i.e. Quantitative methods relies upon estimations, science,
measurements, reviews or numerical investigation of information while qualitative method
expects to accumulate an inside and out comprehension of an in depth understanding (Bell, et
al., 2019). The quantitative method includes the historical data review and the energy
measurements conducted through the energy audit. The qualitative method includes the social
sustainability survey conducted and the semi-structured interviews in order to get the required
information.
Since the investigation goes to and fro as far as hypothesis and empirical findings the most
proper methodology will comprise of a blend of both deductive and inductive methodologies
(Ibid.). The underlying thought of the applied research approach was the purported deductive
methodology which is a connection among hypothesis and research. Where hypothesis is
building speculation, which is basically examined experimentally (Ibid.).
22
4.4. Empirical case data collection approach
Figure 8 Data Collection
Figure 8 represents the data collection approach for study. Mainly this study consists of two
major data collection approach i.e. primary and secondary data collection. The primary data
collection consists mainly in two ways. The semi-structured interviews and the survey helped
to get the technical information about the production process. The 2nd part of the primary data
collection is energy audit which includes the electricity, compressed air and cutting fluid
measurement. Finally, to assess the working environment of the case company respectively to
know about the working environment a survey has been conducted with a 54-sample size which
was the target audience and received a response from 33 respondents.
The secondary data collection approach is based on the theoretical perspective, which includes
literature review and the historical data. The literature review helped to get some theoretical
input for the study whereas the previous historical data help to get some energy invoices of the
case company. To gather the technical data for the study semi-structured interviews were
directed.
There were two methods used overall – Bottom-up audit, Sus-VSM. Furthermore, energy cost
tool was developed through the data collected in the audit process. The bottom-up audit was
both quantitative and qualitative whereas the Sus-VSM was only quantitative used for mapping
the products. It can be said that the bottom-up audit complements the implementation of Sus-
VSM method. Ultimately, energy efficiency measures were proposed based on the energy audit
which would help the company to plan and invest in the future.
The data collection for the Bottom-up audit and Sus-VSM was interlinked and thus carried out
simultaneously. The data collection has been through conducting meetings and semi-structured
interviews with the employees of at the case company. The term 'semi- structured interview'
that covers a wide scope in qualitative research (Bell, et al., 2019). Semi-structured interview
is best utilized whenever researchers won't get more than one opportunity to talk with
researchers and when researchers will send a few questioners out into the field to gather
information. The Semi-structured interview guide gives an away from of guidelines for
questioners and can give solid, practically identical subjective information (Robert wood
23
Johnson Foundation, 2008). Semi-structured interview is frequently gone before by perception,
casual and unstructured talking to permit the researchers to build up a sharp comprehension of
the subject of intrigue important for creating significant and significant semi-organized
inquiries. The incorporation of close-ended questions and preparing of questioners to follow
significant subjects that may wander from the interview guide does, nonetheless, despite
everything give the chance to distinguishing better approaches for seeing and understanding
the current point (Ibid).
The qualitative semi-structured interviews were conducted based on a pre-decided set of
questions. A sample size of five employees were considered who closely worked with the
departments within the system boundary. Due to the information being sensitive, it is not
possible to enlist a detailed summary of the questions regarding the energy carriers and as to
why exactly they are being used. The details of the interview are presented in the form of a
table which states what energy carrier is being used in which operations (see Appendix 2. Semi-
structured interview template).
4.4.1. Data collection for Bottom-up audit
The energy audit is combined with iterative method as described in (Rosenqvist, et al., 2012).
This is since the actual workflow is not linear but an iterative process. This iteration is stopped
when there is enough data to suggest efficiency measures. This is described as follows in Figure
9.
Figure 9 Iterative process for industrial audit, (Rosenqvist, et al., 2012)
The focus of this thesis was for four products which are turning tools. Thus, the data collection
phase was primarily focused on four products. The operations and material lists were obtained
for all the products. This involved information about the machining codes of operation, name
of operation, time/piece, setup time etc.
The first phase of the audit was Survey. The Survey phase is applicable to both bottom-up
energy audit as well as Sus-VSM method. Before the start of execution, the system boundaries
and scope were defined (Bell, et al., 2019). The active power invoices for the Industrial Area
1 was collected for the year 2018 and 2019, thereby providing an overall picture of the
company. But as mentioned previously, the study was carried out in GVP3 (part of the main
workshop at the case company) inside the workshop ‘V66’, Heat Treatment and Packaging
department. The different machining operations in the manufacturing facility were identified
in the facility. The STAMA (automatic machine based in the V66 workshop in the case
company) machines were fitted with sensors and the data was collected in a separate software
known as PI System Explorer. The energy loggers were inserted for a week inside the SCHMID
(semi-automatic machine based in the V66 workshop in the case company) machine and Heat
24
Treatment. Unfortunately, due to limitations, it was not possible to get the energy use data for
the Packaging. The time interval of one minute was set to get the total energy use in kWh. This
data was collected in a software which was provided in the form of Excel document by the
Electric Department at case company.
The operations ‘Machining 1’ and ‘Machining 2’ are carried out in GVP3 while Heat Treatment
and Packaging have a separate department. The data collection started with the ‘Machining 2’
operation as it is carried out in STAMA machine cells (GVP3) which is connected to various
types of sensors. The data collected from the sensors was readily available in a software called
“PI System Explorer” (see Appendix 1. PI System Explorer). The sensors connected measures
information like energy use, supply and return temperature of cutting fluid, volume of fluid,
volume of compressed air supplied, power use etc.
The collection continued for the ‘Machining 1’ operation next, which takes place in SCHMID
machine cell in GVP3. There are total two SCHMID machines in GVP3. The energy logger
was inserted in SCHMID machine 2 cell for a duration of one week. This monitored the energy
use for the whole week where different work order was processed and manufactured. Further,
the data was collected for the Heat Treatment operations. The energy logger was inserted in
the switch cabinet specific to the operation. This was for one week each for the two operations.
The energy loggers were not kept for Packing operation. Hence, the values for electricity use
for this operation is not available for the different products.
The operation ‘M + ASY’ which refers to Measuring and Inspection, is done manually by the
operators. The case company takes a few samples from the work order and check if the
tolerances are within limits and if the dimensions are appropriate. Hence, this operation does
not use any energy. The invoice of the compressed air was also collected. This comprised of
energy data regarding heating systems, recycling to ventilation, heat that cannot be recycled
and total instantaneous electricity. This monthly invoice was for the year 2017 and 2018. There
are six and four compressors operating at the same time which are installed close to V66
facility. They supply the compressed air to the all the facilities in Industrial Area 1.
The second phase consists of Analysis. The data gathered from the first phase is analyzed
further after the removal of loggers. The data for energy use per piece was also collected for
the different carriers like electricity, cutting fluid and compressed air. Surveying phase helped
in the helped in the identification of unit processes, although the quantification of energy use
specific to its processes was not possible due to them being highly integrated and automated in
the machine cell. The energy use for different work orders is compared as well as for the non-
working week with the working week of production. Finally, energy efficiency measures were
proposed which would help the MNCs to plan, take decisions for investments in the future.
4.4.2. Data collection for Sus-VSM
The data collection for VSM was primarily conducted in the form of semi structured interviews
with the case company engineers working in different departments (see Appendix 2. Semi-
structured interview template). Engineers within the Departments of CAD/CAM, Heat
Treatment and Packaging were interviewed in order to get the required information. The
25
interviews were conducted for all the four products which would eventually lead to the creation
of four VSM diagrams.
The meetings helped to know more about the production processes and related operations for
the products within the selected facility. The different environmental metrics were identified
which consisted of time, raw material usage and process energy use. The information regarding
energy carriers (compressed air, electricity, cooling, cutting fluid) are presented inside the
boxes of diagram. Parameters like lead time, uptime and downtime for the operations were
identified by analyzing the historical and current data from the PI System Explorer. The plant
performance software helped to find the exact operation time in order to complete the Sus-
VSM diagram. By analyzing the previous historical data, the material usages were calculated
in the diagram. Thus, there will be four Sus-VSM diagrams drawn for the four products with
their respective detail, thereby tracking the energy use of the production line.
Regarding the metrics of the VSMs, the data collection for Value Stream Mapping also
included the data previously collected from the Energy Audit. This was used for the energy use
metric in the VSM diagram. The data regarding the raw material usage was collected from the
CAM Engineers, Engineers working within Heat Treatment and Packaging departments. The
same is applicable to the time metric considered in the VSM diagram.
The following metrics are considered for the formation of Sus-VSM diagrams:
1. Raw material usage metric
The energy use and raw material usage to produce the product account for almost 50% of
costs in manufacturing (Sygulla, et al., 2011). The largest material waste in manufacturing
relates to quantities lost through removal processes leading to increased scrap material
(Faulkner & Badurdeen, 2014). Thus, capturing effectiveness of raw material usage in Sus-
VSM is important and is included in the Sus-VSM for this purpose.
The manufacturing steps are broken down to two types – additive and subtractive (Sygulla,
et al., 2011). Subtractive manufacturing includes operations that involve material removal
such as machining of a gear or in this case, material removal from milling etc. (Ibid). It is
quite useful to know the material added and removed at each operation because the initial
and final raw material usage may not give the intermediate details. Thus, it becomes
imperative to include the raw material usage metric which helped to track the mass added
or removed at each operation.
The metric is represented on the Sus-VSM using two lines. One line is for the initial raw
material mass and the final for the finished product. This is used as a reference for the other
line. The processes which involve removal of materials and addition of material was placed
below or above the reference line in the form of boxes. For a process which does not add
or remove material from the product is kept as a line without any boxes.
2. Energy use metric
The energy use has a direct relationship to environmental sustainability due to the use of
non-renewable sources of energy and the corresponding GHG emissions (Ibid.). Therefore,
the energy use metric becomes important in the Sus-VSM diagram. The energy use metric
identifies the amount of energy used by each operation in the production line. The
identification of energy use at each operation will enable which operation possesses high
26
energy demand and indicating the need for further analysis and improvements. The values
are retrieved from the energy audit conducted for the studied facilities. These are
represented in the form of square boxes which are further divided into the energy use for
each carrier. There is a box at the bottom right corner which shows the total energy use as
well as the batch size considered for the complete order.
3. Time metric
The time metric is an important metric considered for the Sus-VSM which will indicate the
value-added time and the lead time for the entire production. The level above line indicates
the lead time between the two operations while the level below the line indicates the time
required for manufacturing for the respective operation. The lead time calculated from this
metric will give rise to further investigation and area of improvements for increased
productivity thereby reducing the overall time required for the whole production. Hence,
the time metric is included in the Sus-VSM diagram.
4.4.3. Data collection for Energy cost tool
The energy cost tool is developed by identifying important parameters for the selected
products. The different carriers like cutting fluid (pump energy), electricity and compressed air
are considered. The data for the parameters is collected from the energy audit process and is
served as the basis for the development of tool. The SEK per unit kWh price is identified for
the company depending upon the energy supply. The energy cost tool is developed in Excel
software. The tool is split into three sheets – tool, data and report. The tool sheet presents the
actual tool where the calculations are integrated. The tool sheet is explicitly divided into two
categories, Production and Facility. The Production category caters to the calculation from the
manufacturing operations like Machining 1, Machining 2, Heat Treatment and Packaging. The
first table in the tool sheet requires the user to input the values from the data sheet. To simplify,
tutorial boxes are used as a reference for the user such that the user knows where to input
values. The second table considers the calculation of energy use per piece, total energy use for
the batch size, total cost for production and the equivalent total GHG emissions released. The
third table in the tool considers the energy use per machine where the total number of machines
is identified in the studied facility. This calculates the energy use per machine. The Facility
category considers the total district heat used in the facility department. As the cost per unit for
district heat is identified, the total energy cost for facility is calculated and the equivalent GHG
emissions. The actual cost of supply for electricity and district heat has been omitted from the
tool due to confidentiality and are represented by different values. The energy use for support
processes represent different values than reality due to confidentiality. There have been some
important assumptions made in the energy cost tool. The assumptions are mentioned as
follows:
• The GHG emission factor for electricity has been assumed to be 0,13 kg CO2eq/kWh
(Johnsson, et al., 2019).
• The energy use per machine has been assumed to be equal for all the machines in order
to simplify and approximate. This provides a rough estimation, giving an overview of
the energy use per machine in Industrial area 1.
• GHG emission factor for district heating has been assumed to be 0,0556 kg CO2eq/kWh
(Johnsson, et al., 2019).
27
• Energy per piece values in data sheet has been calculated as average of all the sampled
values from PI System Explorer for that respective energy carrier and product.
• For the Machining 1 operation, Product E is assumed to be equivalent for all the
selected products. Hence, the electricity required per piece is the same for all.
• For Packaging operation, the compressed air is taken directly proportional to the
number of connection pipes and its equivalent area with reference of Machining 2
operation.
A ‘Reference Chart’ is outlined in the tool sheet. This enables the user of the tool to understand
which energy carrier is being used in which manufacturing operation. If an energy carrier is
being used, it is denoted by a ‘✔’ symbol and if not then ‘X’ symbol. The data sheet includes
all the energy use data regarding the different operations for the respective products. The data
is formulated in terms of tables for the energy carriers. Finally, the output sheet is presented at
the end, which fetches the data from the values inserted in the tool sheet. This sheet consists of
a brief summary of the total energy use and costs (electricity and district heat) and total GHG
emissions. It also contains five pie diagrams which give a distribution of energy use and GHG
emissions released in different areas. The five pie diagrams mentioned are – total energy use,
production energy use distribution, support processes energy use distribution, total GHG
emissions and GHG emissions between production (electricity) and facility (district heat).
4.4.4. Data collection for Energy Performance Indicators
The methodology for EnPIs was carried out in accordance to the method implemented by
(Kanchiralla, et al., 2020). The theory mentioned in the paper served as a reference to suggest
new EnPIs. The paper was thoroughly studied and analyzed, thus the EnPIs are inspired from
it. There were four explicit EnPIs tables derived. First table shows the list of EnPIs used in
STAMA cells. This table showcases the current EnPIs which are used in the PI System
Explorer software serving the purpose of monitoring and collecting energy related data. These
EnPIs were retrieved from the software. The EnPIs enlisted by Kanchiralla (2020) was used
for Table 7, Table 8 and Table 9. Table 7 shows the list of new EnPIs which can be derived
through available data from the software or through production data invoices. Table 8 shows
the list of suggestions of new EnPIs which require additional data currently unavailable in the
software and may/may not be available in the production data invoices. The information
relevant to these EnPIs are also presented below the table which could be useful if it were to
be implemented in the future. Table 9 shows the new EnPIs corresponding to the support
processes. As of now, almost all the EnPIs currently available in the software correspond to
the different machines used in the production line. The integration of this would require
additional sensors for the prioritized support process like pumps, compressors, ventilation,
lighting etc.
4.4.5. Data collection for Social sustainability
In this research work, the social sustainability assessment was conducted through a survey
questionnaire. That surveys contain a total of 10 questions and most of the questions are
developed by considering the sustainability goals. The social sustainability was assessed
through this survey. This survey was consisting of a questionnaire (Both in English and
Swedish) which was sent out to the working professionals at the case company. It was
28
important to keep the list of questions simple so that most of the participants could respond
without any difficulty. Simple random sampling method has been followed. The simple random
sample is the most essential type of likelihood sample. With random sampling, every unit of
the population has an equivalent likelihood of consideration in the sample (Bell, et al., 2019).
As this survey was conducted in the case company by considering the full-time employees of
four departments, which was around 54 (sample size) and the total population was 450 at the
case company (full time employees). This study was focused on the production process, so the
target group were chosen those were directly involved with the production process. There were
several departments, out of them four departs were chosen, so the sample size was 54. This
survey was not dependent on the employee’s availability (Ibid.). There was a scoring matrix
table formed based on the answers received from the survey. Ratings were provided to the
answer of statements. This was given as follows.
• “I agree” statement was given a rating of 4.
• “I somewhat agree” was given a rating of 3.
• “I somewhat disagree” was given a rating of 2.
• “I disagree” was given a rating of 1.
The number of responses received for the statement was multiplied by the rating provided as
mentioned above. For example, in statement one which says “Sandvik Coromant in Gimo is
actively working with sustainability” recorded 23 responses under “I agree”, thus it was
multiplied by 4 in the scoring matrix which gave 92 as a result. This was done in a similar way
for all the statements. At the end, an average score for that statement was calculated which was
out of “4”. Higher score meant that there is a higher satisfaction with that statement whereas a
lower score meant a lower satisfaction. A score of “3,6” and above was termed as good where
there is no need of much improvements while a score below “3,6” and below was deemed as
areas which could be improved further. During this social sustainability survey all ethical
parameters have been followed. Then the results of the survey were interpreted to give an
overview of social sustainability within the case company.
4.5. Motivation of Research Methodology
The bottom-up energy audit method is necessary in order to track the energy use of the products
requires measurement and analysis from the machine level. This gives rise to a bigger complex
system, thus making the original system a sub-system of the new emerging system. The audit
helps in studying and analysis of the energy use within the system boundary. The bottom-up
approach focuses on individual technologies for industrial processes (Sathaye & Sanstad, 2004)
which was the requirement in this study. While the Unit-Process-approach was used in this
audit as it is a general way for structuring the data for various processes (Thollander, et al.,
2014). This method of categorization helps to compare and generalize across all the companies
regarding process-specific comparisons between industrial companies with regards to for
example energy efficiency (Ibid.). The result from the audit will be energy efficiency measures
which would help the company for future investments. The Sus-Value Stream Mapping method
helps to visualize with clarity the present state of performance of a production line (Faulkner
& Badurdeen, 2014). The identification of relevant metrics and their visual representation helps
to develop comprehensive sustainable VSM (Sus-VSM). The energy cost tool was developed
through the data and analysis from the energy audit which will help the company in the future
29
to approximate costs generating from the different carriers of energy. The EnPIs are developed
so that the case company could monitor its energy end use more closely in the future and also
potentially evaluate its carbon footprints in real time. The survey related to working
environment was conducted among the employees (total 54 employees), which will be helpful
to identify the major factors need to consider while implementing social sustainability in a tool
manufacturing industry.
4.6. Ethical and legal consideration
Two main ethical issues were encountered during this research at the case company, data
management and invasion of privacy issues. The first issue concerned the data management
i.e. the routine collection and storing of digital data and the practices of data sharing raise new
concerns about confidentiality and related other ethical issues. Few questions raised about the
extent to which information can legitimately be used for research purposes that may be
different from the original reason for collecting the data. This issue focuses on who owns the
data and under what circumstances researchers are entitled to use it (Bell, et al., 2019).
The second ethical issue arise i.e. invasion of privacy is all about guaranteeing obscurity and
secrecy according to the chronicle of data and the upkeep of records identifies with all
techniques for business look into (Ibid.). Prior to doing the data collection and the
measurements, all the work was asked to the responsible employee for their consent. They were
also introduced to the motivation and purpose of such data collection. After that, most of the
data validated by the responsible employees at the case company and corrected some uncleared
information related to a few specific operations.
4.1. Limitations
Figure 10 System Boundaries for study
There have been several limitations considered for the thesis. The studied facility is inside the
V66 workshop, specifically GVP3 instead of the whole factory along with Heat treatment and
Packaging departments. This area comes under “Industrial Area 1” of the plant and falls under
30
site Gimo. It was not possible insert loggers inside the switchgear of the plant. This in turn,
changed the focus of the thesis where the data was readily available. The data collection has
been affected due to the ongoing Covid-19 situation, thereby affecting the results directly or
indirectly. The machines from which data was collected were in the Machining 1 and
Machining 2 operations inside GVP3. The STAMA machine (in Machining 2 operation) is
fitted with various type of sensors which measured parameters like machine electricity use
(kWh), power used (W), air use, supply and return of cutting fluid and compressed air etc.
While the parameters in SCHMID machine (in Machining 1 operation) and Heat Treatment
had to be measured manually with the help of energy loggers. As the company has thousands
of products, it was important to restrict to few products and study in detail about them regarding
its energy use. This data is collected on product level. Hence why there were only four products
selected for the study based on the company’s prioritization. Furthermore, the measurements
did not coincide with the manufacturing dates of prioritized products, hence similar product
was identified which would approximately have the same value as them. There was no
possibility to measure the electricity for the compressors and its related efficiency.
In the Value Stream Mapping (VSM) diagrams, the metrics have been identified based on the
environmental perspective of sustainability. The receiving and shipping have been excluded,
thus the focus solely being on manufacturing of the product inside the factory. This was
calculated only for ‘Machining 2’ operation due to the availability of sensors. Parameter like
pump energy requirements is also restricted to ‘Machining 2’ operation. For the rest of the
operations, only electricity energy use has been calculated. The risks associated with the
operations have been excluded as well as they were beyond the scope of this thesis. The Sus-
VSM diagrams considers only a few carriers like electricity, cutting fluid (pump energy),
compressed air and cooling water. The metrics have been limited to time, raw material usage
and energy use. The data collection about the operations overall has been restricted to only
those which were used to manufacture the prioritized products. The sample size for the social
sustainability survey was 54, which was relatively small compared to case company’s total
employees.
5. Result and analysis This chapter represents the empirical results of the research work. It also describes the
analyzation of the collected data with and concludes with some short outcomes. This chapter
represents the detailed description of the study and the results for the thesis.
5.1. Audit
The bottom-up energy audit has three phases – Survey, Energy Analysis and Energy efficiency
measures. These are described as follows.
5.1.1. Survey
There was no specific energy invoice for GVP3 or the other departments. Hence, there was a
necessity to carry out the bottom-up approach from the machine level to fulfil the purpose of
the thesis. The operations for the products are the same and involve 5 operation sequence. The
raw material in the process flow are in the form of raw blanks which undergo further machining
operations (see Figure 11). The different machining operations are listed as follows.
31
1. Machining 1
2. Machining 2
3. Heat Treatment
4. Assembly and Inspection
5. Packaging
Figure 11 Production flow for the products
5.1.2. Energy Analysis
The invoices of the active power sum L1-L3 with a duration of 10 minute was collected for the
year 2018 and 2019. This is applicable for the whole of the Industrial Area 1. As seen from the
diagrams, the curve dips during the month of July due to the low production. Apart from this,
there is regular production in the other months excluding some minor dips due to problems like
maintenance or other issues.
Figure 12 Active power sum L1-L3 (10m) for 2018
32
Figure 13 Active power sum L1-L3 (10m) for 2019
The Unit Processes was identified which comprises of GVP3, Heat Treatment and Packaging
department. The diagram consists of two categories of processes: Production and Support. The
Production processes are needed to manufacture the products. The Support processes are
needed to support the production processes but not needed for production (Rosenqvist, et al.,
2012). The unit processes have been identified which come under the system boundary. Due
to the production processes being highly automated inside the machine cells, it was not possible
to quantify the electricity use for each process.
33
Figure 14 Unit Processes of GVP3, Heat Treatment and Packaging
Sankey Diagrams
In this section, the Sankey diagrams are presented for the four products. In these diagrams, the
energy flow of the operation is directly proportional to the width of the arrows. The diagrams
consider three energy carriers – electricity, cutting fluid (pumping energy) and compressed air.
The values for all the energy carriers are represented in terms of energy use per piece. The
values which were unavailable are termed as “missing”, while the value “0” indicates not in
use. The dotted lines are linked with the missing values. The width of the lines is according to
the values, higher the value higher the width and vice versa. The width of the missing values
also changes based on assumptions. It is assumed Heat treatment operation will use more
electricity than Packaging operation. The width of compressed air for Machining 1, Heat
treatment and Packaging is kept the same. The dash dot line for the compressed air in packaging
assumes the energy use proportional to area and number of connecting pipes with reference to
Machining 2 operation. As they are based on rough assumption, it has been indicated by a dash
dot line. The width of the lines is according to the values, higher the value higher the width and
vice versa. The width of the missing values also changes based on assumptions. It is assumed
Heat treatment operation will use more electricity than Packaging operation.
34
Figure 15 Sankey diagram: Product A
Figure 16 Sankey diagram: Product B
35
Figure 17 Sankey diagram: Product C
Figure 18 Sankey diagram: Product D
36
Compressor system
Four and six compressors are operating at the same time which are installed nearby to V66
workshop. This distributes compressed air to all facilities not just V66. One compressor would
probably be more than enough for GVP3 while the six and four compressors feed the whole
Industrial Area 1. The type of compressor installed are Rotary screw type (oil) with on-off load
feature combined. The set pressure inside the compressors is 9,25 bars. The compressors
possess a heat recovery system. The compressed air system is central, and the machines are
supplied with compressed air through different sub-distribution systems. The invoices of the
compressors were studied and analyzed. It was collected for the year 2017 (January data
missing) and 2018. The main parameters considered in the invoices were the ‘total energy
recycled from compressors’, ‘recycled energy going to ventilation and preheating the incoming
air’ and ‘total instantaneous electricity’ in MWh. The exact values are not represented due to
confidentiality but instead are represented by the percentage. The percentage recycling has
been calculated by dividing monthly recycled energy (kWh) by the total energy recycled (kWh)
in that year. This shows which months have lower recycling and which months have higher
recycling. The percentage for the recycled energy for ventilation and total instantaneous
electricity has been calculated by similar method and the variation is fairly even during the
entire year. The total instantaneous electricity was increased by 7,81% in 2018 as compared to
2017. The following graphs illustrate the three parameters.
Figure 19 Percent energy recycled from compressors
37
Figure 20 Percentage of energy going to the ventilation and preheating the incoming air
Figure 21 Percentage of total instantaneous electricity of compressors
5.1.3. Energy Efficiency Measures
This section presents potential energy efficiency measures based on the audit analysis. It is
difficult to quantify the energy efficiency percentage increase. The measures are merely stated
qualitatively and thus could act as guidelines for future investment related to energy efficiency.
The measures are mentioned as follows.
1. In-house energy management
For the purpose of comparison, the energy use of a working week with a non-working week
was analyzed and compared. The time period was kept the same which would give accurate
comparative results regarding the total energy use in the Machining 2 operation. The machines
used in this operation is known as ‘STAMA’. This total energy use is inclusive of machine
energy, compressed air energy and pumping energy use. The data was collected through the PI
38
System Explorer software. The results from this requires further analysis and investigation in
the future as to where exactly the energy is being consumed, these are stated as follows. The
period was kept the same. The production week data is from 10th February to 15th February
2020. The non-production week data is from 17th February to 21st February.
Figure 22 Working week total energy use in STAMA cells
Figure 23 Non-working week total energy use in STAMA cells
As seen from the graph, the non-working week where the production is closed down still
consumes a substantial amount of energy when compared to working week of production. The
non-working week is still consuming approximately 40% of the energy in the working week.
One potential reason for this could be due to the carrying out of trials of production of different
work orders. Although there could be several other reasons like idling of the machines,
compressed air losses, pumping losses or other machine losses. The efficiency can be increased
by better in-house energy management. One such framework is described which the company
can follow in order to assess and improve the energy efficiency in this regards.
Stama 1 Stama 2 Total
Energy use (kWh) 487,0 374,8 861,8
0,0
100,0
200,0
300,0
400,0
500,0
600,0
700,0
800,0
900,0
1000,0
En
ergy U
se (
kW
h)
Machine
Energy use during production week
Stama 1 Stama 2 Total
Energy use (kWh) 125,9 219,0 344,9
0,0
50,0
100,0
150,0
200,0
250,0
300,0
350,0
400,0
En
ergy (
kW
h)
Machine
Energy use during non-production week
39
Current working of energy management:
This section gives a overall picture of the working of energy management for Sandvik
Coromant in Gimo. Sandvik Coromant division have energy efficiency goals for each year.
Before every new year, the Energy and Sustainability engineer at the site reports environmental
actions to a global database as well as environmental data i.e. how much electricity, water,
waste, district heating, oil etc. Every quarter during the year, Sandvik Coromant reports status
on the energy efficiency measures on to the global databse which is being followed by the
global Environment Health and Safety (EHS) department. This department measures the total
energy efficiency for all of Sandvik Coromant sites together after each passing year. The energy
efficiency actions are taken in coordination with the global EHS department and the local
production or facility manager at the site. Sandvik Coromant in Gimo is deemed to be not
energy intensive, hence there is no specific energy management standard certified.
Suggested model of energy management:
An energy management system needs to be implemented which will identify and analyse the
energy flow. In addition. A responsible person must be appointed and given a suitable position
in the company. The work description of the person responsible for energy issues includes the
following tasks (Hessian Ministry of Economics, Transport, Urban and Regional Development,
2011):
1. Monitoring and organization of energy data collection
2. Performance of energy audits
3. Support for service providers (e.g. data acquisition, selection of measures)
4. Evaluation and selection of energy efficiency targets
5. In-house communication on the theme of energy
6. Monitoring and support during implementation of the measures
An example of an organization structure is shown in the chart below.
Figure 24 Organizational structure of Energy Management
40
Volvo CE is a good example to illustrate its strategy towards energy management and its
principles can be adopted. Its new strategy focussed in the following order: energy
conservation, imporved energy efficiency and renewable energy (Thollander, et al., 2020). The
three are described as follows.
• Energy conservation: It refers to not using the energy in the first place. E.g. turning off
equipment not in use, turning on equipment later at the start of production and turning
it off earlier and generally to use existing equipment in a smarter way to eliminate or
reduce the amount of energy used.
• Energy efficiency: It refers to investing in more energy efficiency equipment. E.g. new
electrical motors (like replacing IE2 motors with IE5), investing in energy recovery
and fundamentally investing in right size equipment.
• Renewable energy: It is the final step of the energy pyramid. It was termed CO2 neutral
but changed to renewable not to include nuclear energy and hence participating in
creating a global demand for renewable energy. It also highlights the need to start
prioritizing energy conservation, then on energy efficiency rather than purchasing solar
panels while wasting majority electricity produced by the solar panels.
Figure 25 Energy Pyramid at Volvo CE (Thollander, et al., 2020)
The strategy from the energy pyramid have resulted in several benefits (Ibid.). It helped to build
culture and behaviour where everyone in the factory is involved in energy conservation. This
takes time and to make sure all the employees are involved along with the different levels of
management in factory. Energy conservation is deemed to be low cost, thus it enables the
strategy to be self-funded. Energy bills are reduced and hence costs are reduced. Energy
conservation also reduces the size of future investments which is often overlooked. Without
making substantial capital investments, and trying to do low cost waste elimination
improvements, one gets to know the system better. E.g. reduced flow rates in a future
investment enables the use of smaller and less expensive pumps and motors. It is important to
note energy conservation is a never-ending journey. There needs to be some expectation from
the organization and leadership.
A KPI can be defined called as ‘relative idle electricity %’ which will allow the comparison
between the different factories despite variances in product, size, working hours etc (Ibid.). The
KPI can be defined as follows.
Relative idle electricity % = 𝑖𝑑𝑙𝑒 𝑒𝑙𝑒𝑐𝑡𝑟𝑖𝑐𝑖𝑡𝑦 (𝑘𝑊ℎ′𝑠 𝑑𝑢𝑟𝑖𝑛𝑔 10 𝑖𝑑𝑙𝑒 ℎ𝑜𝑢𝑟𝑠)
𝑃𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑜𝑛 𝑒𝑙𝑒𝑐𝑡𝑟𝑖𝑐𝑖𝑡𝑦 (𝑘𝑊ℎ′𝑠 𝑑𝑢𝑟𝑖𝑛𝑔 10 𝑝𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑜𝑛 ℎ𝑜𝑢𝑟𝑠)
Renewable Energy
Energy Efficiency
Energy conservation
41
Benchmark studies showed a good level of idle electricity for similar companies would be less
than 10% giving rise to potential for more challenging targets in the future (Ibid.).
Summarizing, the method proves that a large non energy intensive company can achieve
conisderable energy reductions through continous and systematic improvement activities like
Lean Energy.
Verein Deutscher Ingenieure (VDI) (English: Association of German Engineers) have
developed a standardized procedure to enable potentials to be realized within the framework
of an energy efficiency project called as ‘VDI Guideline 3922’, “Energy Consulting for
Industry and Business” (Ibid.). The purpose behind the guidline is to check energy use at
regular intervals and where necessary to carry out changes or renewals. A characteristic feature
of the procedure is the iterative process.
Figure 26 Procedure for implementation of energy efficiency measures (Hessian Ministry of Economics, Transport, Urban
and Regional Development, 2011)
First steps towards identifying energy efficiency potentials is to record the current state (Ibid.).
It is necessary to collect relevant data on energy supplies and energy use (e.g. technical
documentation on energy consumers, energy infrastructure and energy recovery) in order to
provide a strong basis for the description of current state. To create this basis, energy use data
must be assigned as carefully to their respective origins. For this, a balance scope will have to
be defined for the individual origins i.e. energy carriers therefore sensors or measuring devices
are installed if required. It is also necessary to classify the data by energy carrier like electricity,
heat etc. and category like lighting, ventilation etc. The balance scope can cover e.g. machines,
cost centers, production areas etc.
The next step is to develop proposals for increasing energy efficiency in the areas with energy
saving potential (Ibid.). When devising the measures, it is important to consider the following
set of approaches:
- Avoiding unnecessary energy use (e.g. reduction of idling losses)
- Reducing energy demand (e.g. use of energy efficient technologies)
42
- Reduction of transformation losses (e.g. reduction of distribution losses, increasing
utilization ratio)
- Implementing energy recovery (e.g. heat recovery applications)
- Use of regenerative energy sources (e.g. solar hot water systems)
It is imperative to observe the system in its entirety (Ibid.). There might be adverse effects on
the result. Hence, it is not possible to lay down an absolute order in which the procedure should
be carried out. Thus, the next step is to develop an overall concept. It is important to integrate
economic effects too when it comes to impact of the concept on technology and product quality.
Several alternatives should be worked out and compared in the manner of scenario analysis
(Computer aided simulation instruments). The relevant decision-making criteria are provided
here by key business figures and the energy saving potential. Other criteria could also be
profitability evaluation although it differs from one company to other. Examples of this are
security of supply, emission balance, anticipated new regulations etc. The final step is the
implementation and result checking, which should be carried out under the supervision of the
advisor. Continuous recording and maintenance of the energy related data enables assessment
at regular intervals of how far the goals have been achieved.
2. Pumps
A visit during the non-production week was made which was from 6th April to 10th April 2020
to investigate if there was idling of pumps in GVP3 facility. It was observed that almost all the
pumps were running resulting in idling losses. For instance, the energy use from the pumps
used for supplying cutting fluid to the STAMA machines (1 and 2) was calculated from the PI
System Explorer software. The production week data is from 10th February to 15th February
2020. The non-production week data is from 17th February to 21st February.
Figure 27 Pump energy use during production week in STAMA cells
STAMA 1 (M7
and M8 pump)
STAMA 2 (M7
and M8 pump)Total
Pump energy use (kWh) 123,9 99,0 222,8
0,0
50,0
100,0
150,0
200,0
250,0
En
ergy U
se (
kW
h)
Pump
Pump energy use during production
week
43
Figure 28 Pump energy use during non-production week in STAMA cells
The graphs indicate that there is relatively less energy use during the non-production week as
compared to production week. The approximate energy cost savings for the company could be
done by addressing the idling losses. Although, before deciding on a possible investment, the
existing pumps should be examined (Thollander, et al., 2020). One possibility could be that the
refurbishment costs would be lower than investment costs of a new pump. Say the pumps can
be refurbished by changing seals and bearings or maybe composite coated, or the impeller
diameter can be changed so that the pump fits better to the current operating point (Ibid.). Any
decision on renovation or new investment, the condition of electric motor driving the pumps
must also be examined and investigated.
Possible ways to reduce electricity requirements in pumps and improve the current working
system are mentioned as follows (Ibid.):
- Turning off unnecessary pumps
- Adjusting the dimensioning of pumps
- Installing an energy-efficient control of the flow (e.g. use of frequency converter or soft
start device avoiding throttle control)
- Installing an energy-efficient electric motor
- Eliminating the wear in the pumps
3. Compressors
Most of the compressors come in the form of packaged system in which the motor and the
compressor are in a full- or semi-hermetic enclosure (seal that is gas tight or impervious to gas
flow). Many compressor systems run in an efficiency range of only 5% to 10% (Waide &
Brunner, 2011).
STAMA 1 (M7
and M8 pump)
STAMA 2 (M7
and M8 pump)Total
Pump energy use (kWh) 13,1 0,1 13,2
0
2
4
6
8
10
12
14
En
ergy U
se(k
Wh
)
Pump
Pump energy use in non-production
week
44
Table 4 Example of losses in a compressed-air system, (Falkner & Slade, 2009)
Source of power loss Transferred “useful”
power (kW)
Power loss (kW)
Electrical power input 100 90 (heat)
Air from compressor 10 1 (e.g. filter pressure drops)
Treatment 9 1 (e.g. filter pressure drops)
Leakage 6 3 (leakage)
Distribution system 5.5 0.5 (e.g. excess pressure
drops)
Over-pressure 5.0 0.5 (heat)
Thus, it becomes imperative to calculate the efficiency of the compressors installed in tool
manufacturing companies. It would serve as a baseline for future investments if the compressor
efficiency is deemed to be low. There are two possible ways to measure the compressed air.
1. To calculate the compressor efficiency by taking the average power of the compressor
when the operations are not running which is divided by the average power of the
compressor when the operations are running. If the power of the compressor when the
operations are not running, it is difficult to know how much power the compressors are
using for compensation of leakages in the system.
2. To log the power of the compressor that is providing the machine with compressed air.
The data about total flow of compressed air the compressor produces is collected. The
ratio is calculated between the total flow and the flow going to the machine. This ratio
could be estimation of how much of the logged power in the compressor that can be
allocated to the machine.
With the above listed methods, one can have a rough idea about how efficient the compressor
systems are, while there is a need of further research and investigation about the compressors
considered in the case study. Electric servo or linear motors can serve as more efficient systems
which would replace many compressed-air and pneumatic control systems (Waide & Brunner,
2011). While some other measures on improving the energy efficiency in an industrial
compressed air system which the company can implement as per Thollander & Palm (2013).
These measures should be prioritized in the order that is presented below.
1. To examine alternatives to compressed air. Replacing as much as possible of the
compressed air demanding tools and processes.
2. To reduce or minimize the air leakages. This is an easy measure with short payback
period.
3. To use Variable Speed Drive (VSD) compressors.
4. To section the industrial compressed air system. Some machines would have different
pressure levels and different working hours.
5. To improve recycling of heat from the compressors. As seen from Figure 19, the energy
recycled in the month of August is low as compared to other months. This heat can be
used in the form of space heating purpose or in hot tap water.
45
5.2. Sustainable Value Stream Mapping
The below diagrams represent the value stream mapping of the four prioritize products i.e.
product A, product B, product C and product D. The yellow boxes in the left upper corner of
the diagrams shows the used carrier in the production process with different symbols ( Cutting
fluid- , compressed air- , cooling- , , electricity- , whereas the yellow boxes in the right
upper corner of the diagrams shows the units of the carrier used (Time- Minute, Material-
Grams, Energy- kWh). The description boxes below the product name indicates the different
operation information. This involves the uptime which considers the production to be
continuous. The raw material usage, lead time and the other carriers like electricity, cutting
fluid, compressed air, cooling water were represented along with the metrics. These all carriers
would not be quantified as all their data was not available, hence would be placed under the
operations indicating their use. The presence of the shapes indicates their use and absence
indicates not in use.
In the 2nd part of the diagrams represents the different process and the different carrier used i.e.
raw material removals, non-value added (lead time), value added (operation time) and batch
size. In the left bottom corner of the diagram shows the batch size, which is 100 for every
product, the total lead time, operation time, total energy, total material removal and the total
material added to a single product. The units used for the time, raw material and electricity are
placed in the top right corner.
In order to give a clear understanding to the reader, there are different color codes has been
used for each steps such as the line which indicates the operation time and lead time colored as
blue, the straight line with 4 boxes colored as green (represents the raw material uses) in the
production process. In the last part of the Sus-VSM diagrams shows the amount of carrier used
in different operation excluding the last operation (Packaging) as data was not available. The
upper blue lines represent the operations (value added) whereas the lower blue line represents
lead time (non-value added). The energy use for compressed air in Packaging operation has
been represented by a dash-dot line as it is based on rough assumption and may not indicate an
accurate picture. The Sus-VSM diagrams are shown below.
46
Figure 29 VSM diagram for Product A
Figure 30 VSM diagram for Product B
47
Figure 31 VSM diagram for Product C
Figure 32 VSM diagram for Product D
As the above products belongs to a same product family, they have some similarities in terms
of the carrier used and the raw material weight. The 1st machining operation only used two
carriers i.e. compressed air and cutting fluid as this is a dry operation. This machining operation
performs the complete milling operation. In the 2nd machining operation consumes all the
carrier, as this step performs multiple operation (taper turning, drilling, grooving, nulling etc.).
48
In the heat treatment operation. The 1st two operations are normally milling operation, so they
remove lots of material in each step. Which represents in a green line in the above diagrams.
The operation time is calculated by considering the production start and end time. The lead
time is calculated by the taking the end time and date of the 1st operation and the starting time
and date of the 2nd operation. For few of the products the lead time is high due to some
maintenance work, tool failure and the closing of the production plant. The heat treatment
operation (3rd operation) uses compressed air, cooling water and the electricity with a standard
operation time. But unfortunately, in this study the researchers failed to collect the energy
invoices due the COVID-19 pandemic. So, it’s bit difficult to analyze the electricity use for
that operation.
The lead time is calculated by the taking the end time and date of the 1st operation and the
starting time and date of the 2nd operation. For few of the products the lead time is high due to
some maintenance work, tool failure and the closing of the production plant. The heat treatment
operation (3rd operation) uses compressed air, cooling water and the electricity with a standard
operation time. But unfortunately, in this study the researchers failed to collect the energy
invoices due the COVID-19 pandemic. So, it’s a bit difficult to analyze the electricity use for
that operation. The last step is the packaging part, which involves marking, oiling, assembly,
inspection and stickering of the products. As the involvement of robots were there, so this
operation used compressed air and the electricity. From the above diagrams the operation time
for last phase is lesser as compared to the other three steps. This step adds around 0.06 gm of
extra weight to the product which is similar to the weight addition of the heat treatment step.
From above diagrams shows that the total lead time for product A is 9798 minute and the total
operation time is 2662 minute, the total material removal is 0.915 kg and the material uses is
0.12 kg. In product B, the total operation time is 266-minute, lead time is 9798 minutes. The
raw material removal for product B was 0.918 kg. Only 0.12 kg of extra material was added to
all the four products in the packing and the heat treat operation. For product C, the total
operation time is 8122-minute, lead time is 3805 minutes. The raw material removal for product
C was 0.756. For the 4th product (Product D), the total operation time is 7774 minutes, the lead
time is 29993 and the material removal rate is 0.897 kg from the first two machining operations.
The metrics other than lead time have been merely mapped to gain an understanding of the
current state. Regarding the lead time, Product A has the least which implies it is doing
relatively good while Product B, Product C and especially Product D have a high lead time. As
the products belong to the same family of turning tools, ideally the lead time should be close,
but it is not the case here.
5.3. Energy Cost Tool
With the help of the Energy Audit and Sus-VSM methods, the data for the cost tool is made
available. The energy cost tool is split into two excel sheets – tool and data. The tool sheet
consists of the actual energy cost tool whereas the data sheet consists of the data required as
input to tool. It was not possible to collect/calculate all the values in the data sheet due to
limitations stated previously. It is hoped that the missing values would be inserted into the data
sheet in the future.
The Tool sheet is further divided into Production and Facility section. The M7 and M8 pumps
are assumed to be the pumping energy requirement for cutting fluid. The electricity use in
Machining 2 operation was made for another equivalent product of the same dimension as the
49
original four products. Hence it is assumed to be the same value for all the four products. The
energy use per product for compressed air in Packaging operation is roughly assumed to be
directly proportional to the number of connecting pipes and its equivalent area. The gas used
in the Heat Treatment was not monitored.
To make the tool more user friendly, tutorial boxes are placed wherever there is an input
required. Table 3 in the Tool sheet assumes equal energy use per machines. The emissions from
production and support processes are summed up at the end giving the total (kg CO2eq). A
“Clear All” button is also added at the bottom of the tool to facilitate the user. By clicking this
button, the fields which require input from the user are cleared and is ready for new values. A
reference chart is also provided in the Tool sheet so that the user knows which energy carrier
is being used in which operation. It considers electricity, cutting fluid and compressed air.
Table 5 Reference Chart for the Tool sheet
Operations Electricity Cutting Fluid Compressed Air
Machining 1 ✔ X ✔
Machining 2 ✔ ✔ ✔
Heat Treatment ✔ X ✔
Packaging ✔ X ✔
Machining 1 ✔ X ✔
The * symbol is the assumed value for the GHG emission factor. The GHG emission factor for
electricity and district heat is taken from the source (Johnsson, et al., 2019). In the Data sheet,
the values are represented in terms of energy per piece for the energy carriers for the four
products. Figure 33 and Figure 35 demonstrates the energy cost tool working. This is not the
actual representation as some of the values are missing currently. In the example shown in the
following figures, ‘100’ number of products have been placed for Product A. The missing
values for energy carriers have been placed by ‘1’ kWh. Total energy use in Industrial area 1
is placed by ‘100’ kWh and the total district heat supplied is placed by ‘1000’ kWh. This has
been done to exemplify how the tool would work in the future when all the values are inserted.
It does not show an accurate picture as the numbers have been arbitrarily placed in the tool.
50
Figure 33 Energy Cost Tool: Tool Sheet
51
Figure 34 Energy Cost Tool: Data Sheet
52
Figure 35 Output Report Sheet
53
5.4. Energy Performance Indicators (EnPIs)
There are several Energy Performance Indicators (EnPIs) used to track and monitor the energy
use in the STAMA machine cells. The list of the current EnPIs is shown below.
Table 6 List of current EnPIs used in STAMA cells
Sr. No. EnPIs Characteristic
1. Power consumption by M7 pump (W) Absolute
2. Power consumption by M8 pump (W) Absolute
3. Energy use by M7 pump (kWh) Absolute
4. Energy use by M8 pump (kWh) Absolute
5. Total Power consumption (W) Absolute
6. Energy Mode Savings (%) Ratio
7. Power consumption per hour (W) Absolute
8. Power consumption per minute (W) Absolute
9. Total energy use (kWh) Absolute
10. Total energy use per piece (kWh) Absolute
By analyzing the literature paper, (Kanchiralla, et al., 2020) there were several EnPIs which
were studied and further suggested. The EnPIs shown below are the indicators which could be
developed and added into the PI System Explorer software through current available data.
Table 7 List of suggested new EnPIs which can be developed through available data in STAMA cells
Sr.No. EnPIs Characteristic
1. Peak demand in a month (kW) Absolute
2. Electricity use (kWh) during peak hours Absolute
3. Total energy use (kWh)/tonne of production Ratio
4. Total energy use (kWh)/hour of production Ratio
5. Total energy use per cycle (kWh) in combination with
article and used methods
Absolute
6. Total production time in hours (for one order)/article Absolute
7. Total energy use of energy carrier (kWh) in
combination as well as separate/article *
Absolute
8. Total energy use (kWh) in Eco-mode * Absolute
9. Total energy use (kWh) in idle mode * Absolute
10. % of total energy use at idle (kWh) vs total energy use
(kWh)
Ratio
*The additional information about the selected EnPIs are discussed as follows.
• The EnPI ‘Total energy use energy carrier (kWh) in combination as well as separate
/article’ can be used to evaluate which article uses a lot of the energy carrier in that
operation. The energy carrier could be cooling water, electricity, compressed air etc.
For example, it would help in investigation for an article using a lot of cutting fluid.
This will help the company to develop new methods which would use much less of the
energy carriers.
• The EnPIs ‘Total energy use (kWh) in Eco-mode’ and ‘Total energy use (kWh) in idle
mode’ can be used to evaluate how much energy is being lost (idling) or saved (Energy
saving mode or Eco-mode). These will require indicators if anything shifts, for instance
if compressed air is being used more than the normal value.
54
It may be noted that the EnPIs listed in Table 5 and Table 6, only list the indicators which are
currently in use and could be developed through available data respectively. While these
indicators are used for the STAMA machine cells at present, these may also be used in other
machine cells in the industry. This would require connecting sensors which are presently
unavailable. It is important to address that these EnPIs cater to the production processes only.
There could be several factors like different production technique, different raw material,
different amount of cutting fluid or compressed air used etc. thereby affecting the energy
performance. Apart from the EnPIs suggested in Table 5 and Table 6, there were new proposed
EnPIs in Table 7. These new proposed EnPIs would require additional data in order to
implement and to be used in the software.
Table 8 List of suggested new EnPIs in STAMA cells
Sr.No. EnPIs Characteristic
1. CO2 emissions (tonne)/ energy use in process (kWh) Ratio
2. Total energy savings (kWh) from EEM/year Absolute
3. Actual energy use to actual output/rated energy use
to rated output
Statistical
4. Machine energy efficiency (%) Ratio
5. Instantaneous energy efficiency (%) Ratio
6. Cooling demand for cutting fluid (kW) Absolute
*The additional information required to develop new EnPIs is listed as follows.
• The EnPI ‘CO2 emissions (tonne)/ energy use in process (kWh)’ would require the
calculation of CO2 emissions by identifying the emission factor in (t CO2)/kWh.
• The EnPI ‘Total energy savings (kWh) from EEM/year’ would require the quantitative
evaluation of the energy efficiency measures adopted in the production process.
• The EnPI ‘Actual energy use to actual output/rated energy use to rated output’ requires
the data of actual energy output, rated energy use and rated energy output.
• The EnPI ‘Machine energy efficiency (%)’ use Specific energy use to evaluate and this
requires one additional parameter, total volume of removed material (Vmaterial) while the
total energy use of the machine tool (E) in kWh is available (Lirong, et al., 2016). This
can be calculated as follows:
Specific energy use = 𝐸
𝑉𝑚𝑎𝑡𝑒𝑟𝑖𝑎𝑙
• The EnPI ‘Instantaneous energy efficiency (%)’ requires two additional parameter,
material removal cutting power Pcut(t) and the machine input power P(t). This can be
expressed as:
Instantaneous energy efficiency (t) = 𝑃𝑐𝑢𝑡(𝑡)
𝑃(𝑡)
• The EnPI ‘Cooling demand for cutting fluid (kW)’ requires the specific heat capacity
of the cutting fluid (Cp) in J/kg ̊ C, mass flow rate of the cutting fluid (m) in kg/s, inlet
(Ti) and outlet temperatures (To). This can be formulated as:
Cooling demand for cutting fluid = m*Cp*(To-Ti)
The EnPIs enlisted in the literature (Kanchiralla, et al., 2020) for the support processes were
also studied and investigated. The general EnPIs are the ones which can be used for all the
55
support processes like lighting, pumps, ventilation and so on, while there are a couple of EnPIs
specific to the compressors. At present, there are limited/no sensors monitoring the support
processes. Thus, it requires capital investment first to purchase and install the appropriate
sensors for energy monitoring. The EnPIs for support processes are shown below and are self-
explanatory.
Table 9 List of suggested new EnPIs for support processes for the industry
Sr.No. Unit Process EnPIs Characteristic
1. General for
support
Energy use during peak hours (kWh) Absolute
Total energy savings (kWh) from
EEM/year
Absolute
CO2 emissions (tonne)/Energy use in
process (MWh)
Ratio
Total energy use (kWh) Absolute
2. Compressed
Air
Energy used (kWh)/air supply (m3) Ratio
Leakage rate (Compressor Free Air
Delivery (m3/h) X avg load time/total
operation time (h))
Statistical
5.5. Interpretation of Social Sustainability
Social sustainability is the least quantifiable dimension when compared to environmental and
economic sustainability (ADEC Innovations, 2020). In order to answer the 3rd research
question this survey was carried out in the case company with 10 questions (Appendix 3). Out
the 54-sample size there was around 33 participants who answered the question. This segment
decries the analysis of the participants response. Table 10 represents all the statements used the
in the survey and the total number of responses given by the 33 participants.
56
Table 10 Results of social sustainability survey
Sr
no.
Statements I
agree
I somewhat
agree
I somewhat
disagree
I
disagree
1 Sandvik Coromant in Gimo is
actively working with
sustainability.
23 10 0 0
2 Sandvik Coromant in Gimo have
a way of working that enables
me to work in a sustainable way
with regard to psychosocial
health and well-being.
12 20 1 0
3 I have the possibility to educate
and make a career at Sandvik
Coromant in Gimo if I desire to.
18 14 1 0
4 My workplace is adapted for all
employees to have good
ergonomics.
20 10 3 0
5 In my workplace I can
experience loud noises.
8 10 12 3
6 I feel safe working at Sandvik
Coromant in Gimo with regards
to injuries and accidents.
25 8 0 0
7 At Sandvik Coromant in Gimo
all employees are treated as
equals no matter of gender,
background or nationality.
25 8 0 0
8 At Sandvik Coromant in Gimo
gender equality is important.
19 11 3 0
9 At Sandvik Coromant in Gimo
we work with diversity and
inclusion.
17 16 1 0
10 I believe Sandvik Coromant,
Gimo is working towards
improving resource efficiency
and reducing waste.
21 11 1 0
For instance, the first question was ‘Sandvik Coromant in Gimo is actively working with
sustainability’. Most of the participants agree with this statement, out of 33 participants 23
people completely agree with the statement and 10 people are ‘somewhat agree’ with the
statement. The same is applicable to all the other statements in the survey.
57
Table 11 Social Sustainability score matrix
Sr
no.
Statements "I agree"
score
"I somewhat
agree" score
"I somewhat
disagree"
score
"I disagree"
score
Average
score
1 Sandvik Coromant in Gimo is
actively working with
sustainability. 92 30 0 0 3,69
2 Sandvik Coromant in Gimo have a
way of working that enables me to
work in a sustainable way with
regard to psychosocial health and
well-being. 48 60 2 0 3,33
3 I have the possibility to educate
and make a career at Sandvik
Coromant in Gimo if I desire to. 72 42 2 0 3,51
4 My workplace is adapted for all
employees to have good
ergonomics. 80 30 6 0 3,51
5 In my workplace I can experience
loud noises. 32 30 24 3 2,69
6 I feel safe working at Sandvik
Coromant in Gimo with regards to
injuries and accidents. 100 24 0 0 3,75
7 At Sandvik Coromant in Gimo all
employees are treated as equals no
matter of gender, background or
nationality. 100 24 0 0 3,75
8 At Sandvik Coromant in Gimo
gender equality is important. 76 33 6 0 3,48
9 At Sandvik Coromant in Gimo we
work with diversity and inclusion. 68 48 2 0 3,57
10 I believe Sandvik Coromant,
Gimo is working towards
improving resource efficiency and
reducing waste. 84 33 2 0 3,6
As stated in the methodology chapter, “I agree” was given a rating of 4, “I somewhat agree”
was given a rating of 3, “I somewhat disagree” was given a rating of 2 and “I disagree” was
given a rating of 1. The average score of each statement was computed at the end. As seen from
Table 10, almost all the statements have a high score out of 4 except for statement five. In this
statement, lower score expresses satisfaction as less noise is good for the working environment.
Statements one, six and seven have relatively high score than the rest where the company’s
sustainable, health and safety and no discrimination values are reflected in a positive manner.
Statements two, three, five, eight and nine have relatively less score. The score of these
statements show that there is a scope of improvements in those areas. The following describes
the description of statements along with the improvement suggestions in Table 12.
• Statement two: This statement reflects the importance of the implementation of
sustainability with regards to the physical health and wellbeing.
• Statement three: It reflects the importance of education inside the organization.
• Statement four: It reflects the importance of ergonomic conditions in the workplace.
Primarily, this statement was more targeted towards the employees working closely in
the production areas.
58
• Statement five: This statement has the importance of impact on the employees due to
loud noise at the workplace. As 50% of the participants works in the production line,
so there are experiencing load noise.
• Statement eight: It reflects the importance of gender equality which suggests that
Sandvik Coromant needs to strive for better balance in all its departments at site.
• Statement nine: It shows the importance of diversity which suggests that Sandvik
Coromant needs to strive for better balance at site.
Table 12 Improvement suggestions in social sustainability survey
Statements Improvement 1 Improvement 2 Improvement 3 Improvement 4
Statement two Promoting mental
health and social
wellbeing (European
Commission, 2014):
1. Being valued at
work
2. Being able to make
decisions on issues
that affect employees
3. Having all the
necessary resources
that employees need to
do the work
4. Having a job that is
well designed (i.e. not
overloaded)
5. Having work that is
organized better in
terms of work
schedules and time
offs
Social aspects of
workplace:
1. Social support
where the workmates
can help individuals
share, cope with and
overcome personal
issues.
2. Coping skills as
social interaction in
the workplace can
directly or indirectly
provide opportunities
to learn effective
coping skills.
3. Material support
where workplaces
provide resources in
terms of monetary
income.
- -
Statement three Encouraging more
educational and self-
development programs
within the company
for its employees.
Make the necessary
education better
accessible than it is
presently.
- -
Statement four Work surfaces should
be the right height of
the task and the
employee to eliminate
bending or reaching.
Frequency of tools and
parts should be stored
within easy reach or
location.
To avoid reaching,
extension poles and
adjustable height
platforms could be
used.
Utilizing sit/stand stool
can reduce the amount
of time employees are
standing.
Statement five Installation of modern
machines which
produces less noise.
Covering the machines
cells with sound-proof
glasses.
- -
Statement eight Need to increase
hiring of female/other
gender employees as
most of the working
professionals are male.
Should introduce
programs to encourage
more female
professional or
graduates.
- -
Statement nine Hiring of candidates
from different
countries with
multicultural work
background as most of
the working
professionals are from
Sweden though
Sandvik Coromant is a
global organization.
- - -
59
In order to implement this, the authors argue that tool manufacturing industries need to see first
the organization as a social framework in itself and second how they are installed in other social
frameworks (Fobbe, et al., 2016). Also, they have to set up basic conditions and improve their
insight to have the option to disguise social sustainability before actualizing instruments and
activities that lead to social sustainability (Ibid).
6. Discussion This section outlines, sum up and propels the investigation section through a conversation as
per the research questions. The discussion raises why certain things were analyzed and why
some were not alongside how they were applicable for the study. Additionally, the conversation
part treats the analysis, the confinements, and recommended future work within the same area.
Also, this segment, the analyzed empirical data and initial theoretical findings will be analyzed
in relation to each other to ultimately answer the research questions. More specifically, value
stream method (VSM), energy audit, energy cost tool implementation, EnPIs framework and
social sustainability will be applied on the empirical case and an analytical relation with the
literature will be discussed. Finally, this section will also give a basic introduction for future
research.
Research question 1
In this study the 1st research question is ‘How can energy use be studied, mapped and its energy
efficiency be improved in a tool manufacturing?’. This 1st research question was broken down
into two explicit parts in order to achieve the desired results. For the energy study, bottom-up
energy audit was implemented and for energy mapping, Sus-VSM methodology was adopted.
The audit process helped to understand and comprehend the production process ongoing for
the selected products through surveying phase. The structure of the audit was adopted like the
one developed by (Rosenqvist, et al., 2012) i.e. survey, analysis and efficiency measures. The
bottom-up approach was deemed necessary in order to get the overall picture while the top-
down audit approach would have been difficult to implement. It may not have provided the
desired results for this study. The Sus-VSM method developed by (Faulkner & Badurdeen,
2014) can be considered as relatively new. The application to case studies was limited to
satellite production line, bar fabrication and mortar fin production. This study serves as an
extension to its methodology, barring a few changes to the metrics and the original framework.
The study demonstrates a correlation between the two methods which was found missing in
the previously identified literature. The study provides a new insight into the relationship
between the two methods (audit and Sus-VSM) and how it can complement each other.
Due to the limitations enlisted by the company and the Covid-19 scenario, the study has been
affected. Due to the lack of data, the results cannot exactly confirm which energy carrier like
compressed air, cutting fluid, electricity etc. affects the energy use most in the production line.
The energy measuring was limited till heat treatment operation thus excluding packaging
section. It was beyond the scope of the thesis to study the support processes like lighting,
ventilation, pumping etc. in detail. The energy balance diagram thus could not be created. The
energy efficiency measures are merely stated qualitatively as the quantification of energy
savings is quite difficult. Though the measures are based on the previous literature and
research, they are likely to have a positive outcome on energy efficiency. This will in turn
influence positively on the economic sustainability of the company. The majority values in the
60
Sus-VSM are termed as missing thus making it difficult to grasp the overall picture of the
manufacturing process of the products.
There is a need to determine the missing values in the Sus-VSM to fulfill the need of knowing
which energy carrier uses the most energy in the future. This can be done through a thorough
energy measurement in-house or with the help of an external audit. This will help to fill in the
missing values in the diagrams. Further research is needed to see if this new established
relationship between audit and Sus-VSM could be extended and implemented in other large-
scale industries or even SMEs.
Research Question 2
The 2nd research question was ‘How can EnPIs and energy cost tool be developed and
implemented in a tool manufacturing industry?’. The results support and build on the studies
conducted by (Kanchiralla, et al., 2020) and (Johnsson, et al., 2019) and extended it to a tool
manufacturing industry. Several of the suggested EnPIs in this study share several similarities
with their studies for example Peak demand in a month (kW) in Table 7. The identified three
tables of new EnPIs will assist the company to closely monitor the energy use for its support
and production processes. It is more likely that Table 7 EnPIs could be integrated into the
software system readily as they require minimum additional information. While Table 8 and
Table 9 EnPIs would require a greater time frame in order to evaluate and integrate. The
categorization of system boundaries is in accordance with the study conducted by (Sommarin,
et al., 2014) which divide into overall, support process and production process specific figures.
The results of this study are based on the categorization into support and production processes.
Studies show that the comparison of EnPIs in the industry is complex due to different energy
end-use, undefined boundaries and heterogenous products (Bunse, et al., 2011). Tool industry
generally have homogenous products, thus the suggested EnPIs in this study could potentially
be extended for other tool manufacturing industries. The limitation of this study is that the wide
range of products in the manufacturing industries makes it difficult for more detailed EnPIs.
Further research in this area could be to develop EnPIs at sub-unit process level.
The manufacturing costs are not only limited to the production, but also other parameters like
cost of staff, support processes, materials etc. Thus, the cost tool developed tried considering
both the production section as well as facility section. While (Nord, et al., 2015) considered
operation time in their model, the cost tool developed in this study excludes this parameter but
retains the type of operations and carrier. The tool simplifies the energy cost calculation on
energy use (kWh) per piece for the production section and for the facility. The combined energy
use from the production and facility will provide a rough estimation on the carbon footprints
from the manufacturing of the products. While there are several cost tools models which have
been developed with a high degree of complexity involved, the cost tool in this study strives to
simplify as much as possible. This is needed so that the tool can widely be used among the
employees who may/may not have knowledge about energy use and related terminologies in
general.
The cost tool data sheet has majority of the values missing which is a major limitation. The
tool as of now can be deemed difficult to use due to this reason. As mentioned previously, the
cost tool is limited to production and facility. Further work in this area involves the evaluation
of cost related to materials, cost of staff and so on. This will provide and depict an accurate
61
picture of the total cost involved in the product’s manufacturing apart from energy use. It
remains to be seen if this simplified framework can be generalized for other manufacturing
industries as well. The tool can help and facilitate in evaluating the carbon footprints from their
production line. This data can further help and support energy efficiency measures thereby
reducing the emissions.
Research Question 3
The 3rd research question was ‘How can social sustainability be measured and improved in a
tool manufacturing company?’. The social sustainability is an important aspect in an
organization. In order to answer the 3rd research question, the authors decided to do a survey
among the employees working with three different departments in the case company. The
sample size targeted was 54 and the responses received were 33, which is about 61%. These
were explicitly perused to a contextual analysis as the principle objective was to see how social
sustainability in the organizational context could be executed in a proper manner. The
congruity of literature and the outcomes from the 3rd research question drove the researchers
to the suspicion that their conclusions from the RQ 3 were likewise appropriate to different
MNCs. As the case study company was a typical multinational organization, it works in several
countries and cultural settings.
The key discoveries from the present truth of the case study organization were an absence of
comprehension on what social sustainability implied and whether it was critical or essential.
Also, there was a missing review of approaches and an ineffectual structure with regards to
social sustainability (Boström & Magnus, 2012). These outcomes affirmed for the most part
what the researches had explored in the current literature on the subject.
From the survey, there are few factors where the case company need to focus in order to
implement social sustainability. The social sustainability matrix gives a good interpretation of
the results from the survey. This gave rise to explore the potential to improve regarding
statements two, three, four, five, eight and nine. The case company need to work on the
diversity, gender quality, continuous learnings within the company and loud noise created by
the machines. These are the few major areas need to be considered and likewise could be the
applicable for other MNCs. The way that fact all respondents had an alternate comprehension
of social sustainability was additionally in accordance with the writing depicting social
sustainability as increasingly hard to get a handle on (Boström & Magnus, 2012). Hence, there
was a need to begin from the essential comprehension of the idea of social sustainability before
its implementation. The limitation in this case is the number of people surveyed. As Sandvik
Coromant, Gimo has about 400-500 employees at Industrial area 1, the sample size considered
is very small. The survey could be extended to the whole organization in future and not only
site Gimo. This is to see where exactly they are in social sustainability context to gain a deeper
understanding of this pillar.
62
7. Conclusion This study gave a small benefaction to the academic research work in order to understand the
current and future benefits and challenges in implementing Sustainable Manufacturing in tool
manufacturing industries. This study could also be helpful in Sustainable business in different
MNCs. From this research work, the reader could learn that the implementation of sustainable
manufacturing is an important initiative, which will help the organizations to improve their
productivity by reducing cost, waste and environmental impact, thus giving a positive effect
on the triad of sustainability: Economic, environmental, and social dimensions. Today we are
living in the fourth industrial revolution era, where many SMEs and MNCs are dealing with a
rapidly growing economy and environmental challenges. Therefore, the survival of the existing
and new companies depends on their ability to address these challenges. Rather than
considering this as an obstruction to their development, the organizations should accept this as
an opportunity and find ways to gain competitive advantage from their sustainability efforts.
The research aimed to look at all three dimensions of sustainability for a family of products in
a production line and to see how far the case company i.e. Sandvik Coromant has come in the
sustainable manufacturing dimension. Furthermore, the research aimed to create a tool in order
to evaluate environmental sustainability concerning energy use and CO2 emissions. Based on
a quantitative and qualitative analysis of the three sustainability dimensions, it can be
concluded that to achieve sustainable manufacturing it’s important to look each of the three
aspects.
The results indicate that bottom-up energy audit and Sus-VSM can complement each other to
improve the environmental sustainability of tool manufacturing company. Although there are
relatively few journal articles which cover the bottom-up energy audit method, the thesis study
implemented concept of unit process from the research article (Sommarin, et al., 2014) and the
overall audit approach from (Rosenqvist, et al., 2012). The benchmarking approach used in this
study considering Volvo CE regarding energy management from the article (Thollander, et al.,
2020) could be beneficial for other tool industries too. This will help to evaluate what is
currently lacking in terms of the approach, policy or management in their present-day set-up.
Regarding the EnPIs and energy cost tool development, results indicate both could be
developed to support the economic as well as environmental sustainability dimensions. The
results from the journal article by (Kanchiralla, et al., 2020) have been extended to tool
manufacturing companies. While, the cost tool is relatively simple in terms of its design, the
parameters considered vary from the tool developed by (Nord, et al., 2015) and also differs in
terms of its purpose. The simplicity of the design in this study makes it more extensible and
adaptable to other tool industries with some modifications to evaluate energy use and CO2
emissions.
Most of the literature indicated that, the social sustainability is an emerging challenge for many
organizations in future. This study with the help of 3rd research question showed that there was
an absence of direction and structure on the best way to move towards social sustainability in
a vital manner among companies. This indicates that, there is a requirement for a general
direction on how social sustainability can be effectively achieved. Out of the ten statements of
the survey, there could be improvements made in areas concerning statements two, three, four,
five, eight and nine correlating to: diversity, gender quality, continuous learnings within the
company and loud noise created by the machines.
63
Theoretical and managerial implications:
This thesis gives an outlook about all the three sustainability dimensions – environmental,
economic and social in terms of sustainable manufacturing. This study will benefit individuals
or groups that are interested in energy use in tool manufacturing companies. This can also serve
as a reference for people who would like to conduct studies linking an energy audit process
with Sus-VSM perhaps for large-scale industries in other sectors. It assesses social
sustainability of working environment, developed and suggested EnPIs for tool manufacturing
industry. It also developed a new simplified cost tool, which was found missing in the previous
literatures and could be implemented with some modifications in its design in other companies.
8. Future Scope This study has out lined the vital comprehension on the needs, techniques of implementation,
and techniques for evaluations in achieving a sustainable manufacturing framework in a tool
manufacturing company. Furthermore, the three significant stages to accomplish and
consequently effectively actualize the desires for manufacturing frameworks with
sustainability characteristic features. Such as, research, development, and commercialization,
have additionally been featured in the current setting i.e. social sustainability. The significant
research gap lies in the identification of powerful execution procedures and the ideal needs.
Therefore, a lacuna despite everything exists for a point by point rules that can at last guide in
characterizing the related reasonable structure and sustainable manufacturing practice
techniques (Zindani, et al., 2020).
This segment speaks to various proposals concerning shortening lead time, energy cost and so
forth are talked about. These suggestions depend on lean standards, Design for environment
(DFE) and design for manufacturing (DFM), as explained on in the "Toyota way". Every
proposal's area will first quickly portray the issue, trailed by some potential solutions for
development.
Audit and Sus-VSM- It was not possible to grasp an overall picture of the energy use of the
entire production line due to limitations. The future work in terms of energy audit could be to
have every necessary value regarding the energy carriers used in the different operations. This
will not only aid in fulfilling the Sus-VSM diagrams but also help to evaluate the energy costs
and carbon footprints through the energy cost tool in the future. The energy efficiency measures
proposed in the study need to be further investigated and quantified as to how much energy
savings it would result if implemented. There is a further need of research to determine if the
established relationship between Sus-VSM and energy auditing can induce fruitful results in
terms of enhancing sustainable values within an industry. And, if it could be generalized and
extended to other industries apart from tool manufacturing.
Lessening lead time is a profitable aim on commerce entrepreneurs. Not exclusively does a
shorter lead time mean less time spent trusting that stock will show up, however it likewise
takes into consideration more prominent flexibility (TradeGecko, 2018). From the previous
analysis at the case company, after the 1st machining operation, the product had to wait
approximately 2 days for the next operation i.e. machining operation 2. This duration for the
waiting varies from different operation. Such delay caused by various issues like tool breaking,
maintenance work, lack of machine operators, multiple products for the same operation at same
time period and lack of proper product operation flow. Instead of changing tools frequently,
64
the operators should manufacture the products from the same product family which may results
less down time. Another improvement in terms of the production planning, from the Sus-VSM
diagram is that the lead time is varies from operation to operation and product to product. In
order to reduce the lead time, they should plan the complete operation of a single product
continuously by considering a standard lead time.
Energy cost tool – The tool developed in this study has been considered based on the production
taking place in the factory. The system boundary could be expanded beyond this and consider
the supply chain of the raw material as well as finished product. The raw material refers to the
machining energy use for the raw blanks which are used as an input to the Machining 1
operation in the factory. While the finished product involves the transportation emissions from
the factory to the desired destination. The energy use and its equivalent GHG emissions could
be integrated into the tool resulting in the complete overview. Further research in this area
could be to display it in the form of a dashboard system which would monitor all the
information in real-time. This will be the ideal case for the company to showcase its
sustainability performance and would be a worthwhile contribution to its stakeholders as well
as customers.
EnPIs -The development of the proposed EnPIs are hindered by the barriers mentioned in the
study by Andersson and Thollander (2019). To overcome these barriers related to EnPIs, tool
manufacturing industries could be encouraged to engage in joint research collaborations. While
increasing awareness of sustainability among the customers and key stakeholders could require
the company to adopt EnPIs to closely monitor its energy use. This will further help to develop
and increase energy efficiency within processes falling under different system boundaries
thereby reducing carbon footprints. The suggested new EnPIs require further research as to
how they could practically be integrated into the system while having the results in this study
as the baseline.
Social sustainability- Most of the findings from the case study on what is expected to actualize
social sustainability in a tool manufacturing company. Due to the lack of groundwork in the
case company about social sustainability, the researchers failed to develop more efficient
guidelines for implementation of social sustainability. Subsequently, there is requirement for
further research within the case company and other tool manufacturing industries. The
researchers suggest that future research should begin with the genuine guidelines for the
implementation of social sustainability.
65
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Appendix
Appendix 1. PI System Explorer
73
Appendix 2. Semi-structured interview template
74
Appendix 3. Social sustainability survey template
75
Appendix 4. VSM Calculation
Table 13 Material removal
The above table represents the total material removal and added in the all operation. From the
analysis, the Machining 1 process removes most of the material from the raw material block.
It’s the same for all four products. The 1st two operations removes most of the material from
the raw products and the last two operations adds extra material to the finished products, which
is comparatively very less. Because the heat treatment and the packing operation are the final
operations for the complete products.
Product Volume
Blank
Wt.
in kg
Volume
After
Machining 1
Wt. in
kg
Volume
After
Machining
2
Wt. in
kg
Wt. in kg
after Heat
treatment
Wt. in kg
after
Packaging
Product A 182938,05 1,44 105251,66 0,83 89988,81 0,71 0,05 0,05
Product B 182938,05 1,44 102850,42 0,81 89332,89 0,70 0,05 0,05
Product C 159469,52 1,25 100430,32 0,79 82400,26 0,65 0,05 0,05
Product D 182938,05 1,44 102819,76 0,81 90265,09 0,71 0,05 0,05
76
Table 14 Operation and lead time
The above table represents total operational time for each operation and the lead time in
minutes. As stated in the literature section here the calculation is done for the operational time
by comparing the end date & time of the previous operation and the start of the next operation.
Here in this study, most of the operational time and the lead time varies from product to product
due to some losses such as the maintenance work, tool breakdown and the order sequence. But
at the same time in the packaging part the operational time is very less as compared to the lead
time.
Product
Name
Machining
1 (min)
Lead
time
(min)
Machining 2
(min)
Lead
time
(min)
Heat Treatment Lead
Time
(min)
Packaging
Product A 508 1348 1305 4847 526 3603 323
Product B 4774 882 753 1881 218 9872 180
Product C 5325 1835 1781 1773 355 197 661
Product D 558 27562 428 1158 315 1273 6473