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Prague, September 2016
Industry 4.0: The future of the Czech F&B industry – Big opportunity or existential threat?
2
A few words about me
Managing Partner Roland Berger Prague
Philip Staehelin
> 21 years consulting & industry experience, including:
– CEO of CCS (fuel cards and telematics), other executive roles in A.T.
Kearney, T-Mobile, Accenture and UniCredit
> Pilot "Executive-in-Residence" at StartupYard (Prague), and mentoring
startups of other accelerators in the region
> Angel investor, and entrepreneur (founded 4 startups)
> Represented the Czech Republic startup community in Silicon Valley for
the Visegrad 4 Startup project
> MBA from INSEAD
Source: Roland Berger
3
Roland Berger is the only strategic consultancy of European origin – We provide strategic advice to the world's top decision makers
Roland Berger: Company overview – Top global management consulting
Source: Roland Berger
Austria, Vienna; Bahrain, Manama; Belgium, Brussels; Brazil, São Paulo; Canada, Montreal; Croatia, Zagreb; Czech Republic, Prague;
France, Paris; Germany, Berlin, Dusseldorf, Frankfurt, Hamburg, Munich, Stuttgart; Greater China, Beijing, Guangzhou, Hong Kong, Shanghai, Taipei;
Hungary, Budapest; India, Mumbai, New Delhi, Pune; Indonesia, Jakarta; Italy, Milan, Rome; Japan, Tokyo; Lebanon, Beirut; Malaysia, Kuala Lumpur;
Morocco, Casablanca; Myanmar, Yangon; Netherlands, Amsterdam; Poland, Warsaw; Portugal, Lisbon; Romania, Bucharest; Russia, Moscow;
Singapore; South Korea, Seoul; Spain, Barcelona, Madrid; Sweden, Gothenburg, Stockholm; Switzerland, Zurich; Thailand, Bangkok;
Ukraine, Kyiv; United Arab Emirates, Dubai; United Kingdom, London; USA, Boston, Chicago, Detroit
Founded in 1967 in Germany by Roland Berger
50 offices in 34 countries, with around 2,400 employees
Nearly 220 RB Partners currently serving
~1,000 international clients
4
Content
Source: Roland Berger
Industry 4.0: from global buzz to reality A.
Industry 4.0 readiness of F&B in the Czech Republic B.
Czech Republic to prepare for Industry 4.0 – Next steps C.
5
The global manufacturing industry is gearing up for the next level of industrial revolution – Industry 4.0
Development stages of industrial manufacturing
Source: Bitkom/Fraunhofer, DFKI, Roland Berger
First industrial revolution
Mechanical weaving loom
Introduction of mechanical production assets based on water and steam power
1784
Second industrial revolution
Introduction of a "moving" assembly line at Ford Motors
Introduction of mass production based on division of labor and electrical energy
1923
Third industrial revolution
First programmable logic controller (PLC)
Introduction of electronics and IT for higher automa-tization of production
1969
Fourth industrial revolution?
Real time, self optimizing connected systems
Introduction of intelligent machines, embedded cyber-physical sensors, collaborative technologies, and networked processes
2014
Drivers of this
development
> Large amount of data
available
> Rising demand for
(mass) customized
products
> Advanced algorithms
allowing better real-time
and large data analysis
> More affordable
sensor/actor
technologies
> Increasing prevalence of
communication including
wireless technology in
the factory
4.0 3.0 2.0 1.0
A
6
Industry 4.0 can be understood as the full integration and digitalization of the industrial value creation
Source: Plattform Industry 4.0, MIT Sloan Management Review, Roland Berger
Definition of Industry 4.0 (not exhaustive)
> Digital transformation refers to the changes associated with the application of digital technologies in all aspects of human society
> Industry 4.0 is the industrial application of the concepts applied in the digital transformation, key elements are:
– Complete connectivity with real-time ability
– Decentralized, intelligent and self optimizing/organizing
– Modular and reconfigurable
> Assessment of Industry 4.0 impact needs to take analogies from digital transformation and specifics of the manufacturing industry into account
> The digital transformation in the consumer goods sector is much more advanced than the industrial application
Digital transformation
Industry 4.0
Mobile devices
E-Commerce
Car sharing
Apps
Contactless pay
Home robotics
Wearables
Smart Home
Cloud data
Smart handbooks
Private robots
Self-optimizing systems
Self-learning robots
Predictive Maintenance
A
7
Interlinking of real (physical) and virtual (cyber) world will lead to so called cyber-physical systems that determine Industry 4.0 solutions
Schematic interlinking of physical and virtual world – Examples
Self-learning robots
Self-reconfiguring machines
Predictive maintenance
Smart environ-ment recognition
Industry 4.0 solutions
> Connectivity as the key factor is linking both worlds in each solution
> Enable
– Individualized or mass customized products
– Highly flexible production
– Integration of customers and value adding partner into value creation
– Coupling of production and high-value services
– Cost and efficiency benefits and quality improvements
Characteristics/Goals
Source: Roland Berger
Cyber world
> Advanced algorithms
> Machine learning
> High-performance hardware
> Embedded systems
> Real-time image processing (e.g. OCR)
> Data storage hardware
> Advanced data analytics
> Database mgmt. systems
> Cloud computing
> Real-time image processing
> Advanced data analytics
> Advanced algorithms
Physical world
> Robotics
> Automation equipment
> Traditional machinery
> RFID
> Automation equipment
> Traditional machinery
> Traditional & semiconductor based sensors
> Camera & imaging systems
> Visual sensors
> Traditional sensors
A
8
Industry 4.0 combines a wide set of technologies becoming well known – Across the 5 dimensions of the Industry 4.0 ecosystem
Monitoring/ control
2
Precision Manufacturing operations
3
Work organization
5
CAO, IAO
Flexibility
Traceability
Services (integration, maintenance)
CFAO
Virtual industrialization
Centralized planning and management of machines
Interconnected machines & plants
"Smart" machine (self-correction)
Precision engineering
Additive manufacturing Cobotics
Multi-support and multi-operation machines
Per piece RFID tracking
Active sensors
Retrofit
Conditional maintenance
Machine installation
Task specialization
Duty organization
Augmented operator
Learning organization
4
Monitoring, command
Flow management
Automated logistics/ Internet of Things
Automated internal logistic
Available maturity/ Industrial diffusion
Emerging maturity/ Limited diffusion
Future maturity/ Precursors
Product design/ process
1
"Virtual manufacturing plant" digitalized, production process simulation
Remote monitoring, mobile app, shared databases Thermal, hygrometric,
counting sensors...
Shared GPAO
Laser sensors, vibra switches, corrective programs
3D printing, Intelligent Assist Devices
Big data, télémaintenance
PLM MES Gravage laser, flashcode, puces
Lean Manufacturing
GPAO, PLM, RFID GV grinding,
laser cutting, HFwelding
Transfer center
SNC, programs, multi-spindle, etc.
Programmed/ De-programmed machines
Batch mana- gement
Digitalization of order- flow
Digital command
Traditional techniques
A
Source: Roland Berger
9
Most industrial players have launched Industry 4.0 pilots to test those solutions in legacy plants – F&B industry is catching up
Intelligent logistic bins
Augmented reality
Smart production
Humanoid robotic
Source: press review, companies websites, Roland Berger
Collaborative robotics
3D food printing
Conditional maintenance
MOST INDUSTRY 4.0 TECHNOLOGY BRICKS ARE EXISTING
Traceability
A
10
> Integrate production units from different manufacturers via software interface to enable smart platforms
> Reduce machine integration costs through faster integration of production and packaging lines
A few projects and concepts are emerging and look extremely promising in the manufacturing world – Examples food & beverage
Smart production
Traceability 3D food printing
> Modern track-and-trace technology documents product flow and enables each item to be tracked back- and forwards
> Data stored in corresponding database, which can be connected to other IT systems e.g. SAP
> Example: Meat industry – identification of slaughtered animal to finished meat pack possible
> Personalize food based on selected ingredients, nutritional components, medication etc.
> Flexibly produce custom output (mass customization)
> Shape individual products creating new shapes, textures, etc.
Source: Arla, ABB, TNO, RSW BV, Roland Berger
Collaborative robotics > Robots pick 2 waffles each based
on visual line tracking and collision guard
> Number of waffles and their position on the conveyor belt is communica-ted to robots via camera
> Robot controller assigns an equal amount of waffles to each robot while avoiding collision when picking the waffles Industry
4.0 in the food & beverage
industry
Unit #1 Unit #2 Unit #3
A
11
The goal of 'Industry 4.0' is the intelligent factory which is characterized by adaptability, efficiency and a full digital integration
Source: Roland Berger
Factory 4.0 – Overview
Suppliers
Cluster of suppliers
Cluster of plants Plant of the future B
Plant of the future A
3D printing/ additive manufacturing
Sensors
Nanotechnology/ Advanced materials
> Zero default/deviation > Reactivity > Traceability > Predictability
> Scrap elimination > Mass customization > Rapid prototyping
> Smart value added products > Technical differentiation > Connectivity
Robot
Cloud computing
> Stronger protection for internet based manufacturing
> Technology products with longer life cycle
Cybersecurity > Give sense to complexity > Creativity > Collaborative manufacturing
> Cyber Physical Systems (CPS) > Digital command
– Full automation – Totally interconnected systems – Machine to machine
communication
Logistics 4.0
> Fully integrated supply chain
> Interconnected systems
> Perfect coordination
Big data
Advanced manufacturing
systems
Clients
Autonomous vehicle
> Customer & marketing intimacy > Flexibility > Perfect match with customer's
needs with production mass efficiency
> On demand manufacturing
Mass customization
Internet of things
> Object tagging > Internet-object communica-
tion via low power radio > Real time data capture > Optimized stocks > Reduced wastes
> Real time – Autonomy – Productivity
> Full transparency on data reporting
> Flow optimization > Increased security > Lower costs
Resources of the future
Wind Alternative/non conventional Solar Geothermic
> Clean and renewable energies everywhere
> Energy Storage > Alternative raw materials
> Characteristics
> Smart robots and machines – Multipurpose "intelligent" robots able to adapt, communicate, and interact with each other and with humans based on remote control
> Big Data – New methods to handle huge amounts of data and tap into the potential of cloud computing
> Cyber-physical systems (CPS) and marketplace – IT systems built around machines, storage systems and supplies linked up as CPS
> New quality of connectivity – Connection of digital and real worlds with constant exchange of information between machines, work pieces, systems and human beings
> Energy efficiency and decentralization – Energy decentralization for plants due to climate change and scarcity of resources
A
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Data and communication will be the backbone of Industry 4.0 – Some players with already wide offering and new players entering
Positioning of different players for Industry 4.0 – Factory view
Source: Roland Berger
Players1)
Data/ Funct.1)
ERP System MES System Sensors/Automation Building Automation 3D Data Big Data Services
> All transaction data > Asset data > Price/cost data
> Shopfloor transaction data
> Machine data > Maintenance data > Logistic data
> Sensor status like pressure, position etc., communication with other sensors
> Machine control data
> Status of all building data, e.g. temp., light, access control, ventilation
> Product 3D data > Factory 3D data > PLM data
> Storage capacity > Algorithms and
analytics > Connectivity
Client
M
M
M
M
Controls & Automation
MES System
MES System
ERP System
Factory 4.0
Building automation
"Virtual" Production routing
New players
A
1) Not exhaustive; examples only
13
Industry 4.0 is changing the paradigm of manufacturing strategy…
Industry 4.0 – Characteristics
1 Flexible production, short production lead time enabling new business models emergence and affordable customization
From mass production
to mass customization
2 From large factories specialized per product in LCC to smart factories with high technological equipment enabling to produce at competitive cost everywhere
From volume scale effect
to localized & flexible units
3 From an organized production, based on planning and forecast and supported by stocks, to dynamic production and yield management, on demand
From planned make to stock
to dynamic make to order
4 Integrated conception, services being a key element of the business model/ decision factor
From product
to usage
5 Higher ROCE for lower Capital employed as complexity is transferred to the digital elements and working capital needs are reduced
From cost driven
to ROCE driven
6 Remote work (augmented reality, permanent connectivity), Tasks parallelism, flexible organization and management
From taylorism
to flexible work organization
From hard working conditions
to attractive work space 7 Development of complex artisanal production, with clean/highly connected work space, white collars intensive
Source: Roland Berger
A
14
… and will significantly change the rules of the game; It offers enormous upside to the new winners, but kills non-innovators
Industry 4.0 – Expected benefits
Source: Roland Berger
A
Design and manufacture better products – Industry 4.0 will enable adaptation of manufacturing methods by region e.g. automated zero defect manufacturing 1 Improve process efficiency and save costs – It would connect digital and real processes to identify and address manufacturing issues in advance, e.g. a quality issue 2 Create new business models – Industry 4.0 would disintermediate value chains or change the business rules itself e.g. Value chain will become more visible and need for intermediaries might be eliminated
3 Generate additional business – New 'Industry 4.0' comers would be the future game changers e.g. 3D bio-printing for fabricating biological constructs to produce soft tissues and artificial bones would help in generating additional business
4 Unleash innovation – It would free up additional creativity to fully leverage digital potential e.g. demand for business-model innovation is currently rising 5 Rethink organizations – Industry 4.0 would make organizations more responsive and flexible e.g. R&D teams would be able to leverage on global expertise at a faster rate 6
15
But… 'Industry 4.0' is a long journey and technologies will take 10-15 years to reach maturity in the market
Industry 4.0 roadmap
Laboratory solutions
Isolated/selective pilot installations
Transition to "True Industry 4.0"
Broad adoption of standard solutions
Source: Roland Berger
Mainly showcases or laboratory solutions in development
In next years mainly technology driven isolated standalone/plug-in solutions will be developed
The penetration of the market with isolated solutions will lead to an interconnection of many solutions via existing connectivity channels
Along the lifecycle of most production machinery the transition to true Industry 4.0 will start to be more comprehensive once most machinery, infrastructure and employees are Industry 4.0 ready
~2018
2025+
Today ~2020
2025
2030+ New Factories
(Greenfield)
Existing Factories (Brownfield) 2020
A
16
Countries have prioritized Industry 4.0 in their future plans as a key enabler for future growth – Czech Republic needs to catch up
Source: European Commission, Roland Berger
Selected initiatives supporting advanced manufacturing and ICT in Europe
1) Federal Ministry of Education and Research
Program [content, funding volume] Eligibility CZ Issuer
BMGBF1)
Fund for Digital Society
University of Warwick
Innovate UK
Cleantech Vlaanderen
Made different
CFI
European Commission ✓
✓
✓
Future Project Industry 4.0
Future Inventions
Warwick Manufacturing Group
Catapult Centers
MIP
Factories of the Future 4.0
Intelligent factories clusters
Factories of the Future
SPARC Robotics
Digital Convergence
Future Internet Technology
EUR 200 m
EUR 150 m
EUR 229 m
EUR 370 m
n.a.
EUR 8 m
EUR 41 m
EUR 1.2 bn
EUR 700 m
EUR 10 m
EUR 300 m
Support German industry for future challenges
Monetary support for R&D on embedded systems, big data and integrated objects
Different research initiatives focused on automotive & ICT
Double manufacturing contribution to GDP
Innovative cleantech and transition economy projects
Support the development of "Factories of the future"
Structure Italian manufacturing community to develop & leverage research, with 4 projects
Financial resources for Research and Innovation dedicated to advanced manufacturing in the EU
Support from EU to the robotics industry from R&D to production (part of Horizon 2020)
Foster the digital convergence throughout the EU (part of the European regional development fund ERDF)
Advance future internet usage across EU countries ✓
A
17
B. Industry 4.0 readiness of F&B in the Czech Republic
18
A country's 'Digital Transformation' indicators can serve as a proxy for Industry 4.0 preparedness – And it shows CZ needs to catch up
Technology absorption at company level
Innovation capability
International patents, apps/million of people
Internet usage for B2B
Internet usage for B2C
Employee training and development
#29
Czech ranking
Source: WEF Global Information Technology Report 2015, Roland Berger
Czech ranking in "Business Usage Index"
B
"Underperformer" "Leader"
Business Usage #32
#12
#25
#55
#28
#50
19
CZ goes against the trend of de-industrialization, which means it has much to gain, but even more to lose, in regards to Industry 4.0
26% 27%
Greece
11% 9%
Italy
15%
20%
Spain
13%
18%
23% 23%
France
16%
11%
UK
16%
11%
Manufacturing share of gross value added in selected countries, 2000 vs. 2014 [%]
Source: UNCTAD, Roland Berger
USA
15% 12%
Russia
15%
22%
China1)
28% 32%
Japan
21% 19%
Portugal
17%
13%
Australia
12% 7%
Poland
18% 19%
Global Average 2000: 17%
2014: 16%
Austria
11% 10%
B
Czech republic
Germany
1) 2004 vs. 2014
20
Czech Manufacturing GVA in the Food & Beverage segment is slowly declining – Both in absolute and relative terms
Food & Beverages1)
Sector-wise contribution to GVA [bn EUR, %]
Slovenia
7.0
Ø EU 28
14.5
Slovakia
7.1
Germany
7.3
Poland0
16.8
Hungary
8.0 9.9
Czech
Republic
F&B share1) of Manufacturing GVA, 2013 [%]
36%
23%
36%
2%
2009
37%
24%
2% 3%
25%
2010 2011
37% 37%
23%
38%
133 135 135
37%
132
3%
39%
38%
135
3%
Services 33% 36%
37%
25%
2012
Construction,
Utilities, Mining
& Quarrying
2014
143
Manufacturing
3%
27%
2013
Agriculture
& allied activities
10.4% 10.0% 9.0% 8.4% 8.0% 7.6%
Sector-wise contribution to GVA Czech Republic [bn EUR, %]
Source: Eurostat, UNdata, Ministry of Agriculture of the Czech Republic, Roland Berger
1) Share of value added in manufacturing total GVA = Gross Value Added = GDP + subsidies – taxes on products
Comments
> The Czech F&B industry's GVA has fallen by 7% from 2009 (EUR 3.2 bn) to 2014 (EUR 2.9 bn)
> The F&B industry in the Czech Republic accounts for 8.0% of manufacturing GVA, but manufacturing GVA is heavily skewed by the automotive sector (unlike in Poland)
B
21
Because of its reliance on industry, the Czech Republic needs to ensure it becomes a Frontrunner… or it will put its economy at risk
Manufacturing share [% GDP; index]
Greece
Luxemburg
Germany
Romania
Norway
Cyprus
Belgium Finland
Netherlands
Bulgaria
Lithuania Hungary
Czech Republic
Sweden
France
UK
Italy Slovenia Spain
Estonia Portugal
Denmark
Poland
Latvia
Croatia
Austria
Slovakia
Frontrunners
Traditionalists
Hesitators
Source: Roland Berger
Roland Berger Industry 4.0 Readiness Index1)
Industry 4.0 readiness – Positioning European countries for Industry 4.0
High
Low
Low High
Potentialists
1) Based on industrial excellence (production process sophistication, degree of automation, readiness workforce and innovation intensity) and value network (focus on high value add, industry openness, innovation network, internet sophistication)
B
22
C. Czech Republic to prepare for Industry 4.0 Next steps
23
Required focus areas to address Industry 4.0
A dedicated and focused approach is needed to increase the Czech Republic's readiness for the Industry 4.0 revolution
Source: Roland Berger
Government/ Regional support
> The Government would need to support in creating a suitable ecosystem by investing in infrastructure, power, data connectivity
> Czech companies will have to show readiness to adopt new technologies
1 > Public and
private partners have to collaborate closely to boost innovation
> In Czech Republic, industrial bodies need to take the lead in promoting innovation by providing avenues for stakeholders to come to a common forum
Accelerate Innovation 2
> Industries need to adopt the global best practices in four major domains:
– Business Model
– Value Chain
– Financial Base
– Knowledge base
> Widespread adoption of global practices will ensure overall growth
Adoption of best Practices 3
> The digital aspect has become mission-critical for many products and services
> Therefore, "new" industry needs a competitive environment that fosters dynamic telecommunications and Internet usage
Establish Infrastruc-ture 4
> Each company needs to identify the objective and potential of Industry 4.0 for their firm and develop a tailored strategy accordingly
> Top down organization change is required to implement the strategy and generate buy in across all levels
Develop a Roadmap
> Besides infrastructure, this dynamic digital environment also needs to foster new talent
> Backward looking education policies and ancient content will need to be radical changed to enable adoption of Industry 4.0
Foster New Talent 5 6
C
24
Roland Berger helps prepare companies with a 4-step approach to define an Industry 4.0 vision and prepare an implementable roadmap
Approach to define Industry 4.0 roadmap
Key
del
iver
able
s
Source: Roland Berger
What are the opportunities for your company?
2.
> Internal diagnosis of current company 4.0 performance
> Review of current initiatives
> Defined target for the company
> Gap analyses to target
Customer needs/ differentiation
Disruptive new technological solutions
Internal performance
diagnosis
2
3
4
What is your company's objective?
1.
> Validated list of priority objectives to cover through the program
Priority Objectives
1
What is the potential for your company?
3.
> List of priority improvement levers
> Financial target impact on CAPEX, Working Capital, Gross margin
> Detail of impacts on job and skills (resource shift, new skills to capture)
Prioritization of levers
Quantification of full potential (financial, skills …) & impacts
Mapping of building blocks (regulations, technology, cyber security, standards, …)
5
6
Which way to excellence?
4.
> Operational roadmap including key milestones
> Adjusted budget including program financial impacts
> Governance structure
Implementation roadmap and program governance
7
Opportunity identification
C
25
25
Your contact in Prague
Source: Roland Berger
Philip STAEHELIN
E-mail: [email protected]
Tel: +420 210 219 511
Roland Berger GmbH Na Poříčí 24, 110 00 Praha 1
Managing Partner
