Communicating progress in real -time from an infrastructure construction site A Thesis Submitted in Partial Fulfilment of the Requirements For the Degree of Bachelor of Engineering In Civil Engineering By Ryan J. Caetano 312 078 609 Supervisor: Adjunct Professor Michel Chaaya School of Civil Engineering University of Sydney, NSW 2006 Australia October 2015
1. Communicating progress in real-time from an infrastructure
construction site A Thesis Submitted in Partial Fulfilment of the
Requirements For the Degree of Bachelor of Engineering In Civil
Engineering By Ryan J. Caetano 312 078 609 Supervisor: Adjunct
Professor Michel Chaaya School of Civil Engineering University of
Sydney, NSW 2006 Australia October 2015
2. ii Student Disclaimer The work comprising this thesis is
substantially my own, and to the extent that any part of this work
is not my own I have indicated that it is not my own by
acknowledging the source of that part or those parts of the work. I
have read and understood the University of Sydney Student
Plagiarism: Coursework Policy and Procedure. I understand that
failure to comply with the University of Sydney Student Plagiarism:
Coursework Policy and Procedure can lead to the University
commencing proceedings against me for potential student misconduct
under chapter 8 of the University of Sydney By-Law 1999 (as
amended). Departmental Disclaimer This thesis was prepared for the
School of Civil Engineering at the University of Sydney, Australia,
and describes the development and implementation of a
semi-automated solution to activity progress monitoring. The
opinions, conclusions and recommendations presented herein are
those of the author and do not necessarily reflect those of the
University of Sydney or any of the sponsoring parties to this
project. .. Ryan Caetano
3. iii Summary Large infrastructure projects require constant
monitoring and adjustment to avoid delays and budget overruns. The
desire to work according to lean construction principles by
optimising workflows is driving research into the field of project
monitoring. Having timely access to project performance information
can improve the decision-making processes that make the adoption of
lean principles possible. This study investigates and develops a
cloud-based solution to activity progress tracking, and suggests a
method of visualisation through Earned Value metrics within a
Building Information Model. A digital Daily Site Report was
specifically developed to capture progress data on a large
infrastructure construction site. Specialised software was used to
harness this data into a useable format that could be interpreted
to inform variation control. Existing paper-based processes on-site
were re-engineered to accommodate for the implementation of the
form, thus facilitating real-time control. Standardisation and
cloud- based data dictated the success of the study. The
implications of the development are discussed in the context of
Automated Data Collection technology. A readily implementable and
flexible framework incorporating the digital form is
advocated.
4. iv Acknowledgements I am grateful to Dr Michel Chaaya for
his continual support throughout this research. I would like to
thank my thesis partner Timothy Gollan for being a reliable wall to
bounce off, and a calming presence. To several other university
friends, namely Sam, Gabriel, Hashan, and Jonah, its been a
pleasure sticking it out with you through University. To the team
at EIC, thank you for the inspiration and the opportunity to make
this research happen. I will always be grateful. To Rob, thanks for
putting up with my persistence over the past few months. Without
your help, this thesis wouldnt have been possible. Your
contributions were instrumental to its success. To my family, thank
you for your patience and understanding in my undertakings over the
past four years. Finally, to my partner Jaimie, your support has
been unwavering through the times I hadnt been so sure.
5. v Contents 1 Introduction
......................................................................................................................1
1.1
Background.................................................................................................................1
1.2 Industry
collaboration.................................................................................................1
1.3 Thesis aims and objectives
.........................................................................................2
2 Literature review
..............................................................................................................3
2.1 Lean construction
.......................................................................................................3
2.2 Building Information Modelling (BIM)
.....................................................................3
2.3 Project monitoring and
control...................................................................................4
2.4 Progress
monitoring....................................................................................................6
2.4.1 Existing solutions
...................................................................................................6
2.4.2 Daily Site Report
....................................................................................................6
2.4.3 Progress
measurement............................................................................................8
2.4.4 Automated Data Collection
(ADC)........................................................................9
2.4.5 Progress monitoring in BIMs
...............................................................................11
2.5 Summary of analysis
................................................................................................12
3
Methodology....................................................................................................................13
3.1 Research
approach....................................................................................................13
3.2 Analysis of existing monitoring processes
...............................................................14
3.3 Progress measurement
tool.......................................................................................14
3.4 Focus group
..............................................................................................................15
3.5 Activity progress
calculation....................................................................................16
3.6 5D model
development.............................................................................................16
3.7 Process guide for implementation
............................................................................17
3.8 Methodology limitations
..........................................................................................17
4 Digital form development
..............................................................................................18
4.1 Analysis of existing monitoring processes
...............................................................18
4.2 Data requirements for progress measurement
..........................................................19 4.2.1
Methods of
measurement......................................................................................19
4.2.2 Gates for type D activities
....................................................................................19
6. vi 4.2.3 Activity group methods of
measurement..............................................................20
4.3 Digital DSR
development.........................................................................................20
4.4 Focus group
..............................................................................................................22
4.4.1 Activity
mapping..................................................................................................22
4.4.2 Progress calculations
............................................................................................23
4.4.3 Industry
perspective..............................................................................................24
4.4.4 Recommendations
................................................................................................24
4.4.5 Focus group summary
..........................................................................................24
5 Progress
visualisation.....................................................................................................25
5.1 Progress measurement
calculation............................................................................25
5.1.1 Data sourced
.........................................................................................................25
5.1.2 Activity progress
..................................................................................................26
5.1.3 Activity
status.......................................................................................................27
5.1.4 Summary activity
progress...................................................................................27
5.2 Dynamic connection in 5D BIM
..............................................................................28
5.2.1 System interface
...................................................................................................28
5.3 Activity progress processes
......................................................................................29
6 Discussion
........................................................................................................................31
6.1 Digital form
development.........................................................................................31
6.1.1 Standardisation
.....................................................................................................31
6.1.2 User experience
....................................................................................................32
6.2 Progress visualisation
...............................................................................................34
6.2.1 Cloud-based 5D BIM
...........................................................................................34
6.2.2 EVA
method.........................................................................................................35
6.3 Feasibility of
implementation...................................................................................36
6.4
Limitations................................................................................................................37
6.5 Practical implications
...............................................................................................37
7
Conclusion.......................................................................................................................39
7.1 Future work
..............................................................................................................39
References................................................................................................................................41
Appendices
.............................................................................................................................A1
7. vii Figures Figure 2.1 - Typical S-curve (Del Pico, 2013)
...........................................................................5
Figure 3.1 - Three-phased research
approach...........................................................................13
Figure 4.1 - Existing activity progress monitoring
process......................................................18
Figure 4.2 - Digital DSR: desktop view
...................................................................................21
Figure 4.3 - Entering progress into digital
DSR.......................................................................21
Figure 5.1 - Data sourced from databases
................................................................................25
Figure 5.2 - Relational database established in
QlikView........................................................28
Figure 5.3 - 5D BIM cost and schedule data
visualisation.......................................................29
Figure 5.4 - Semi-automated solution
processes......................................................................30
Figure 6.1 - Digital DSR: tablet
view.......................................................................................33
Figure 6.2 - Recommended ADC implementation approach
...................................................38
8. viii Tables Table 2.1 - Common data captured within
DSRs.......................................................................8
Table 2.2 - Methods of progress
measurement...........................................................................8
Table 2.3 - Automated Data Collection
technologies.................................................................9
Table 2.4 - Barriers to implementation of ADC
technology....................................................10
Table 4.1 - Existing progress data collection and reporting
processes.....................................18 Table 4.2 -
Defined methods of progress
measurement...........................................................19
Table 4.3 - Example: gate breakdown and weightings for type D
activity ..............................19 Table 4.4 - Example:
matching methods of measurement to activity groups
..........................20 Table 4.5 - Re-engineered processes
based on the digital DSR form
......................................22
9. ix Abbreviations AC ADC API BIM CBS DSR EV EVA FM/SE ICT IT
LPS MS PE PM PP PPC PV RFID ROI WBS Actual Cost Automated Data
collection Application Programming Interface Building Information
Model or Building Information Modelling Cost Breakdown Structure
Daily Site Report Earned Value Earned Value Analysis Foremen and
Site Engineers Information and Communication Technology Information
Technology Last Planner System Microsoft Project Engineer Project
Manager Project Planner Percent Plan Complete Planned Value
Radio-Frequency Identification Return On Investment Work Breakdown
Structure
10. 1 Chapter 1 Introduction 1.1 Background The conceptual
pillars defining lean manufacturing focus on the elimination of
waste and the optimisation of workflows, the benefits of which have
boosted productivity levels within the manufacturing industry
(Forbes and Ahmed, 2010). Large infrastructure construction is
innately complex, and relies on constant monitoring and control to
mitigate the repercussions of variation. Project complexity is
increasing, perhaps causing the stagnation in productivity that is
characteristic of the current construction market. Firms are
looking toward Lean Construction principles in an attempt to
increase productivity through variation control. Progress
monitoring and control is a key aspect to its implementation,
however existing systems do not enable a fast enough response to
issues and changes on-site. The essence of progress monitoring
involves obtaining data directly from the construction site.
Traditionally, this is a labour intensive task requiring manual
collection. Development of technological tools such as Building
Information Models (BIMs) and Automated Data Collection (ADC) are
presenting opportunities to automate these tasks, in- turn
improving productivity. Development goes astray by focusing on
finding applications of new technologies within the construction
industry, where instead, the focus should be on finding problems
encountered in order to solve them with technological solutions
(Navon and Sacks, 2007). Key research in the field has been aimed
at ADC (e.g. El-Omari and Moselhi, 2011; Golparvar-Fard et al.,
2015; Turkan et al., 2012), however this is largely underdeveloped
for complex applications such as infrastructure construction.
Recent research is responding to this divide between research and
industry (Isaac and Navon, 2014; Matthews et al., 2015), however it
lacks a holistic approach necessary for industry implementation,
particularly within complex infrastructure projects. 1.2 Industry
collaboration This research was industry driven by a large
infrastructure project that is in the process of transferring
existing paper-based data collection to a digital format. The study
was undertaken in collaboration with several companies involved
with the project, namely Hochtief ViCon,
11. 2 EIC Activities, and Leighton Contractors. The North West
Rail Link: Operations, Trains and Systems project has been elected
as a testing platform for future digital expansion within the
group. The project team requested the implementation of a
cloud-based BIM solution to synthesise construction and planning
information in an attempt to track the project against planned
baselines. Pivotal to the success of the implementation was an
update of existing activity progress tracking processes.
Particularly, replacing the existing Daily Site Report with a
digital form. 1.3 Thesis aims and objectives This research is an
amalgamation of past research efforts into one implementable
system. It proposes a semi-automated, holistic, and flexible
solution to data capture such that activity progress can be viewed
and controlled in real-time. The project was used to establish lean
processes of progress data collection to inform Earned Value (EV)
visualisation through a cloud-based database. The study aimed to
combine the efforts of semi-automated data collection and
cloud-based BIM-generated EV metrics, providing a means for future
implementation of automated solutions. Namely, the study aimed to:
i. Create a digital tool to capture activity progress data ii. Use
data captured to inform data flows in a semi-automated framework
for activity progress visualisation iii. Document processes for
implementation purposes
12. 3 Chapter 2 Literature review 2.1 Lean construction
Technological advancements have enabled some industries to improve
efficiency and reap the benefits of time and cost savings, while
others have failed to capitalise. Efficiency in the construction
industry seems to have plateaued in recent times. To contextualise
this, time wastage in manufacturing and construction are estimated
at 12% and 57% of total time expenditure respectively (Aziz and
Hafez, 2013). A large contributor to efficiency gains in the
manufacturing industry is a shift in management ideals from mass
production to lean production principles. Where mass production
considers the sale of a product post-production to leverage
economies of scale through repetitive manufacturing, lean
production focuses on long-term gains, waste reduction, human
development, and problem solving through learning and understanding
(Forbes and Ahmed, 2010). The relatively stable nature of
manufacturing makes lean principles readily implementable (Howell
and Ballard, 1998); processes are well established and not overly
susceptible to external interference. Despite the obvious benefits,
application of these principles to a construction environment is
somewhat problematic. Processes are highly prone to external
interference due to the vulnerability of work interfaces
encountering problems (De Souza and Koskela, 2014). The reason for
this high vulnerability is the nature of project work - projects
are highly customised, unique, dynamic, and consume mass resources
(Hao, 2012). This gives rise to an adaptation of lean principles,
through lean construction; where lean manufacturing is implemented
through iterative means, attempting to improve an existing process,
lean construction must be applied with the formation of every
project. 2.2 Building Information Modelling (BIM) BIM is a
technological tool to enhance project planning and management by
serving as a container for mass data input and a multi-user access
point to this data (Becerik-Gerber et al., 2012). It makes design
information explicit through a multi-dimensional representation
more akin to peoples intuitions, making its intent and program more
understandable and evaluable
13. 4 (Penttil, 2006). Benefits lie in enhanced collaboration
amongst stakeholders, causing a positive Return On Investment (ROI)
by reducing errors and omissions (McGraw Hill Construction, 2014).
BIMs are applicable throughout all phases of a project (Computer
Integrated Construction Research Program, 2011). The BIM Use
Classification System categorises BIM use into five categories:
gather, generate, analyse, communicate, and realise (Kreider and
Messner, 2013). While lean principles and BIMs are conceptually
independent, synergies between them appear to suggest that the use
of BIM inherently entails a large degree of lean uptake. Indeed a
study by Sacks et al. (2010, p. 973) found 56 interactions between
BIM functionalities and lean principles, the majority of which were
linked to online communication of product and process information.
Communication links between individual parties are not isolated
channels between separate entities, as is the case in the current
construction environment, but instead all communication channels
flow through the BIM (Ding et al., 2014). This ensures that all
communication data is consistent and accessible, reducing the
repetition of work involved in collecting and processing data. A
reduction of unnecessary waste ensures BIM is lean. 2.3 Project
monitoring and control The types of words associated with project
monitoring and control are synonymous with the BIM uses above -
collect, extract, generate, analyse, report (Isaac and Navon,
2014). The two are not necessarily linked, but at the core of each
is a desire to use information to communicate in an efficient
manner. Although largely amorphous (Cook, 1997), the concept behind
project monitoring is collecting information about how a project is
progressing and communicating this to others who are in a position
to control or modify the progression. The two go hand in hand;
project monitoring informs what should be changed, corrected or
prevented as dictated by project controls. Project monitoring and
controlling are background tasks (Project Management Institute,
2013), which should not detract from their importance - they are
necessarily ubiquitous throughout all project management process
groups. However, they remain some of the most neglected areas of
project management (Larson and Gray, 2011), preventing
opportunities to reduce waste in the industry. Construction sites
are subject to change; project monitoring strengthens communication
channels (Dave et al., 2014) to facilitate controlling processes
that stem the flow and knock- on effect of changes, creating a more
stable environment in line with Lean Construction. Earned Value
Analysis (EVA) is the traditional method of project monitoring and
control and is commonly used in construction. EVA informs project
controls by comparing
14. 5 planned schedules and budgets to actual performance. In
short, management can assess whether a project is not progressing
as planned with respect to scope, cost and time, and as such,
whether corrective measures are needed. As defined by the Project
Management Institute (2013), there are three dimensions for
monitoring purposes. i. Planned Value (PV) or Budgeted Cost of Work
Scheduled is the time-phased budget, defining physical work that
should have been completed. ii. Earned Value (EV) or Budgeted Cost
of Work Performed is the amount of actual work completed as a
measure of the budget. It incorporates percentage complete of
individual work packages in the Work Breakdown Structure (WBS).
iii. Actual Cost (AC) or Actual Cost of Work Performed is the
actual, time-phased monetary consumption of a project. Tracking EV
metrics allows progress visualisation through S-curves shown in
Figure 2.1. EVA necessarily relies on data - it is driven by
schedule, cost, and progress data. Tracking progress within these
measures is one of the primary aims of project monitoring. Figure
2.1 - Typical S-curve (Del Pico, 2013, p. 116) The BIM uses
mentioned identify a space for project controlling through a visual
representation of EVA metrics. Some of the primary benefits of BIM
identified in literature include scheduling, visualisation, project
cost, and communication (Barlish and Sullivan, 2012), all of which
culminate in a use of EVA with BIM. In relation to lean principles,
improving communication and reducing wastage through repeated data
entry validate the combination and pave the way for implementing
lean construction principles.
15. 6 2.4 Progress monitoring 2.4.1 Existing solutions Progress
data informs EVA calculations such that an evaluation of the
projects performance can be made in line with project control
procedures. However, the regularity of progress measurement often
dictates what can and cannot be controlled. Ideally, field
personnel measure the completion of planned tasks through frequent
monitoring and data collection in order to adjust activities in the
short term. Being informed by real-time information systems
enhances control. Typical information delivery times, through
intermittent progress reporting, often exceed the time within which
controlling processes can be executed to mitigate deviations
(Navon, 2005). The effectiveness of project control is hindered by
a slow and staggered information flow from the construction site to
management. Regularly updated data informs EVA such that schedule
deviations and waste can be monitored and controlled to avoid
delays and cost overruns. Due to the infrequent and inconsistent
nature of existing data collection processes, the benefits of
project controlling are often not fully utilised. Data collection
in BIMs has two fronts: planning and performance of construction
works (Babic et al., 2010). Planning inputs include schedule
developments, activity planning, resource planning, and cost
budgeting (Koskela and Howell, 2008). Digital-based processes are
firmly grounded in ubiquitous software solutions within these
domains, and as such integrating planning information into a tool
such as BIM is achievable (Koekemoer and Smallwood, 2007).
Performance of construction work inputs come from the construction
site, namely, monitoring the progress of the project within each of
the planning domains. Capturing data whilst the construction is in
progress implores the need for data capture from the field. 2.4.2
Daily Site Report The most convenient and well-established way of
collecting on-site data for activity progress monitoring is through
the use of Daily Site Reports (DSRs). Data acquisition has
traditionally been paper-based, and integrating captured data into
BIMs is made difficult due to this manual data input. These
paper-based forms have become out-dated due to the advent of their
digital counterparts, reasons for which are explored in a study by
Russell (1993). The inherent problems associated with manual data
collection are outlined by the study. Individuals avoid
comprehensive data collection due to time constraints, and a stigma
that interprets daily reporting information as incriminating. The
cross-section of people filling out daily reports varies, and as
such so do their legibility, comprehensibility, and
applicability.
16. 7 Information can be biased, with individuals interested in
representing the selective truth for their own advantage. Field
personnel are overburdened by filling out forms, with estimates of
the time spent recording and analysing site data reaching 30-50%
(McCullouch, 1997; Navon and Sacks, 2007). Chin et al. (2005)
further developed this research, suggesting that daily reporting is
time consuming and data input is inconsistent. DSRs are standard
forms with blank fields requiring relatively uninformed and free
data entry. This creates variability in everything from activity
names, codes, locations and personnel. In short, insufficient or
inadequate information from the construction site contributes to
poor productivity and rework, which can lead to schedule delays and
cost overruns (Matthews et al., 2015). These inherent issues lead
to site information remaining relatively unused as data is
difficult to accumulate for current and future project use. For
this reason, progress data is often instead used for litigation
purposes regarding claims and other disputes (Navon and Haskaya,
2006). Both Russell (1993) and Chin et al. (2005), advocate
standardisation as a solution - by integrating planning and control
systems, data integrity is maintained, reducing inconsistency,
biased information and overburdening. This enables the development
of the current project status, faster response times in dealing
with problems, enhanced communication, increased schedule updating,
and assistance in dealing with claims (Russell, 1993). The approach
in standardising daily reporting information is enabled through the
use of digital forms. Going further, Navon and Sacks (2007) promote
real-time data collection, a currently manual process with
potential for automation using ADC technologies. Their research
assessed the information needs for project control to identify the
current shortfalls of monitoring data collection and reporting.
Industry responses emphasised the need to improve communication at
the daily resolution, particularly regarding activities.
Integrating data systems ensures that integrity is achieved - by
entering data only once into any one system, the reuse of that data
thereafter remains consistent. Through identifying data needs and
sources, repetition of input can be identified and eliminated.
Typical data captured in DSRs incorporate information on
activities, material, plant, and labour as summarised in Table 2.1
(adapted from Abdelsayed and Navon, 1999; Chin et al., 2005; Navon
and Haskaya, 2006; Pogorilich, 1992; Russell, 1993).
17. 8 Table 2.1 - Common data captured within DSRs Data Group
Data Activity Information Weather and ground conditions Activity
identification Activity status Description of work accomplished
Major events Problems encountered Receipt of drawings and plans
Material and Plant Information Materials arriving to the site
Number and type of equipment Equipment location Labour Information
General contractor workers by trade Subcontractor workers Name and
identification of person inputting data The groupings of data above
form three separate avenues of data collection (Isaac and Navon,
2012). Material and plant information is typically captured within
delivery dockets completed on arrival of the product. Labour
monitoring involves human resource usage and tracking labour
productivity and involvement through time-sheeting. Already, this
duplication of data defies intended lean construction principles.
Activities consume both material and human resources, however the
activities themselves achieve progress through the completion of
tasks within a defined process. Activity information can be
directly derived from the Work Breakdown Structure (WBS) or
scheduled activities established in almost all large-scale
projects. Chin et al. (2005) stress the importance of integrity and
consistency of data by integration with schedule information. 2.4.3
Progress measurement The complexity and uniqueness of construction
projects make it difficult to define a single way of measuring
progress. There are several methods considered (Forbes and Ahmed,
2010) in Table 2.2. Table 2.2 - Methods of progress measurement
Method of Measure Description Units Completed Completion based on
linear assumption of progression. Incremental Milestone Milestones
within an activitys process have a predefined. Percentage
completion based on a reasonable estimate informed by previous
experience. Start/Finish Similar to incremental milestone method,
however tasks can be started before others are completed.
Supervisor Opinion Reasonable estimates based on previous
experience. Inherent bias with subjective nature of measurement.
Cost Ratio Progress measured using the ratio of actual expenditure
to forecasted values.
18. 9 Jung and Kang (2007) offer a standardised solution to
progress measurement in which measurement methods are pre-assigned
to activities in the WBS. By combining this with the WBS and
schedule, integrity and accuracy of data improves, while time and
waste in repetition reduce. The variability in measurement methods
for any particular activity type triggers the necessity for defined
methods of measurement for all activities. 2.4.4 Automated Data
Collection (ADC) An abundance of technologies are available for
ADC; Table 2.3 below summarises the technology currently available
on-site (adapted from Navon and Sacks, 2007). Table 2.3 - Automated
Data Collection technologies Technologies GPS RFID Barcode Video
Audio Load Gauges Accelero- meters LADAR Materials Bulk ETO
Personnel Interior Exterior Equipment Building Earth-moving
People-moving Activity Progress Hand Tools Refuse/Waste Materials
In terms of measuring activity progress, most of these technologies
bypass traditional methods and minimise manual data entry. The
inconsistencies, biases, and delays identified by Russell (1993) as
common problems associated with manual data entry, are abolished.
Several studies have developed systems in which progress is
measured automatically (e.g. Chin et al., 2008; Ghanem, 2007;
Golparvar-Fard et al., 2015). However there is little uptake of
their methods in industry. Automation in data collection is lean
due to the benefits it provides. By offering simple and continuous
access to a rich, consistent source of information, many of the
inherent wastes in existing monitoring processes are eliminated.
Effective progress monitoring helps to inform project controlling
such that variations can be identified and controlled. This makes
the value in implementing ADC technologies undeniable, however a
study by Majrouhi Sardroud (2015) explains why there is little
uptake of the technology regardless of these benefits. Barriers to
implementation are outlined in Table 2.4.
19. 10 Table 2.4 - Barriers to implementation of ADC technology
Barriers to Implementation Cost-related Uncertain ROI Financial
constraints Investment cost Unclear benefits of technology use Poor
availability of tools for evaluating benefits of using ADC
Process-related Lack of understanding of the implementation process
Traditional business practice of the construction industry
Technology-related Lack of an Information Technology (IT)
infrastructure Lack of established IT system standards Lack of
perceived suitability of software Technology immaturity levels
Other barriers Different working practices and resources High
degree of fragmentation due to uniqueness of projects Culture
Behavioural barriers Lack of staff Advances in ADC technologies
have accelerated in recent times, driving costs down and making
benefits of monitoring and controlling more apparent. In a survey
study, Majrouhi Sardroud (2015) identified that barriers to
implementation of the technology have shifted from technical
problems to cost and process-related problems. Technology maturity
levels are improving, while implementation processes remain poorly
understood. Majrouhi Sardroud emphasises the development of a flow
chart and strategic plan to combat this, and a general focus on
processes is stressed (Navon and Sacks, 2007). In the context of
complex infrastructure construction, application of ADC technology
to a wide range of activities is questionable. Their applicability
is not universal; each ADC technology is suited to certain
construction tasks on-site. It is difficult to capture progress
completed for activities that do not only involve installing an
object or tracking delivery. A study by El-Omari and Moselhi (2011)
presented a control model that integrated several ADC technologies
for the purpose of progress measurement. The narrow opportunity for
implementation was apparent through the inclusion of pen-based
computers to collect data. Although LADAR was used in the system,
it was targeted towards quantity activities such as earthworks.
Progress-measureable activities that were not captured within ADC
solutions required manual data entry, which is to be expected. BIM,
however, is flexible enough to accept information input that stems
from the needs of organisations. Where current methods seek to fit
technological solutions to business needs, BIM enables
organisations to focus on business processes in order to determine
only the ADC technologies that are most suited to those needs
(Navon and Sacks, 2007; Sacks et al., 2010). While El-Omari and
Moselhi (2011) did develop technological solutions to suit project
needs, attempting to implement their
20. 11 approach in a complex infrastructure environment is
problematic. The detail to which ADC technology is currently able
to measure is largely underdeveloped. Making progress is not merely
installing objects in their intended positions (Matthews et al.,
2015); time and money is expended on preparation, material
delivery, formwork, cleaning, and the like. ADC technologies can
only compare actual completion to the planned model; they
communicate whether elements of a digital model exist in that state
in real life. A more flexible solution and focus on processes is
necessary for this method to be applicable to a live environment -
the research solely identified the potential for this methods
existence. As such, and remaining in line with the process-related
barriers to implementation identified above, ensuring progress
solutions are implementable and documented is essential for
continued support of the BIM. 2.4.5 Progress monitoring in BIMs Not
only do the aims of both BIMs and progress monitoring align
similarly with communicating progress, BIMs can be used as the tool
to achieve this. Many existing ADC solutions use BIMs as a platform
for their implementation (e.g. Golparvar-Fard et al., 2015; Kim et
al., 2010; Matthews et al., 2015; Toledo et al., 2014). The
planning data contained within the BIM is a useful data source that
can be used to communicate progress. It is an optimal environment
to visualise planned and actual data in its context. Projects are
becoming increasingly complex and uncertain (Howell and Koskela,
2000). Implementing flexible solutions not only encompasses ADC
technologies suitable for all progress-measureable activities, but
also the free flow of data. Cloud-based computing provides instant
access to an online shared pool of data that can be distributed
with little management (Mell and Grance, 2011). This enables
real-time collaboration that extends BIM use beyond design to
construction. Cloud functionality makes progress measurement
on-site more feasible, as live data can be accessed and updated
accordingly. However, cloud-based BIM research lacks insight into
how this technology can be implemented in practice (Wong et al.,
2014). A study by Matthews et al. (2015) uses a cloud-based BIM
approach to progress monitoring. Processes are recorded to
establish the feasibility of implementation of the system and
documented to continually support the BIM. The research
successfully develops an approachable way of implementing a system
for progress data capture using a flexible digital solution.
However no link is made to EVA nor any other data visualisation
tool - the data is not visualised in a BIM. Several studies used
BIM-based data to automatically generate EVA graphs. Kim et al.
(2010) created a system for EVA visualisation through a 5
Dimensional (5D) BIM, however real-time cloud-based data was not a
priority. Data was downloaded in .xml form
21. 12 once a month from a web-hosted database, and uploaded to
a program to view the 3D model in conjunction with time and cost
data in an EVA graph. Despite the success of the 5D BIM, again the
focus on development did not take into account practicality and
opportunities for implementation. Progress data capture was not
mentioned. Turkan et al. (2012) proposed a web-based real-time
tracking system. EVA was reported successfully, and progress data
captured, however this was done through ADC technology specific to
volumetric and linear quantity tracking. There is some mention of
reporting, however a fully automated system was the focus; no
distinct progress reporting system was defined. As such, the
unsuitability of automation for some tasks was not resolved. The
research identifies the limitations of the ADC technology used,
suggesting that they do not measure progress on a detailed enough
level, being only able to discern installed objects. The proposed
solution was therefore not able to track progress of tasks that
were ahead of schedule - these activities were not included in the
4D BIM and hence not compared to the baseline. By having
flexibility in both progress monitoring tools and mapping of data
to the baseline, these issues can be resolved. 2.5 Summary of
analysis The analysis of literature indicates that an opportune
point of similarity exists between lean construction principles,
BIMs, and project monitoring. Existing solutions attempt to unify
these concepts through automation. This technology is
underdeveloped, at least in the context of complex infrastructure
projects. There appears to be a missing link between research
efforts and industry. A holistic approach to progress monitoring
that considers both data capture and visualisation is as yet
unexplored. Digital forms seem to be the only realistic approach to
standardise progress data capture in the current market. Likewise,
EVA is the only workable and widely understood method to
communicate and visualise this progress. Synthesising these
concepts into a single solution may provide the link from lean
principles, BIMs and project monitoring, to controlling, which
existing solutions fail to provide to industry.
22. 13 Chapter 3 Methodology 3.1 Research approach The
methodology is outlined in three distinct phases as provided in
Figure 3.1, namely an investigation into research and industry,
development and interpreting feedback, and visualisation and
process documentation. Figure 3.1 - Three-phased research approach
Phase I: The first phase of the study focused on developing a
course of action for the subsequent phases through investigative
means. This included determining existing solutions to progress
tracking by analysing literature, and reviewing existing business
processes and software. The Daily Site Report (DSR) was identified
as the candidate for digitalisation, as this was an existing
platform for progress monitoring. Phase II: A progress data
collection tool was developed for the needs of the project. The
parameters for its development were established in the preceding
phase, namely the data to be captured and the processes to be
supported. A pilot form was developed and distributed on- site. The
digital form needed to streamline processes utilising progress
data, and as such, an industry focus group was held. The results of
this phase were analysed for refinement of the form and
determination of the methodology for phase III. Phase III:
Real-time communication between site personnel and management was
achieved by connecting progress data captured within the developed
digital DSR with schedule
23. 14 activities and cost data. These were linked to a 5D
model using specialised software. From the initial phase of
research, Earned Value Analysis (EVA) was identified as the
suitable communication tool for progress information. A guide was
subsequently developed to inform users of the processes to follow
in implementing the system. 3.2 Analysis of existing monitoring
processes Information regarding processes was sourced from the
project. Existing progress monitoring processes were determined in
collaboration with managers and engineers through multiple
consultations. Typical time expenditure was recorded by on-site
personnel, based on opinionated feedback, to inform opportunities
for implementation. The investigated processes informed the
research plan and determined how a semi-automated solution could be
used by the project. Ultimately, the information required, and the
opportunities to automate processes, were resolved. The existing
paper-based DSR was identified as the candidate for digitalisation
(Isaac and Navon, 2014). 3.3 Progress measurement tool Specific
progress measureable items and measurement methods were defined
(Forbes and Ahmed, 2010). Of particular interest were
milestone-based progress measurements, which were assigned
percentages for milestones reached within the activity. The
percentages of each milestone were determined in collaboration with
the project and associated companies. The methods of measure were
assigned to activity groups created to cluster similar activities
provided in the WBS, a similar approach of standardisation to Jung
and Kang (2007). This was done to simplify mapping of progress
measureable activities to their relevant measure type. The existing
paper form was analysed to determine what was to be included in its
digital counterpart, however as mentioned, the activity progress
tracking component was the focus of this study. Several
requirements were defined by the project in developing the digital
form. Primarily, the form was to fit in with existing software
infrastructure - namely, using data sourced from an online
Microsoft (MS) SharePoint site hosted on a MS SQL Server with a
Standard licence, and similarly publishing captured data to this
database. The MS SharePoint site acted as a central repository for
progress, cost, and schedule data. Access was to be granted on a
tablet device to allow use on-site, with Apple iPad Air 2 devices
supplied by the project, as well as online through the MS
SharePoint site. The form had to be useable offline,
24. 15 as areas of the construction site had limited to no
internet access. The Formotus mobile application was used to
circumvent limited internet access. The form was developed in MS
InfoPath and was to be implemented and used by the Foremen and Site
Engineers (FM/SE) who typically complete the paper-based DSR. A
pilot form was developed and used on-site such that constructive
criticism could improve the form in a process of iteration. Such
feedback was provided through consultations with FM/SE. 3.4 Focus
group Focus groups draw upon respondents views in a group setting,
allowing respondents to take initiative in their detailing of
information and enabling the researcher to elicit large amounts of
information in a short period of time (Gibbs, 1997). They are
particularly useful in exploring consensus on a given topic, and
balance rigour with pragmatism (Darke et al., 1998). A focus group
was a suitable qualitative interviewing approach in light of the
below research aims. A semi-structured focus group was conducted
with the aim of informing further development with respect to
implementation and progress calculation. The focus group was
directed towards personnel responsible for progress calculation -
those who used progress data to calculate EVA metrics required for
project control. The participants were aware of project control
processes and progress data capture. The interview participants
included a Project Engineer (PE), Project Manager (PM), Senior
Project Manager, and BIM Engineer. The focus group was conducted
with the following aims: i. To understand the relationships between
the WBS, Cost Breakdown Structure (CBS), and payment items ii. To
determine the current methods of progress calculation iii. To gain
insight into recommended approaches in achieving process automation
iv. To recognise an industry perspective on the development Four
general areas of discussion were established in line with the above
research aims. The recording of the focus group was transcribed and
coded for meaning, and then analysed in light of the research
questions and focus group aims. Methodological rigour was
maintained by cross-coding the transcript and through additional
collaborative consultations with experts in the field (Paulus et
al., 2008).
25. 16 3.5 Activity progress calculation The digital form was
created to track progress for progress measureable activities or
tasks. As such, actual progress accumulated per activity was
necessarily calculated. Likewise, progress of each activity at each
successive level of both the WBS and CBS was required by the
project for a number of purposes, namely determining percentages
complete for payment claims and for general project controlling
purposes. To enable this, a relation between the two was
determined. The sources of data established in the focus group
defined how to map schedule and cost activities so as to link time
and cost data. Existing activity progress on the project is
communicated through EVA and as such, on-site personnel and
management are familiar with these metrics. MS Excel was used to
pool schedule, budget, progress, and actual expenditure data, as
required for EVA metrics, from a number of online databases by
creating a dynamic link such that data could be refreshed in
real-time. The Power Query add-on enabled OData feed connections to
the online databases and was henceforth used to calculate progress
at each level of the WBS and CBS as required. This was then made
viewable through graphs published on the MS SharePoint site to give
on- site personnel immediate feedback as to the progress of on-site
activities. The MS Excel file was stored on the online MS
SharePoint site for multiple user access. 3.6 5D model development
Visualisation of the collected data through the lens of a 5D model
was important in understanding the impact of cost overruns and
schedule delays on surrounding activities (Kim et al., 2010). In
order to make data visible and useable for project controlling,
such that management decisions could be made, incorporation of EVA
calculations into the BIM was necessary. ViCon 3DBIS, a specialised
software package developed by Hochtief ViCon, was used as the 5D
BIM platform. A 3 Dimensional (3D) model was provided by the
project. Using a QlikView scripting interface, data was imported
from the MS Excel file created and stored on the MS SharePoint
site, as well as the WBS, payment items, and schedule data
similarly accessed from the MS SharePoint site. As opposed to
recalculating progress calculations within ViCon 3DBIS,
calculations were taken directly from the Excel file so as to avoid
excess loading times - the 5D BIM operated quickly. As such, the
Excel file needed to be downloaded, refreshed, and re-uploaded to
ensure the 5D model had the most up-to-date data. The structure of
the model was vital to the interoperability of data. The
object-based model needed to again be mapped to the schedule so
that incoming progress data could be assigned to a location within
the model.
26. 17 3.7 Process guide for implementation Informed by
feedback captured in the focus group and subsequent development,
implementation of the semi-automated solution to progress
monitoring was documented. Defining and documenting processes
allowed full implementation of the progress monitoring solution
(Majrouhi Sardroud, 2015; Matthews et al., 2015). Informing those
involved in the progress monitoring process of how to interact with
the digital form and 5D BIM was critical for the success of the
proposed solutions implementation. 3.8 Methodology limitations
Using MS Excel was necessary to provide immediate feedback to the
FM/PE on-site - installing ViCon 3DBIS for all on-site personnel
was unrealistic. The real-time aspect of the solution relied on
frequent refreshing of the data file developed. However, an
in-browser refresh function for MS Excel files with Power
Query-based OData feed connections is not enabled in MS SharePoint.
Initial trials of the MS Excel solution used the Power Pivot add-on
for MS Excel. Installing the Power Pivot add-on for MS SharePoint
enables in-browser refresh of MS Excel files with OData feed
connections, however as the existing MS SharePoint site was hosted
on an MS SQL Server with a standard licence, this was not possible.
An enterprise licence is required to authorise this install. An
added process step of downloading, refreshing, and re-uploading the
file was necessary before progress could be viewed in real-time.
Like Matthews et al. (2015), implementation of the innovative
technological solution was constrained by the delivery strategy
already adopted by the project. However the terminology itself is
perhaps misleading - whether real-time can ever truly correspond to
continuous when applied to progress monitoring in construction
settings is questionable. In reality, the solution is only
real-time in so far as providing regularly periodic updates of
progress. Limitations inherent in a semi-automated, human-driven
system render real-time progress monitoring idealistic. In truth,
real-time updates can only coincide with automation. Typical time
expenditure for both existing and developed processes were not
rigorously tested through the proposed methodology. Times are
recorded as estimates based on the respondents experience, which
are subjectively opinionated and prone to error. Likewise,
milestone-based weightings were solely reliant on the experience of
the select few consulted within the project. The rigorous testing
of these weightings is beyond the scope of this research.
27. 18 Chapter 4 Digital form development 4.1 Analysis of
existing monitoring processes The project used a paper-based DSR to
manually record progress (Appendix A). Existing processes and their
time expenditure were determined in collaboration with the project.
Table 4.1 - Existing progress data collection and reporting
processes Conventional DSR Process Time required (mins) On-site
processes 28 FM/SE makes handwritten notes of daily shift
activities 5 Write Daily Site Report on PC 20 Send report to
reporting manager 3 Off-site processes 40 Reporting manager checks
and collects missing documents 30 Reporting manager produces daily
client report (time per single day report) 10 Figure 4.1 - Existing
activity progress monitoring process Significant time expenditure
was observed both on-site and off-site as shown in Table 4.1.
Converting handwritten notes into a digital format created
duplication. Opportunities to digitalise the DSR were realised.
Likewise, collection of DSR documents and report
28. 19 production was time-consuming. The conventional DSR
process above was placed in the context of the entire activity
progress monitoring process in order to inform future
implementation, shown in Figure 4.1. 4.2 Data requirements for
progress measurement In order to successfully digitalise the
existing DSR form, several requirements were met such that data
provided by the project could be used within a digital form. 4.2.1
Methods of measurement With the intention of standardising progress
measurement, several methods of measure are identified Table 4.2 in
line with the review of literature. Table 4.2 - Defined methods of
progress measurement Type Method Description A 0-100% Complete
Until the activity is complete, the associated progress will remain
at zero. Upon completion, progress is deemed to be 100% B 50-50%
Complete When the activity is started, the progress is evaluated as
50%, and when complete, progress is deemed to be at 100%. Any
progress in between is not considered. C Percent Complete A
percentage value between zero and 100 is progressively assigned.
This progress measurement is at the discretion of the supervisor. D
Interim Milestone A set of milestones or gates are predefined for
specific commonly executed activities. Each milestone has an
associated percentage. Between each milestone, no progress is
recorded. E Yard Stick Depending on the activity at hand, a unit of
measurement is defined and used to quantify the work complete.
Physical work complete is measured to the highest degree of
accuracy possible. 4.2.2 Gates for type D activities Through
extensive collaboration with industry partners, common gate
structures and their associated progress percentage for Type D
activities were formulated. An example is provided in Table 4.3; a
comprehensive list is provided in Appendix B. Table 4.3 - Example:
gate breakdown and weightings for type D activity Process &
Process Gate Breakdown Gate Weighting Concrete (FRP) 100% 1 Minor
Excavation 10% 2 Blinding Concrete 10% 3 Rebar 25% 4 Formwork 25% 5
Pour Concrete 25% 6 Strip & Backfill 5%
29. 20 4.2.3 Activity group methods of measurement All
activities defined within the WBS were matched to an activity
group, dependent on the type of activity. These activity groups
were assigned methods and units of measure such that progress could
be monitored for activities within each activity group. An example
is provided in Table 4.4; a comprehensive list is provided in
Appendix B. Table 4.4 - Example: matching methods of measurement to
activity groups Activity Group Method of Measurement Unit Backfills
Type E m3 Cabling Type D lm Demobilisation Type C % Energisation
Type A ea 4.3 Digital DSR development The digital form was created
for use on a desktop, tablet, and mobile device. The desktop view
is shown in Figure 4.2. The tablet and mobile views are in Appendix
D. This form was published for use through all mediums, and as such
was installed on the MS SharePoint site, and was made available for
install through the Formotus application. Progress measurement was
the focus, however in updating the existing form, several data
capture requirements were maintained, such as the Foremans end of
shift checklist. Consultations with FM/SE indicated difficulties in
using the pilot DSR form. Aptitude with technology was a problem
for some, which led to a general dissatisfaction with the imposed
development. Navigating for activities through the WBS was
unfamiliar and criticised. Adjustments to the pilot form were made
in light of the feedback received. Note: the digital form presented
in Figure 4.2 is the final iteration of its development after
feedback provided by FM/SE. The pilot form is attached in Appendix
C.
30. 21 Figure 4.2 - Digital DSR: desktop view Users entered
progress dependant on the type of activity, selected through the
activity groups established and the detailed location of that
activity within the site - this information comes from the WBS. The
process is established in Figure 4.3 Figure 4.3 - Entering progress
into digital DSR
31. 22 Time expenditure for re-engineered digital DSR processes
in Table 4.5 was determined in collaboration with the project, in
particular, through the pilot implementation of the form. Feedback
from FM/SE completing the form on-site informed the effectiveness
of its implementation from a time-saving point of view. Table 4.5 -
Re-engineered processes based on the digital DSR form Digital DSR
Process Time expected (mins) On-site processes 10 Fill out
structured digital form on mobile device 5 Finalise digital form on
mobile device 5 Automated sending 0 Off-site processes 5 Quality
check and approval of received daily reports 5 Automated assembly
of daily report 0 In comparison to the initial paper-based DSR
processes, significant time-savings were observed both on-site and
off-site. Completing a structured digital form reduced duplicated
work - all previously handwritten notes were effectively converted
into a digital format in the one process step. The digital DSR
forms were electronically stored on the MS SharePoint site ready
for review. The daily reports were automatically assembled for
publishing. Time savings were estimated through this process at 53
minutes per day. Assuming 6 sites operating on any one day and 23
working days per month, the time savings accumulate to 148 working
days per year. 4.4 Focus group The success of the digital DSR not
only depended on its initial development and ability to query data
from external sources in a singular interface, but also whether
available activity progress data was useful. The focus group
addressed these issues as per the research aims, and four recurrent
themes were explored through a qualitative analysis by grouping the
main ideas discussed. The coded transcript is provided in Appendix
E. 4.4.1 Activity mapping As expected, it was identified that the
schedule and cost breakdowns were separate entities. Despite
covering the same project, the two breakdowns did not match: the
WBS doesnt talk to the Cost Breakdown Structure, CBS. This
incompatibility made it difficult to map costs to their schedule.
The level of detail within each breakdown structure differed. Costs
were broken down into items that could be budgeted, and actual
costs measured against. Schedule activities were
32. 23 broken down into progress measureable items, and as such
were required in more detail: the problem is with cost codes, you
want to keep that to a realistic amount of things to group together
to make it not too much detail. But with the program obviously we
want to break it up into more detail. Ensuring a level of detail at
which costs could be aggregated to map to schedule activities was
important in calculating EVA metrics for each of these activities.
Schedule activities needed budgeted and actual costs in order to
make this possible. Due to the identified lack of cohesion between
the WBS and CBS, the approach in doing so was to laboriously
calculate costs on a case-by-case basis: wed look at the progress
claim and see how the activities are broken up, and then wed work
out which ones of these cost centres relate to which of those
progress items, and then wed add them together and do the
percentages, manually at the moment. 4.4.2 Progress calculations
Physical calculation required quantity data to establish EVA metric
calculations. The source of this data was necessary for both the
original calculations carried out by the engineers, as well as for
EVA calculations under the proposed method identified in Phase I of
the study. As such, the delivery of this quantity information was
established: that comes from survey information and an original
strata model that was developed based on the borehole logs to work
out how much of each type of material there was. Likewise, the
source of cost data was needed to feed the proposed methods of
calculation. Forecast costs - market research, quotes - were
distinguished from actual costs: forecast is just our budgetwe are
putting actual cost into ROVER and tracking those. There was a
consensus that existing calculation methods were complex and
confusing. Calculating budgeted and actual costs, and mapping these
costs to schedule activities in order to submit a progress claim,
was a task that occupied a significant amount of time: its a pretty
big effort. The complexity of this process, and the back-and-forth
calculations and mapping involved, detracted from the actual
engineering work to be performed on-site: were accountants, were
not really engineers. An example calculation was explained for a
Capping Beam (Appendix E). The existing approach was primarily
beneficial in justifying expenditure with the amount of progress
completed to date: it makes it easier to justify that youve spent
this money, and youve earned this value. Justification was
important when deviations from the forecast were experienced.
33. 24 4.4.3 Industry perspective A proposed course of action
for mapping the WBS and CBS sparked a positive response. By
defining a level of detail such that cost data and activity
progress could collate and match, EVA metrics could be calculated
without restricting the engineers nor changing either breakdown
structure: people can still have the freedom to define activities
how they need toand you can make these talk to each other a lot
better. The group deemed the accuracy of proposed progress
calculations to be sufficient by being justifiable and explainable:
that is close enough to this to make sense. 4.4.4 Recommendations
The mismatch of activities between the WBS and CBS was attributed
to problems during the tender phase of the project: this needs to
be done at tender, which it wasnt done. Ensuring the WBS and CBS
are compatible from the outset would avoid problems with the
mismatch of breakdown structures. Although the method of progress
measurement proposed in Phase I of the study was agreed upon as a
feasible approach, type D activities did not have a sufficient
enough gate structure to encompass all progress measureable
milestones: [weve] got about 10 steps, youve got about five. A more
rigorous approach to defining gates for each type D activity was
recommended. Semi-automation was seen as a good intermediary step.
Some data entry was inevitably required, but the advantages of
automated calculation was acknowledged: if that part of it could
all be automated, thatll save us heaps of time. 4.4.5 Focus group
summary The focus group responded to the research questions it set
out to answer. Several key points were discussed. i. The WBS did
not correlate with the CBS due to their isolated development. ii.
Giving PEs the agency to define level 5 activities to map to the
CBS would circumnavigate most mapping issues. iii. Existing
progress calculations were complicated and time-consuming. iv. The
proposed solution was adequately justifiable and thus well
received. v. Type D activity gates were insufficiently
defined.
34. 25 Chapter 5 Progress visualisation 5.1 Progress
measurement calculation 5.1.1 Data sourced Informed by the focus
group, the existing software infrastructure was realised. Data
required for cost and schedule progress tracking was sourced from a
variety of databases, as outlined in Figure 5.1. Figure 5.1 - Data
sourced from databases Establishing a coding system was paramount
to the interoperability of data. It was found that costs and
schedules were established separately - the WBS was defined as per
the work to be done, whereas the CBS was defined as per the likely
expenses. In light of this, the level 5 schedule program of the
WBS, which were progress-measureable activities or tasks defined as
required by project engineers to carry out the defined level 4
program, was matched to the level 2 cost breakdown. The existing
many-to-many relationship between the two was problematic, Project
Planners (PPs) reorganised the schedule to ensure a one-to-many
relationship. Cost codes and associated budgeted rates as defined
in the tender phase of the project were entered directly into MS
SharePoint. The CostX system was the source of cost code
quantities, to be entered by PEs. Material and plant costs were
tracked digitally through the ROVER system. Subcontractor
35. 26 costs were issued monthly via email and as such were
kept track by PEs and entered into the MS SharePoint site. Progress
data was extracted from submitted DSRs using a SharePoint Designer
workflow (Appendix F) and listed in MS SharePoint as per the
measurement type. Primavera P6 provided scheduling data. All data
was pooled into Excel using Power Query M code (Appendix G). 5.1.2
Activity progress In order to define the EVA metrics required,
percentage complete of all activities in progress needed to be
defined. Types A, B, and C were inclusive of a percentage complete
measure; type D activities used a gates-based system to calculate
percentage complete; type E activities measured quantities
complete, which was measured against a reference budgeted unit rate
to calculate EV metrics. All type A, Type B, and Type C activities
had percentage complete calculations included in the initial data
captured - within the DSR at the discretion of the FM/SE.
Percentage complete was accumulated to the report date for each
entry. Activity EV ($) = Accumulated Progress (%) Budgeted Value
($) Type D activities followed a rigid gates-based percentage
complete accumulation, however activities were further subdivided
into objects. Engineers were able to assess progress of all objects
that fell under an activity, all of which followed the same gate
structure. Activity progress was an accumulation of each objects
percentage complete, as calculated from the gate-structure.
Percentage complete was calculated by determining the previous
report dates accumulated gate weighting, and subtracting it from
the current report dates accumulated gate weighting, specific to
the object. This accommodated for the user skipping gates for an
object - the correct percentage complete was calculated. Object
Progress (%) = Accumulated Progress - MAX (Previous Accumulated
Progress) Object EV ($) = Object Progress (%) Budgeted Value ($)
Activity EV ($) = Object EV ($) All type E activities used a
quantity-based measurement that related to the budgeted quantity
entered in the MS SharePoint site. However, budgeted unit rates
were the prevailing factor for calculations. They were used as
opposed to budgeted final values to deal with incorrect estimated
quantities - the likelihood that actual progress exceeds or falls
short of estimated quantities was high. Using budgeted quantities
to calculate percentage complete was inappropriate here as once the
budgeted quantity was reached, the EV would reach a maximum. In
reality, this is not the case. Metric EV ($) = Metric Quantity
(units) Budgeted Unit Rate ($)
36. 27 Activity EV ($) = Metric EV ($) All entries were
appended into one table in order to calculate PV and AC metrics.
The benefit of this approach is that for activities that extend
across several measurement types, PV and AC measurements are not
duplicated. AC was aggregated for all entries between successive
entries of activity progress. This allowed final accumulation of AC
to avoid duplication. Budgeted costs for PV calculation were
aggregated for each activity. Activity AC ($) = Accumulated AC ($)
- MAX (Previous Accumulated AC) Duration to Date (days) = Report
Date - Start Date Accumulated PV ($) = Duration to Date (days) ($)
() Activity PV ($) = Accumulated PV ($) - MAX (Previous Accumulated
PV) Time-phased graphs, filterable by activity or associated cost
codes, were created in the Excel file, which was stored on the MS
SharePoint site for multi-user access. The graphs were published
and viewable directly through the MS SharePoint webpage to give PEs
direct feedback on activity progress. ViCon 3DBIS is a management
tool and was thus only required by those in a position to control
the project. Both, however, used the same data to communicate
progress 5.1.3 Activity status The status of metrics and objects
within Type D and E activities largely determined the status of an
overall level 4 activity. Activity status parameters included Not
Started, In Progress, and Completed. If any object or metric within
an activity was currently set to In Progress, the whole activity
reciprocated. If all objects or metrics were Completed, the
activity was set to Completed. Likewise, if all objects or metrics
were Not Started, the activity was set to Not Started. 5.1.4
Summary activity progress Activity progress was accumulated to
level 4 of the schedule - summary activities. This informed EV for
progress claims. All EVA metrics were calculated by accumulating
their associated level 5 activities. Summary Activity EV ($) =
Activity EV ($) Summary Activity AC ($) = Activity AC ($) Summary
Activity PV ($) = Activity PV ($)
37. 28 5.2 Dynamic connection in 5D BIM The 5D model sourced
data from the Excel file and WBS lists stored on the MS SharePoint
site. A dynamic link was created using QlikView coding (Appendix H)
such that data was refreshable. Level 4 schedule activities were
linked to individual objects in the 3D model. Progress calculations
from the Excel file were mapped through activity codes to the WBS
such that selection of specific activities by the user was more
easily facilitated. Likewise, the most recent activity statuses
calculated from the Excel file were linked directly to activities
under the WBS. All links are viewable in Figure 5.2. Figure 5.2 -
Relational database established in QlikView 5.2.1 System interface
Real-time data was viewable through the two-window interface
provided in ViCon 3DBIS, shown in Figure 5.3.
38. 29 Figure 5.3 - 5D BIM cost and schedule data visualisation
EVA graphs were created from the available metrics and
calculations. A colour scheme was created for activities flagged as
Not Started, In progress, and Completed. Interaction with the 3D
model allowed users to select single or groups of objects, and view
the cost and time progress specific to those objects through the
EVA chart and schedule progress rendered 3D model. Conversely,
users could use parameters within the WBS to reduce the list of
activities to only those required, and view them in isolation or in
the context of the entire site, while viewing their associated cost
and time progress. 5.3 Activity progress processes In accordance
with implementation, processes were necessarily developed to
determine how the system fits in with existing software
infrastructure and business processes.
39. 30 Figure 5.4 - Semi-automated solution processes All users
interact with the solution system as described in Figure 5.4. Using
this, a guide was developed to inform users of the process. The
process guide is provided in Appendix I.
40. 31 Chapter 6 Discussion Development of the digital form and
the integration of data into the progress visualisation tool were
successful. The relevance of this to the existing construction
market is analysed in the context of current research. 6.1 Digital
form development Attempts to measure progress across construction
sites have underestimated the complexities inherent in large-scale
infrastructure. The developed form adopts the aims of project
monitoring, to collect activity progress data in line with lean
construction principles. This is not a novel approach, with ADC
technologies falling under the lean brand, however a focus on a
holistic, flexible, tablet-based digital DSR is undocumented in the
literature. Of primary importance for successful implementation was
an assessment of standardisation, and user experience. 6.1.1
Standardisation The transformation to digital means of data capture
stresses standardisation such that data can be used for their
intended purposes. Of course, existing processes define such
structures from the outset through the WBS and CBS, and the cost
and schedule data flow to and from each. However the two do not
necessarily correlate. In this case each was developed in
isolation, which caused problems for being able to measure progress
on WBS activities, and ascertain cost data for these. In attempting
to map the two breakdowns, a many-to-many relationship was
observed. Databases rely on a single direction of movement; that
is, by definition, they strictly understand one-to-many
relationships. This hindered the development. As such, it was
necessary for PPs to restructure the WBS, and PEs to laboriously
map it to the CBS. The construction phase is not the desired
environment to implement a digital solution as proposed - the
inherent constraints render this difficult (Matthews et al., 2015).
Standardisation of progress measureable activities was a less clear
determination - the flexibility required on-site due to the
complexity of work required a less structured affiliation with
scheduled activities. Initial attempts to measure progress through
the pilot digital DSR
41. 32 indicated that activities were often not adequately
refined to meaningfully measure progress. This was also found in
the study by Turkan et al. (2012), however the flexible nature of
the proposed solution lent itself to accommodating for the
measurement of a wide range of activities. PEs were given the space
to define progress measurable tasks as they saw fit while ensuring
that they related back to the standardised WBS. This standardised
the activity progress measurements in the digital DSR. Methods of
measure replaced existing calculations to provide a standard,
predictable, and simple solution to progress measurement. Existing
calculations were unnecessarily complex - PEs noted the significant
time and effort spent in engaging with complex EVA calculations.
The accuracy of the proposed methods of measure was not analysed,
however of primary importance to PEs in spite of accuracy was the
ability to comprehend and justify calculations. They appeared to be
more concerned with being able to prove progress rather than to
accurately portray it. This fits in with their role as monitors of
progress. Where control seemingly relies on regular and accurate
progress communication, progress monitoring in and of itself seeks
to communicate that progress whether accurate or not. It is not
necessarily in the best interests of the communicators to ensure
the approach to measurement is rigorous as they are not necessarily
controllers themselves. Whether this is significant should be
subject to further research as it is necessary to postulate to what
degree accuracy is useful in serving project controlling purposes.
6.1.2 User experience The design of the tool was pivotal to a
positive reception. The pilot form was scrutinised for being too
complex and confusing for ease of use on-site. Primarily, the
identification of activities through the WBS was unfamiliar to
FM/SE. Initial efforts to cater for this used a four-week look
ahead table within the form (Appendix C) for FM/SE to locate
activities and their associated WBS parameters such that these
parameters could be entered in the progress table to again find the
activity. This was a meandering approach. The final digital DSR
development simplified this process by using the activity groups
already established for each activity. These categorised activities
into understandable clusters. Consequently, activities were chosen
by selecting activity groups and detailed location. This was
sufficient to narrow down the activity list to a manageable select
few. On that note, simplicity was important in ensuring FM/SE were
not overburdened, as forewarned from existing literature (Chin et
al., 2005; Russell, 1993). FM/SE were found to regularly update
repeated information on consecutive days. Using a template specific
to users meant simpler and less repetitive data capture on-site.
Similarly, the tablet and mobile views
42. 33 reduced data fields to only those required for activity
progress monitoring, as shown in Figure 6.1. Again, users were not
overburdened with excessive data entry. Figure 6.1 - Digital DSR:
tablet view Allowing users offline access in remote areas of the
construction site by preloading data into the form was convenient,
however the most updated data was not able to be queried from the
MS SharePoint site in this process. Convenience was a focus of the
digital forms development. Having standardised data entry in a
digital format reduced free text data capture such that FM/SE did
not have to describe progress in prose (Russell, 1993). Railroading
users in this way meant that the data captured was useful, however
in a similar vein, it was not necessarily practical. In particular,
by the complexity of planned works requiring a more refined level
of the WBS to be tracked against, elements within level 4
activities needed to be tracked separately. On a large
infrastructure project, the number of activities worked on at a
site can be numerous, let alone tasks within those activities. The
proposed design runs the risk of obliging FM/SE to track a large
amount of tasks through the digital form. Perhaps completing this
form on a computer device is more practical, however needing
handwritten notes to do so guarantees duplicated work. Regardless,
the form spans both tablet and computer-based mediums and as such
can cater for such circumstances. Emulating the existing DSR meant
that FM/SE were familiar with the digital form from the onset,
smoothing the transition to the proposed system. In addition to
tracking activity progress, labour and material delivery
information was included in the final digital form development.
Despite similar approaches as outlined by Navon and Haskaya (2006)
and Chin et al. (2005), labour and material delivery data capture
are irrelevant here. Tracking material delivery through daily
dockets entered into the ROVER system, and having personnel login
to their workstations through the Onsite Track Easy solution
already implemented on-site, meant data was collected twice,
disregarding lean construction
43. 34 principles. In attempting to inform lean construction,
modern progress monitoring processes and solutions themselves need
to avoid waste. 6.2 Progress visualisation 6.2.1 Cloud-based 5D BIM
Issues in data integration are frequently encountered in ICT
systems. Existing solutions in literature necessarily overcame
interoperability issues in attempting to collate data (Matthews et
al., 2015). Different data formats and file types make it difficult
to access data, particularly in automating data transfer.
Application Programming Interfaces (APIs) allow databases to
communicate, but they need to be developed for each software
package interface. MS SharePoint gets around data interoperability
issues by acting as a central data repository. Software vendors
only need one API to MS SharePoint, a commonly used system, to
integrate their data systems. ViCon 3DBIS is able to mine this data
once it is in MS SharePoint, acting as a cloud-based BIM. This
allows multi-user access to the data crucial to communicating
progress. In order to view this in a BIM, users needed specialised
software installed on their desktop computer. However, as was the
nature of the arrangement with the software vendor, providing the
service to all involved in the progress monitoring process was
cumbersome and impractical. Viewing data outside the context of the
BIM was made available through the cloud for those attempting to
communicate progress. Those reliant on the BIM to understand
progress on-site, were given access to the ViCon 3DBIS software
package. In allowing a wide-spread solution for industry,
alternative BIM viewers are assessed through those utilised in
research. Several progress monitoring solutions use specialised
software to communicate progress (Kim et al., 2010), however
software such as Autodesk NavisWorks is ubiquitous in large-scale
infrastructure. Matthews et al. (2015) advocate using the
iConstruct plug-in to align the breakdown of the model to the tasks
within the schedule. The software is not the focus of either study
- it is unanimously understood that by establishing correct data
flows, any multi-dimensional BIM viewer is applicable so long as
data is matched as per conventional database structures. Kim et al.
(2010) suggest that viewing cost and schedule data in the
conventional sense, through text and tables, is difficult to
understand and captured information is often neglected. The results
of this study indicate a drastic improvement in visualisation by
combining this data with a 3D model, however like Kim et al.s
study, it fails to quantify this improvement. Regardless, the
theoretical benefits are realised. Being able to visualise the
44. 35 flow of work in progress allows the direct application
of lean techniques that make modern manufacturing processes
successful (Sacks et al., 2009). Real-time data is visualised
through the 5D model. Matthews et al. (2015) promote real-time
project monitoring in developing strategies to improve workflows
and mitigate rework and delays. However the established processes
in the construction-phase of the project were a significant
obstacle to interoperability. This reduced the effectiveness of
real-time information transfer. Interoperability issues in this
research were circumnavigated as previously discussed. In contrast
to Matthews et al.s study, the cloud-based database used was
compatible with existing software systems and as such enabled
real-time data transfer. Progress data visualisation times were
reduced from the weekly progress report to almost instantaneous
viewing capabilities, facilitating the coordination process as
found by Golparvar-Fard et al. (2009). 6.2.2 EVA method Solutions
to communicating progress data vary in the modern context. Well
established methods such as EVA are perhaps being phased-out by
those that give significance to workflow. EVA is centred around the
assumption that activities are not interdependent (Kim and Ballard,
2010). In reality, the consequences of such a narrow-minded view
results in lower productivity achieved by the whole system. In
spite of this, visualising progress through EVA was needed in the
development as industry professionals were already familiar with
the concept. In avoiding mass overhaul and overwhelming those
involved, the research proposed progress visualisation through
strictly non-lean methods. Lean construction principles were
sacrificed in favour of simpler implementation, however the
application of EVA in the context of BIM argues the contrary. The
results of the development indicate that EVA metrics of singular or
groups of activities within their context, may provide an
understanding of workflow. Zhang et al. (2014) followed this notion
to suggest that EVA can inform the adjustment of work to achieve
steady workflow. The 5D model allows users to interpret progress in
relation to the activities around it. Naturally, as one activity is
delayed, it affects those that immediately follow it. By
understanding localised EVA parameters within a BIM, we can
navigate to the root of the problem. In fact literature fails to
provide a solution to visualising progress with respect to
workflow. It is inherently difficult to analyse workflows and
identify issues hidden within them, particularly when those
workflows are themselves variable. The Last Planner System (LPS)
gives credit to workflow by accounting for lack of short-term
knowledge and weekly planning (Koskela et al., 2010). Workflow
measurement is
45. 36 an underlying principle analysed by Koskela (2000) - the
focus of monitoring workflow through measurement involves reducing
the risk of variability propagation downstream by encouraging
continual assessment. This is seemingly in line with the
development, with both being derived from lean principles. The
measurement tool responsible for progress tracking in the LPS is
the Percent Plan Complete (PPC) index. Priven et al. (2014) define
it as almost the only measure of workflow stability in planning,
but it does not communicate stability in progress. The PPC method
alone does not cater for workflow visualisation - perhaps in the
context of BIM, this method will yield similar results. Yet the
method of visualisation is almost irrelevant. Ensuring the data is
captured from the construction site allows data flows to
communicate progress through any lens, be it EVA or otherwise. In
this context, the proposed solution merely investigates the
feasibility of communicating progress in real-time; this was
achieved. In actual fact, the EVA visualisation requirements were
set by the project. This is to be expected; it is also changeable
to workflow visualisation methods as they are improved through
future research. 6.3 Feasibility of implementation The time-saving
benefits of implementing the proposed lean solution are realised -
it was estimated to save 53 minutes per day, translating to 148
working days per year. However the developments feasibility is
pivotal to its adoption. The acceptance of new processes during the
construction phase, particularly by those involved such as FM/SE
and PEs, largely determines its effectiveness and use.
Significantly, the users are heavily relied on to be adequate in
using technology. Just as Russell (1993) found variability in
skillsets of those completing DSRs, the same variability was
observed for their capacity to use technology. Be it attributed to
cultural issues or otherwise, there was an apprehension towards
implementing the system. The proposed solution inherently conveys
transparency of happenings on-site, and as Russell suggests,
availability of such data can be incriminating. Such a stigma can
be harmful for the implementation of any similar system. Likewise,
the solution revolves around collaboration between parties. FM/SE
need the PEs to enter quantities, objects, budget rates, and cost
codes for them to be able to complete a DSR. PEs need FM/SE to
regularly complete DSRs to have the most up-to-date data for
reporting purposes. PMs and PPs rely on PEs to provide them with
progress data in real-time to enhance project control. A breakdown
in the process downstream hinders effective progress controlling
upstream. In this way, the process is circulated by a constant
awareness of each partys contribution - if FM/SE fail to complete a
DSR, it is in the best interest of those up the line to ensure this
is rectified.
46. 37 Those associated with the process need to have a clear
understanding of their involvement. The process guide was developed
with this intention. Primarily, it is a blueprint for the
implementation of the entire solution. In response to issues
identified by Majrouhi Sardroud (2015) and a general focus on
processes in a number of studies (Matthews et al., 2015), the guide
can be used to assist implementation by focusing on the processes
critical to its success. It is simple, specific to each type of
user, while also communicating the intention of the solution as a
whole. 6.4 Limitations Ensuring implementation of the solution is
suitable to business needs requires a consideration of existing
infrastructure, and thus an und