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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

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  1. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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