Automated construction progress tracking is becoming critical to efficient and effective construction management. More and more construction companies are putting aside the old way of tracking progress, which was mainly based on foremen daily reports and visual inspections, and are adopting 3D sensing technologies as a new and modern way of tracking progress. Technologies such as 3D laser scanners (LADARs) are investigated as a means to acquire comprehensive 3D point-cloud data which can then be studied by management to determine the progress of construction. Although being much more accurate and efficient than visual inspections, this new progress tracking approach can be improved by applying object recognition algorithms that enable an automated progress tracking. This new approach has been investigated by other researchers, but only for progress tracking of structural elements. This study focuses on mechanical objects such as pipes and ducts, which would give the progress tracking a better level of detail and a wider scope. The investigation is carried out on a field database acquired during the construction of the Engineering VI Building at the University of Waterloo. It was found that the laser scanning technology is a suitable method for acquiring point-clouds of pipes and ductwork, and also that the object recognition algorithm used in this study allows a progress tracking as well as a quality tracking of the HVAC system installation.

Automated construction progress tracking is becoming critical to efficient and effective construction management. More and more construction companies are putting aside the old way of tracking progress, which was mainly based on foremen daily reports and visual inspections, and are adopting 3D sensing technologies as a new and modern way of tracking progress. Technologies such as 3D laser scanners (LADARs) are investigated as a means to acquire comprehensive 3D point-cloud data which can then be studied by management to determine the progress of construction. Although being much more accurate and efficient than visual inspections, this new progress tracking approach can be improved by applying object recognition algorithms that enable an automated progress tracking. This new approach has been investigated by other researchers, but only for progress tracking of structural elements. This study focuses on mechanical objects such as pipes and ducts, which would give the progress tracking a better level of detail and a wider scope. The investigation is carried out on a field database acquired during the construction of the Engineering VI Building at the University of Waterloo. It was found that the laser scanning technology is a suitable method for acquiring point-clouds of pipes and ductwork, and also that the object recognition algorithm used in this study allows a progress tracking as well as a quality tracking of the HVAC system installation.

One of the problems when developing software is the difficulty of knowing how much that is done in a project. This is a basic condition to be able to estimate the remaining efforts with increased accuracy over time. To get accurate progress information it is important that the progress tracking is done in an objective way and also in an as simple way as possible. Our focus in this work has been software projects in general but a case study has also been performed at Ericsson Software Technology AB in Ronneby. We have studied the organization and performed interviews with project managers to find out if this really is a problem and if the process can be improved in some way to ease the task of progress tracking. This case study together with our literature study has resulted in a proposition for a solution. Our approach has been to use automated testing as a way to make progress tracking more objective. The result presented in this thesis is a base for a system that could ease the tracking of progress. In short, the system extracts information from an automated testing process and compares it with estimated figures to be able to automatically generate progress information. / 0708-574327

The documentation of complete and timely as-built information related to construction projects is essential for tracking progress, planning corrective action, and analyzing the schedule. The collection of site information, however, is currently a challenging, time-consuming, and error-prone manual process. To improve the tracking of as-built information, this research focused on the development of a low-cost voice-visual framework that utilizes commonly available communication tools such as email and interactive voice response (IVR). The goal of this research was to create project-wide bidirectional communication between site personnel and head office to automate the tracking of daily site information. The research involved an in-depth analysis of the possible site events and progress-tracking needs related to construction activities. Accordingly, activity-specific email forms and logical-flow diagrams were developed as a means of facilitating site data collection. A framework was then developed that integrates several components: the developed tracking forms; a cloud-based IVR service; a customized scheduling application; and an email application. During construction, the automated system identifies eligible activities to be tracked; collects as-built details from the relevant supervisors; and uses the daily time segments of the schedule as an integrated depository for all as-built details, including progress information, events by all parties, and requests for information (RFIs), quality/safety issues, and other video/audio/drawing-markup notes. The developed system generates detailed as-built schedule that clearly show the evolution of all as-built events and their accurate timing on the daily segments for each activity. The project schedule is thus converted from a static report into information-rich, visualization media, and decision-support tool that provides decision makers with timely progress details so that they can easily follow the project progress , facilitates schedule updates, facilitates accurate schedule forensics, delay analysis, , and the planning of appropriate corrective action. The developed framework was validated though a number of case studies that demonstrated its usefulness and practicality. This research contributes to construction efficiency through the facilitation of bidirectional communication between site personnel and head office and the provision of timely and legible as-built data for decision-making. Ultimately, the research will assist construction firms to have better control over construction projects and more effective decisions during construction through improved communication.

The documentation of complete and timely as-built information related to construction projects is essential for tracking progress, planning corrective action, and analyzing the schedule. The collection of site information, however, is currently a challenging, time-consuming, and error-prone manual process. To improve the tracking of as-built information, this research focused on the development of a low-cost voice-visual framework that utilizes commonly available communication tools such as email and interactive voice response (IVR). The goal of this research was to create project-wide bidirectional communication between site personnel and head office to automate the tracking of daily site information. The research involved an in-depth analysis of the possible site events and progress-tracking needs related to construction activities. Accordingly, activity-specific email forms and logical-flow diagrams were developed as a means of facilitating site data collection. A framework was then developed that integrates several components: the developed tracking forms; a cloud-based IVR service; a customized scheduling application; and an email application. During construction, the automated system identifies eligible activities to be tracked; collects as-built details from the relevant supervisors; and uses the daily time segments of the schedule as an integrated depository for all as-built details, including progress information, events by all parties, and requests for information (RFIs), quality/safety issues, and other video/audio/drawing-markup notes. The developed system generates detailed as-built schedule that clearly show the evolution of all as-built events and their accurate timing on the daily segments for each activity. The project schedule is thus converted from a static report into information-rich, visualization media, and decision-support tool that provides decision makers with timely progress details so that they can easily follow the project progress , facilitates schedule updates, facilitates accurate schedule forensics, delay analysis, , and the planning of appropriate corrective action. The developed framework was validated though a number of case studies that demonstrated its usefulness and practicality. This research contributes to construction efficiency through the facilitation of bidirectional communication between site personnel and head office and the provision of timely and legible as-built data for decision-making. Ultimately, the research will assist construction firms to have better control over construction projects and more effective decisions during construction through improved communication.

In recent years, many researchers have investigated automated progress tracking for construction projects. These efforts range from 2D photo-feature extraction to 3D laser scanners and radio frequency identification (RFID) tags. A multi-sensor data fusion model that utilizes multiple sources of information would provide a better alternative than a single-source model for tracking project progress. However, many existing fusion models are based on data fusion at the sensor and object levels and are therefore incapable of capturing critical information regarding a number of activities and processes on a construction site, particularly those related to non-structural trades such as welding, inspection, and installation activities. In this research, a workflow based data fusion framework is developed for construction progress, quality and productivity assessment. The developed model is based on tracking construction activities as well as objects, in contrast to the existing sensor-based models that are focussed on tracking objects. Data sources include high frequency automated technologies including 3D imaging and ultra-wide band (UWB) positioning. Foreman reports, schedule information, and other data sources are included as well. Data fusion and management process workflow implementation via a distributed computing network and archiving using a cloud-based architecture are both illustrated. Validation was achieved using a detailed laboratory experimental program as well as an extensive field implementation project. The field implementation was conducted using five months of data acquired on the University of Waterloo Engineering VI construction project, yielding promising results. The data fusion processes of this research provide more accurate and more reliable progress and earned value estimates for construction project activities, while the developed data management processes enable the secure sharing and management of construction research data with the construction industry stakeholders as well as with researchers from other institutions.

In recent years, many researchers have investigated automated progress tracking for construction projects. These efforts range from 2D photo-feature extraction to 3D laser scanners and radio frequency identification (RFID) tags. A multi-sensor data fusion model that utilizes multiple sources of information would provide a better alternative than a single-source model for tracking project progress. However, many existing fusion models are based on data fusion at the sensor and object levels and are therefore incapable of capturing critical information regarding a number of activities and processes on a construction site, particularly those related to non-structural trades such as welding, inspection, and installation activities. In this research, a workflow based data fusion framework is developed for construction progress, quality and productivity assessment. The developed model is based on tracking construction activities as well as objects, in contrast to the existing sensor-based models that are focussed on tracking objects. Data sources include high frequency automated technologies including 3D imaging and ultra-wide band (UWB) positioning. Foreman reports, schedule information, and other data sources are included as well. Data fusion and management process workflow implementation via a distributed computing network and archiving using a cloud-based architecture are both illustrated. Validation was achieved using a detailed laboratory experimental program as well as an extensive field implementation project. The field implementation was conducted using five months of data acquired on the University of Waterloo Engineering VI construction project, yielding promising results. The data fusion processes of this research provide more accurate and more reliable progress and earned value estimates for construction project activities, while the developed data management processes enable the secure sharing and management of construction research data with the construction industry stakeholders as well as with researchers from other institutions.

There is shift in the Architectural / Engineering / Construction and Facility Management (AEC&FM) industry toward performance-driven projects. Assuring good performance requires efficient and reliable performance control processes. However, the current state of the AEC&FM industry is that control processes are inefficient because they generally rely on manually intensive, inefficient, and often inaccurate data collection techniques. Critical performance control processes include progress tracking and dimensional quality control. These particularly rely on the accurate and efficient collection of the as-built three-dimensional (3D) status of project objects. However, currently available techniques for as-built 3D data collection are extremely inefficient, and provide partial and often inaccurate information. These limitations have a negative impact on the quality of decisions made by project managers and consequently on project success. This thesis presents an innovative approach for Automated 3D Data Collection (A3dDC). This approach takes advantage of Laser Detection and Ranging (LADAR), 3D Computer-Aided-Design (CAD) modeling and registration technologies. The performance of this approach is investigated with a first set of experimental results obtained with real-life data. A second set of experiments then analyzes the feasibility of implementing, based on the developed approach, automated project performance control (APPC) applications such as automated project progress tracking and automated dimensional quality control. Finally, other applications are identified including planning for scanning and strategic scanning.

There is shift in the Architectural / Engineering / Construction and Facility Management (AEC&FM) industry toward performance-driven projects. Assuring good performance requires efficient and reliable performance control processes. However, the current state of the AEC&FM industry is that control processes are inefficient because they generally rely on manually intensive, inefficient, and often inaccurate data collection techniques. Critical performance control processes include progress tracking and dimensional quality control. These particularly rely on the accurate and efficient collection of the as-built three-dimensional (3D) status of project objects. However, currently available techniques for as-built 3D data collection are extremely inefficient, and provide partial and often inaccurate information. These limitations have a negative impact on the quality of decisions made by project managers and consequently on project success. This thesis presents an innovative approach for Automated 3D Data Collection (A3dDC). This approach takes advantage of Laser Detection and Ranging (LADAR), 3D Computer-Aided-Design (CAD) modeling and registration technologies. The performance of this approach is investigated with a first set of experimental results obtained with real-life data. A second set of experiments then analyzes the feasibility of implementing, based on the developed approach, automated project performance control (APPC) applications such as automated project progress tracking and automated dimensional quality control. Finally, other applications are identified including planning for scanning and strategic scanning.

The increased usage and need for software as part of products has challenged traditional project management, nevertheless for hardware heavy organisations that are used to rely on the linear prediction and tracking of project outcomes. The developments in projects with embedded systems have countless dependencies and almost impossible to predict. Literature shows that software development projects have problems meeting the initial goals of budget, time, and scope. This is discovered too late due to insufficient methods of tracking progress. The purpose of this thesis was to investigate how large agile software development projects can continuously be followed to evaluate their performance and meet initial customer agreements fixed in time, budget, and scope. The thesis was conducted at Saab, active in the defense and security industry. This qualitative exploratory study was conducted with semistructured interviews and focus group discussions at the case company Saab, benchmark interviews with two additional companies, and an extensive literature study. The issues with the existing tracking approach were explored to determine how progress tracking may be created to continuously measure progress and indicate if project goals will be accomplished or not. The more general challenges in software development were also investigated to provide knowledge about areas in need of additional metrics which could indicate the problem and mitigate it. One industry-specific challenge is the security aspect that is unavoidable and requires a lot of documentation that holds up the development activities. Other detected challenges were difficulties in understanding requirements that lead to faulty estimations and work in the wrong direction, undiscovered dependencies that lead to a lot of rework and waiting for additional parts, insufficient testing environments that lead to late feedback, and holds up the development. It was also visible that the projects were conducted with different management approaches and no best-proven practice existed for tracking performance. From an analysis of the empirical data and existing literature, a suggestion of method tracking design was developed for large agile software projects with fixed contracts. The models were proposed to allow flexibility, enable control, and provide a holistic view. As Saab intends to introduce Earned Value Management in their software projects, this method was complemented with COMOD, TRL, IRL, and SRL to provide these three characteristics. Transparency and visibility of both products and processes are also found to be key to project success, thus additional metrics to increase visibility in projects are suggested to enable efficient project leading. / Den ökade användningen och behovet av mjukvara har utmanat traditionell projektledning, speciellt för hårdvaruorganisationer som är vana att kunna förlita sig på den linjära utvecklingen av ett projek. Utvecklingen av projekt som inkluderar inbyggda system med otaliga beroenden är nästan omöjliga att förutsäga. Litteratur visar att mjukvaruutvecklingsprojekt har problem att nå de ursprungliga målen för budget, tid och omfattning. Detta upptäcks för sent på grund av otillräckliga metoder för att mäta framsteg i projekt. Detta examensarbete genomfördes som en fallstudie på Saab, aktiv inom försvar- och säkerhetssektorn. Syftet med denna avhandling har varit att utvärdera hur projektledning för stora agila mjukvaruutvecklingsprojekt kontinuerligt kan följa utvecklingen för att möta de ursprungliga kundavtalen som är fastställda i tid, budget och omfattning. Denna kvalitativa undersökningsstudie genomfördes med semistrukturerade intervjuer och fokusgrupp intervjuer på företaget Saab, benchmarking intervjuer med ytterligare två företag och en omfattande litteraturstudie. För att utvärdera hur en metod för utvärdering av projektstatus ska utformas för att i tid ange om projektmålen inte kommer att uppnås, undersöktes utmaningarna med mjukvaruutveckling och därifrån har möjliga mätvärden och metoder för att mildra eller upptäcka dessa problem utvärderats. Några av de upptäckta problemen verkar överlappa flera industrier medan andra verkar vara mer specifika för just militär- och försvarsindustrin. En branschspecifik utmaning är säkerhetsaspekten som är oundviklig och kräver mycket dokumentation som stannar upp utvecklingsaktiviteterna. Andra upptäckta utmaningar var svårigheter att förstå krav som leder till felaktiga uppskattningar och arbete i fel riktning, oupptäckta beroenden som leder till mycket omarbetning och väntande på ytterligare delar, otillräckliga testmiljöer som leder till sen feedback och håller upp utvecklingen. Stora skillnader i de metoder som idag tillämpas från projektledning i dessa projekt var synligt under projektet, vilket indikerar på att det idag inte finns någon accepteras bästa metod i uppföjlning. Från analys av samlad empirisk data samt befintlig litteratur utvecklades ett förslag på hur en metod för uppföljning av stora agila mjukvaruprojekt skulle kunna se ut. Design på föreslagen modell skulle möjliggöra flexibilitet och kontroll samt förmedla ett helhetsperpektiv. Eftersom Saab avser att introducera Earned Value Management i sina mjukvaruprojekt kompletterades denna metod med COMOD, TRL, IRL och SRL för att få dessa tre egenskaper. Öppenhet och synlighet för både produkt och process visar sig också vara nyckeln till framgång i projektutveckling, vilket är möjligt med ytterligare mått för att öka synligheten i projektet.