The Experts below are selected from a list of 360 Experts worldwide ranked by ideXlab platform
Mario Vanhoucke - One of the best experts on this subject based on the ideXlab platform.
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using real Project schedule data to compare earned schedule and earned duration management Project time forecasting capabilities
Automation in Construction, 2019Co-Authors: Paulo Andre De Andrade, Mario Vanhoucke, Annelies MartensAbstract:Abstract Since Project Control involves taking decisions that affect the future, the ability to accurately forecast the final duration and cost of Projects is of major importance. In this paper, we focus on improving the accuracy of Project duration forecasting by introducing a forecasting approach for Earned Value Management (EVM) and Earned Duration Management (EDM) that combines the schedule performance and schedule adherence of the Project in progress. As the schedule adherence has not yet been defined formally for EDM, we extend the EVM-based measure of schedule adherence, the p-factor, to EDM and refer to this measure as the c-factor. Moreover, we aim to improve the ability to indicate the expected forecasting accuracy for a Project by extending the EVM concept of Project regularity to EDM. The introduced forecasting approach and the EDM Project regularity indicator are applied to a large number of real-life Projects, mainly situated in the construction sector. The conducted empirical experiment shows that the Project duration forecasting accuracy can be increased by focusing on both the schedule performance and schedule adherence. Further, this study shows that the EDM Project regularity indicator is indeed a more reliable indicator of forecasting accuracy.
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a buffer Control method for top down Project Control
European Journal of Operational Research, 2017Co-Authors: Annelies Martens, Mario VanhouckeAbstract:Abstract Timely completion of Projects is an important factor for Project success. However, Projects often exceed their predefined deadline, which results in a late Project delivery and an increase in the total Project cost. In order to increase the probability of timely completion, a Project buffer can be planned at the end of a Project. During Project execution, an assessment of the total buffer consumption at the Project completion date can be made in order to periodically monitor the Project progress. When the expected buffer consumption is higher than 100%, the Project deadline is expected to be exceeded and the Project manager should take corrective actions to get the Project back on track. In this paper, a new buffer monitoring approach is introduced, which sets tolerance limits for Earned Value Management/Earned Schedule (EVM/ES) schedule performance metrics by allocating the Project buffer over the different Project phases. The purpose of these tolerance limits is to provide the Project manager with accurate and reliable information on the expected Project outcome during the Project execution. A computational study is carried out to assess the performance of the proposed approach and to compare its performance with traditional buffer consumption monitoring procedures. Additionally, existing performance metrics for tolerance limits have been put into a hypothesis testing framework, and new metrics have been developed in order to fill the detected gaps in performance measurement. Results have shown that the proposed tolerance limits improve the performance of the monitoring phase, especially for parallel Projects. Consequently, the underperformance of EVM/ES for parallel Projects is mitigated by these limits.
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improving Project forecast accuracy by integrating earned value management with exponential smoothing and reference class forecasting
International Journal of Project Management, 2017Co-Authors: Jordy Batselier, Mario VanhouckeAbstract:In this paper, the earned value management (EVM) Project Control methodology is integrated with the exponential smoothing forecasting approach. This results in an extension of the known EVM and earned schedule (ES) cost and time forecasting formulas. A clear correspondence between the established approaches and the newly introduced method – called the XSM – is identified, which could facilitate future implementation. More specifically, only one smoothing parameter is needed to calculate the enhanced EVM performance factor. Moreover, this parameter can be dynamically adjusted during Project progress based on information of past performance and/or anticipated management actions. Additionally, the reference class forecasting (RCF) technique can be incorporated into the XSM. Results from 23 real-life Projects show that, for both time and cost forecasting, the XSM exhibits a considerable overall performance improvement with respect to the most accurate Project forecasting methods identified by previous research, especially when incorporating the RCF concept.
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an overview of Project data for integrated Project management and Control
The Journal of Modern Project Management, 2016Co-Authors: Mario Vanhoucke, Jose Coelho, Jordy BatselierAbstract:In this paper, an overview is given of the Project data instances available in the literature to carry out academic research in the field of integrated Project management and Control. This research field aims at integrating static planning methods and risk analyses with dynamic Project Control methodologies using the state-of-the-art knowledge from literature and the best practices from the professional Project management discipline. Various subtopics of this challenging discipline have been investigated from different angles, each time using Project data available in literature, obtained from Project data generators or based on a sample of empirical case studies. This paper gives an overall overview of the wide variety of Project data that are available and are used in various research publications. It will be shown how the combination of artificial data and empirical data leads to improved knowledge on and deeper insights into the structure and characteristics of Projects useful for academic research and professional use. While the artificial data can be best used to test novel ideas under a strict design in a Controlled academic environment, empirical data can serve as the necessary validation step to translate the academic research results into practical ideas, aiming at narrowing the bridge between the theoretical knowledge and practical relevance. A summary of the available Project data discussed in this paper can be downloaded from http://www.Projectmanagement.ugent.be/research/data VIDEO about paper: https://youtu.be/9VESaMeh3nI
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a multivariate approach for top down Project Control using earned value management
Decision Support Systems, 2015Co-Authors: Jeroen Colin, Mario Vanhoucke, Annelies Martens, Mathieu WautersAbstract:Project monitoring and the related decision to proceed to corrective action are crucial components of an integrated Project management and Control decision support system (DSS). Earned value management/earned schedule (EVM/ES) is a Project Control methodology that is typically applied for top-down Project schedule Control. However, traditional models do not correctly account for the multivariate nature of the EVM/ES measurement system. We therefore propose a multivariate model for EVM/ES, which implements a principal component analysis (PCA) on a simulated schedule Control reference. During Project progress, the real EVM/ES observations can then be Projected onto these principal components. This allows for two new multivariate schedule Control metrics (T2 and SPE) to be calculated, which can be dynamically monitored on Project Control charts. Using a computational experiment, we show that these multivariate schedule Control metrics lead to performance improvements and practical advantages in comparison with traditional univariate EVM/ES models. Two multivariate Project schedule Control metrics are presented using well-known EVM metrics.Principal component analysis is used to build a correlation reference and to test the multivariate metrics.A large simulation study compares the novel Control approach with the current best practice.Improvements are obtained in comparison with the traditional Project Control approach.
Lauren Y H - One of the best experts on this subject based on the ideXlab platform.
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a bim based system for demolition and renovation waste estimation and planning
Waste Management, 2013Co-Authors: Jack Chin Pang Cheng, Lauren Y HAbstract:Due to the rising worldwide awareness of green environment, both government and contractors have to consider effective construction and demolition (C&D) waste management practices. The last two decades have witnessed the growing importance of demolition and renovation (D&R) works and the growing amount of D&R waste disposed to landfills every day, especially in developed cities like Hong Kong. Quantitative waste prediction is crucial for waste management. It can enable contractors to pinpoint critical waste generation processes and to plan waste Control strategies. In addition, waste estimation could also facilitate some government waste management policies, such as the waste disposal charging scheme in Hong Kong. Currently, tools that can accurately and conveniently estimate the amount of waste from construction, renovation, and demolition Projects are lacking. In the light of this research gap, this paper presents a building information modeling (BIM) based system that we have developed for estimation and planning of D&R waste. BIM allows multi-disciplinary information to be superimposed within one digital building model. Our system can extract material and volume information through the BIM model and integrate the information for detailed waste estimation and planning. Waste recycling and reuse are also considered in our system. Extracted material information can be provided to recyclers before demolition or renovation to make recycling stage more cooperative and more efficient. Pick-up truck requirements and waste disposal charging fee for different waste facilities will also be predicted through our system. The results could provide alerts to contractors ahead of time at Project planning stage. This paper also presents an example scenario with a 47-floor residential building in Hong Kong to demonstrate our D&R waste estimation and planning system. As the BIM technology has been increasingly adopted in the architectural, engineering and construction industry and digital building information models will likely to be available for most buildings (including historical buildings) in the future, our system can be used in various demolition and renovation Projects and be extended to facilitate Project Control.
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a bim based system for demolition and renovation waste estimation and planning
Waste Management, 2013Co-Authors: Jack Chin Pang Cheng, Lauren Y HAbstract:Due to the rising worldwide awareness of green environment, both government and contractors have to consider effective construction and demolition (C&D) waste management practices. The last two decades have witnessed the growing importance of demolition and renovation (D&R) works and the growing amount of D&R waste disposed to landfills every day, especially in developed cities like Hong Kong. Quantitative waste prediction is crucial for waste management. It can enable contractors to pinpoint critical waste generation processes and to plan waste Control strategies. In addition, waste estimation could also facilitate some government waste management policies, such as the waste disposal charging scheme in Hong Kong. Currently, tools that can accurately and conveniently estimate the amount of waste from construction, renovation, and demolition Projects are lacking. In the light of this research gap, this paper presents a building information modeling (BIM) based system that we have developed for estimation and planning of D&R waste. BIM allows multi-disciplinary information to be superimposed within one digital building model. Our system can extract material and volume information through the BIM model and integrate the information for detailed waste estimation and planning. Waste recycling and reuse are also considered in our system. Extracted material information can be provided to recyclers before demolition or renovation to make recycling stage more cooperative and more efficient. Pick-up truck requirements and waste disposal charging fee for different waste facilities will also be predicted through our system. The results could provide alerts to contractors ahead of time at Project planning stage. This paper also presents an example scenario with a 47-floor residential building in Hong Kong to demonstrate our D&R waste estimation and planning system. As the BIM technology has been increasingly adopted in the architectural, engineering and construction industry and digital building information models will likely to be available for most buildings (including historical buildings) in the future, our system can be used in various demolition and renovation Projects and be extended to facilitate Project Control.
Jack Chin Pang Cheng - One of the best experts on this subject based on the ideXlab platform.
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a bim based system for demolition and renovation waste estimation and planning
Waste Management, 2013Co-Authors: Jack Chin Pang Cheng, Lauren Y HAbstract:Due to the rising worldwide awareness of green environment, both government and contractors have to consider effective construction and demolition (C&D) waste management practices. The last two decades have witnessed the growing importance of demolition and renovation (D&R) works and the growing amount of D&R waste disposed to landfills every day, especially in developed cities like Hong Kong. Quantitative waste prediction is crucial for waste management. It can enable contractors to pinpoint critical waste generation processes and to plan waste Control strategies. In addition, waste estimation could also facilitate some government waste management policies, such as the waste disposal charging scheme in Hong Kong. Currently, tools that can accurately and conveniently estimate the amount of waste from construction, renovation, and demolition Projects are lacking. In the light of this research gap, this paper presents a building information modeling (BIM) based system that we have developed for estimation and planning of D&R waste. BIM allows multi-disciplinary information to be superimposed within one digital building model. Our system can extract material and volume information through the BIM model and integrate the information for detailed waste estimation and planning. Waste recycling and reuse are also considered in our system. Extracted material information can be provided to recyclers before demolition or renovation to make recycling stage more cooperative and more efficient. Pick-up truck requirements and waste disposal charging fee for different waste facilities will also be predicted through our system. The results could provide alerts to contractors ahead of time at Project planning stage. This paper also presents an example scenario with a 47-floor residential building in Hong Kong to demonstrate our D&R waste estimation and planning system. As the BIM technology has been increasingly adopted in the architectural, engineering and construction industry and digital building information models will likely to be available for most buildings (including historical buildings) in the future, our system can be used in various demolition and renovation Projects and be extended to facilitate Project Control.
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a bim based system for demolition and renovation waste estimation and planning
Waste Management, 2013Co-Authors: Jack Chin Pang Cheng, Lauren Y HAbstract:Due to the rising worldwide awareness of green environment, both government and contractors have to consider effective construction and demolition (C&D) waste management practices. The last two decades have witnessed the growing importance of demolition and renovation (D&R) works and the growing amount of D&R waste disposed to landfills every day, especially in developed cities like Hong Kong. Quantitative waste prediction is crucial for waste management. It can enable contractors to pinpoint critical waste generation processes and to plan waste Control strategies. In addition, waste estimation could also facilitate some government waste management policies, such as the waste disposal charging scheme in Hong Kong. Currently, tools that can accurately and conveniently estimate the amount of waste from construction, renovation, and demolition Projects are lacking. In the light of this research gap, this paper presents a building information modeling (BIM) based system that we have developed for estimation and planning of D&R waste. BIM allows multi-disciplinary information to be superimposed within one digital building model. Our system can extract material and volume information through the BIM model and integrate the information for detailed waste estimation and planning. Waste recycling and reuse are also considered in our system. Extracted material information can be provided to recyclers before demolition or renovation to make recycling stage more cooperative and more efficient. Pick-up truck requirements and waste disposal charging fee for different waste facilities will also be predicted through our system. The results could provide alerts to contractors ahead of time at Project planning stage. This paper also presents an example scenario with a 47-floor residential building in Hong Kong to demonstrate our D&R waste estimation and planning system. As the BIM technology has been increasingly adopted in the architectural, engineering and construction industry and digital building information models will likely to be available for most buildings (including historical buildings) in the future, our system can be used in various demolition and renovation Projects and be extended to facilitate Project Control.
Jens Heidrich - One of the best experts on this subject based on the ideXlab platform.
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implementing software Project Control centers an architectural view
arXiv: Software Engineering, 2014Co-Authors: Jens Heidrich, Jurgen MunchAbstract:Setting up effective and efficient mechanisms for Controlling software and system development Projects is still challenging in industrial practice. On the one hand, necessary prerequisites such as established development processes, understanding of cause-effect relationships on relevant indicators, and sufficient sustainability of measurement programs are often missing. On the other hand, there are more fundamental methodological deficits related to the Controlling process itself and to appropriate tool support. Additional activities that would guarantee the usefulness, completeness, and precision of the result- ing Controlling data are widely missing. This article presents a conceptual architecture for so-called Software Project Control Centers (SPCC) that addresses these challenges. The architecture includes mechanisms for getting sufficiently precise and complete data and supporting the information needs of different stakeholders. In addition, an implementation of this architecture, the so-called Specula Project Support Environment, is sketched, and results from evaluating this implementation in industrial settings are presented.
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software Project Control centers concepts and approaches
Journal of Systems and Software, 2004Co-Authors: Jurgen Munch, Jens HeidrichAbstract:On-line interpretation and visualization of Project data are gaining increasing importance on the long road towards predictable and Controllable software Project execution. In the context of software development, only few techniques exist for supporting these tasks. This is caused particularly by the often insufficient use of engineering principles in the software development domain. Beyond that, interpretation and visualization techniques from other domains (such as business or production processes) are not directly applicable to software processes because of the specific characteristics of software development. A software Project Control center (SPCC) is a means for collecting, interpreting, and visualizing measurement data in order to provide purpose- and role-oriented information to all involved parties (e.g., Project manager, quality assurer) during the execution of a Project. This article presents a reference model for concepts and definitions around SPCCs. Based on this reference model, a characterization and classification of essential approaches contributing to this field is given. Finally, an outline for future research is derived from identified deficiencies of existing approaches.
Jurgen Munch - One of the best experts on this subject based on the ideXlab platform.
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implementing software Project Control centers an architectural view
arXiv: Software Engineering, 2014Co-Authors: Jens Heidrich, Jurgen MunchAbstract:Setting up effective and efficient mechanisms for Controlling software and system development Projects is still challenging in industrial practice. On the one hand, necessary prerequisites such as established development processes, understanding of cause-effect relationships on relevant indicators, and sufficient sustainability of measurement programs are often missing. On the other hand, there are more fundamental methodological deficits related to the Controlling process itself and to appropriate tool support. Additional activities that would guarantee the usefulness, completeness, and precision of the result- ing Controlling data are widely missing. This article presents a conceptual architecture for so-called Software Project Control Centers (SPCC) that addresses these challenges. The architecture includes mechanisms for getting sufficiently precise and complete data and supporting the information needs of different stakeholders. In addition, an implementation of this architecture, the so-called Specula Project Support Environment, is sketched, and results from evaluating this implementation in industrial settings are presented.
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software Project Control centers concepts and approaches
Journal of Systems and Software, 2004Co-Authors: Jurgen Munch, Jens HeidrichAbstract:On-line interpretation and visualization of Project data are gaining increasing importance on the long road towards predictable and Controllable software Project execution. In the context of software development, only few techniques exist for supporting these tasks. This is caused particularly by the often insufficient use of engineering principles in the software development domain. Beyond that, interpretation and visualization techniques from other domains (such as business or production processes) are not directly applicable to software processes because of the specific characteristics of software development. A software Project Control center (SPCC) is a means for collecting, interpreting, and visualizing measurement data in order to provide purpose- and role-oriented information to all involved parties (e.g., Project manager, quality assurer) during the execution of a Project. This article presents a reference model for concepts and definitions around SPCCs. Based on this reference model, a characterization and classification of essential approaches contributing to this field is given. Finally, an outline for future research is derived from identified deficiencies of existing approaches.
