Impact Assessment of Construction Supply Chain Risk Changes on Project Time and Cost

Abstract

The supply chain plays a key role in the construction industry. The importance of the Construction Supply Chain (CSC) is not less than that of the onsite construction phases. There are many risk factors that influence the progress of a supply chain, and it is problematic when the probabilities and impacts of these risk factors are not well defined. While many approaches have been tried in studying SCs in construction, including risk effects, no study has addressed the dynamic updating of the probability of risk events throughout the construction life cycle to effectively study the impact on project time and cost. In order to reduce the impact of unseen risk factors that may affect the progress of any construction project, it is important to have tools to predict the influence of major risk factors in advance. However, risk factors keep changing in their probabilities and impacts along a project’s duration, and these changes will be more severe and have more influence if recognized later rather than earlier, and will be harder and more costly to manage. This research is aimed at helping to recognize the occurrence probabilities of risk factors during the early stages of a project and during the project execution. It aims to build a simulation model that can automatically detect risk factors in construction supply chain, track their changes, quantify their impact on project time and cost. The study starts by identifying typical risk issues related to a CSC that will influence its state. Then, a model for quantifying the amount of risk by defining the probabilities and impacts for each supply chain life cycle is proposed. The main focus of this research is to build models that automatically detect and adjust changes in probabilities for the most severe risk factors associated with CSCs and then estimate their impact on cost and schedule. Four major steps will be completed in the proposed research. First, a real-world industrial construction project is identified. Second, a detailed study on the risk factors associated with the supply chain of the given project is performed. Then, these risk factors are quantified according to the automated detection models for probability change and for studying the impact of each change. Finally, using a Monte Carlo Simulation tool (@Risk), the study will examine the impact of these risk factors on an industrial project to offer a methodology for generating automated reports for project managers to supply them with information on the impacts on the costs and schedules for their projects. The model offer stakeholders involved in a project with a better understanding of the changes in the risk so that throughout the project execution phase, they can take corrective actions and tap off the negative impact of risk on project time and cost. This system can be used for supply chain planning and operation. The power of the system is its ability to respond to various what-if scenarios. The newly introduced model is validated using a real-world industrial project and the details of the project are documented.