Uncertainty Analysis of Key Schedule Performance Indicators in Design, Procurement, and Construction Phases of Heavy Industrial Projects

Abstract

Construction is a dynamic industry due to the existence of uncertainties surrounding evolving technologies, budgets, resources, and the development process. Because construction environments are relatively complicated, project managers may face significant challenges in delivering timely and effective project outcomes. Delays may occur throughout the design, procurement, and construction (DPC) phases of all construction projects, including those involving heavy industry; however, indicators of schedule delays can be identified early in a project’s life cycle, and appropriate strategies can be applied. This purpose of this study was to identify indicators that lead to the poor schedule performance of a project during the DPC phases and to examine the robustness of each schedule performance indicator. To accomplish this objective, a survey questionnaire was designed and sent to a diverse group of experienced construction professionals. Statistical methods, such as the chi-squared test, the two-sample t-test, and the Kruskal-Wallis test, were employed to evaluate and screen the DPC schedule performance indicators of heavy industrial projects, and a list of schedule delay indicators was developed using the all-possible combination regression analysis approach. The extreme bound analysis (EBA) technique was used to determine the robustness of each indicator’s relationship to the model. The results revealed nine robust schedule performance indicators in each of the DPC phases. The findings of this study can be used by the decision makers in construction projects to emphasize more reliable factors and minimize the number of revisions required during a project’s execution.