Cumulative effect of productivity rates in linear schedules

Rene Antonio Yamin, Purdue University

Abstract

Due to an increase in competition and project owners requirements, construction companies are becoming more sophisticated. In order to be more efficient and achieve competitive operational advantage, companies are narrowing their focus becoming specialists in certain type of construction projects. This specialization requires scheduling tools that can provide better insights and control on their chosen field and specific type of projects. Highway construction has always been a specialized area of construction in which, linear and continuous type of project are the norm. For these projects synchronization and continuity of work is crucial for efficient use of resources making advantageous to arrange for crews to work continuously. Doing so prevents idle intervals for equipment and manpower (Selinger 1980). For that purpose the project manager (PM) has to be able to identify the time and location when to add, maintain or remove resources in order to meet scheduled completion time. The only scheduling tool capable of reproducing such linear and continuous requirements is the Linear Schedule. Unfortunately, LS have not been developed enough to provide planners with the needed sophisticated analytical and statistical information. The LSMh (Harmelink 1995) is the most advanced LS method, since provides an analytical method to determine the controlling path for LS. However, the LSMh does not consider productivity rate uncertainty and its effects on project completion. The LSMh lacks statistical features that are needed to perform risk management and what-if analysis when using a LS. This research is a natural evolution of the LSMh, incorporating to it three important features. First, it provides three new graphical structures that allow the graphical calculation of the cumulative effects of productivity rate variability (CEPRV) in LS. Second, it proposes the Visual Linear Scheduling Model (VLSM). The VLSM allows planners to determine the existence of multiple controlling activity paths due to productivity uncertainty. Third, a simulation model is proposed that automates the calculation of both the CEPRV and VLSM, and in addition, provide planners with the possibility of calculating the probability of project delay (PPD).

Degree

Ph.D.

Advisors

Harmelink, Purdue University.

Subject Area

Civil engineering|Industrial engineering

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