Testing the Application of the Reliable Commitment Model in a Pipeline Construction Project

Abstract

Planning reliability has been highlighted when construction project performance standards deteriorate. Gonzalez et al (2008) established a relationship between planning reliability and project performance, stating an improvement in one would promote the other. However, this can also mean that deterioration in one can have direct ramifications on the other. Even at the operational level of a project, McGray et al (2002) states that the use of intuition and experience by planning personnel to make decisions is a prevalent pattern and adversely affects not only this level but other hierarchical tiers within the project. The Reliable Commitment Model (RCM) was developed by Gonzalez et al (2009) for use at the operational level of projects. RCM provides a flexible short-term planning tool through the use of statistical multivariable linear regression (MLR) techniques to plan resources based on the periodic historical production information measured on-site. The RCM was developed and validated on repetitive projects of the building construction scope, and its possible application on repetitive projects of a different scope (pipeline construction) was proposed and trialled in this research report. Thus, the main objectives of this research report were to test the applicability of the RCM in a project outside those areas of construction to which it had historically been applied, and as such observations and measurements of a pipeline expansion project called the South Western Interceptor were conducted. This project was undertaken by Fletcher Construction Company in conjunction with two of its secondary companies, Brian Perry Civil and PipeWorks implementing open-trenching and tunnelling (trenchless) works respectively, to install an expanded capacity pipeline to the existing service. Over a total period of approximately sixteen weeks, data was collected from two separate sections (units of analysis) of the case study project and the RCM was applied through MLR analysis to explore its applicability. The aims of the research were achieved with the results illustrating the RCM's ability to predict progress within a defined range of accuracy using on-site information, and its use within this scope of construction project made possible. The results provide promise for further application and implementation in projects of this nature.