Singularity Functions to Enhance Monitoring in the Last Planner System

Abstract

Many traditionally managed construction projects suffer from schedule delays. However, in Lean Construction, the Last Planner System TM (LPS) stipulates planning tasks first at the macro (Master Schedule and Phase Schedule) and then at the micro levels (Look-ahead Planning and Weekly Work Plan, WWP) when the week of execution approaches. This paper aims to enhance the control aspect of LPS before the end of the execution in order to finish on schedule. Its objective is to improve the WWP by monitoring project progress on a daily basis to have enough time for corrective measures, catch up to the planned schedule, and minimize wastes in time and resources. The approach allows project participants to compare planned to actual progress, calculate required improvement if needed, and be alerted if cascading delays may occur. It calculates the Process Reliability Index (PRI) to check whether extra allocation of labor is needed to finish the required work, checks for congestion in work areas, and predicts the possible Percent Plan Complete (PPC) before the end of the execution week. Moreover, this paper proposes a new metric that shows the reliability of the team in applying the recommended improvements. This metric allows more realistic improvement plans compared to prior attempts. The monitoring approach can be applied to linear, repetitive, and location-based projects. Singularity functions are used as the core model because they are suitable for such schedules. They can be implemented in various computer applications. An example is used to evaluate the approach and finds it to be reliable.