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.
The construction industry suffers from chronic problems in project delays, crew ineffectiveness, and productivity loss. One of the root causes of such problems is improper planning and control. Project control requires not only sufficient experience, but also proactive decision-making and awareness. In order to ensure proactivity and problem awareness, simulation coupled with Lean Construction principles are used to inform the analysis of workers' performance and conditions on site, facilitate production control, and detect possible future shortcomings or delays. This paper presents an Agent-Based and Discrete-Event model that allows project controllers to simulate current or future project states within the Weekly Work Plan (WWP) of the Last Planner® System (LPS) in order to orient the project activities and performance as desired. This model can be used to help generate more realistic planned production rates considering LPS metrics for crew capacity and performance. Factors resulting in the non-completion of tasks are taken from data of a real project over the course of 94 weeks. The simulation model is applied to an example project to explain the goals behind the proposed model. Results indicate that the proposed model is useful as a basis for a decision support system for project planners to evaluate the reliability of their planned production rates.
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