Enhancing Project Schedule Monitoring: Application of CUSUM and EWMA Memory Control Charts in Earned Schedule Method
نویسندگان
1 Associate Professor, Department of Industrial Engineering, Arak University, Arak, Iran.
2 Assistant Professor, Department of Industrial Engineering, Central Tehran Branch, Islamic Azad University, Tehran, Iran.
3 Ph.D. Candidate, Department of Industrial Engineering, Iran University of Science & Technology, Tehran, Iran.
4 Assistant Professor, Department of Industrial Engineering, Qom University of Technology, Qom, Iran.
5 M.Sc., School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran.
doi
10.22059/aie.2025.389599.1937چکیده
Earned Value Management ( ) and Earned Schedule ( ) are crucial tools for controlling projects and preventing deviations from schedule and budget objectives. In early-return projects, meeting deadlines is critical; however, Earned Value alone may not provide an appropriate criterion for evaluating and analyzing time-related indicators. This study proposes a method to use statistical control charts that consider indicator deviations from the project's start (memory charts) and are more sensitive to schedule deviations. Specifically, Exponentially Weighted Moving Average (EWMA) and Cumulative Sum (CUSUM) charts are employed to monitor the Schedule Performance Index ( ) based on the system. Instead of Expected Value ( ), is used for monitoring. Results demonstrate that both CUSUM and EWMA charts offer higher accuracy compared to classical Shewhart charts and produce fewer error alarms. The CUSUM chart shows less error (75% reduction in initial error alarms), while EWMA displays higher sensitivity (20% faster deviation detection). This proposed method can assist project managers in identifying schedule deviations more accurately and rapidly. The study utilized data from a 30-month construction project, applying normality tests and data transformation techniques to ensure statistical validity. The findings suggest that memory control charts based on provide a more reliable and responsive approach to project schedule monitoring, particularly in time-sensitive projects.
