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Volume 25, Issue 2, 2024


Muayad wali lafta Al Sudani, Sepanta Naimi

> DOI: https://jeeng.net/issue/view/?id=103

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Statistical Control Charts, Project Performance Evaluation, cost performance index



Within the project period, project managers monitor and regulate the various expenses related with project duties. The traditional variances are computed by comparing the actual performance measures gathered during the execution phase to the baseline metrics chosen during the planning phase. These variances are taken into account throughout the control procedures in order to establish their relevance. In real-world projects, the question is whether traditional methodologies can provide a meaningful indicator for project control. The present paper used the exponentially weighted moving average (EWMA) control chart in conjunction with the support vector machine (SVM) to propose an excellent tool for construction project monitoring. The EWMA advances SPC schemes are used to study the chart's upper and lower control limits and to use cost performance index (CPI) data to determine out of control spots. The SVM findings then demonstrated a good indicator for predicting the overall egression of the project based on different time periods. The numerical results show that using the control chart method in conjunction with SVM to analyze the actual values of CPI indices improves project management teams' capacity to recognize cost problems on time.