الفهرس 
English summaryOnly 14 pages are availabe for public view
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Abstract
The construction project is one of the most dynamic, risky, challenging and rewarding field. Due to highly dynamic of construction project; decisions must be taken quickly based on available data. Performance management of construction projects is one of the most challenging and critical tasks carried out by construction team. The successful delivery of construction projects requires management of all project aspects. The main objective of this research is to develop an approach for evaluation a performance of infrastructure projects. This research focus on the construction phase of a project and intended for implementation by contractors. As it is common on project management context, Earned Value Management (EVM) usually integrates time and cost performance within the project scope. It helps the project manager to understand how to deal with project from two points of view; the first is to recognize current performance indexes and second is to provide a forecast to the future. Statistical Process Control (SPC) is an approach that uses statistical techniques to monitor the process. The widely used types of control charts are individual and Moving Range (MR). In traditional control charts, center line, upper control limit and lower control limit are represented by numeric value. For many problems, control limits could not be so precise. This research procedure and methodology utilized a modified Shewhart control chart used in manufacturing process since the 1920s combined with fuzzy theory to create a fuzzy control charts approach associated with α-cut in order to control earned value performance indexes including linguistic terms. Numeric control limits can be transformed to fuzzy control limits by using membership function. Quantitative variables that are indicators of project performance were plotted versus time periods. Therefore, the proposed methodology can be applied to track, monitor, and control construction projects, to integrate cost and schedule functions. The model can be applied to any project elements level (e.g. resources levels, activities levels, units levels and/or for the whole project). “Minitab” program was used to analyze the data to present statistical measures. At the end, it was concluded that the proposed approach improves substantially the project scheme and enhances the capability of earned value technique.