Identify and manage productivity risks in construction processes

In the construction industry, the project managers’ role is to complete the project on time, within budget, and meet the predetermined standard of quality. At site level, the project manager (PM) breakdowns the project into construction processes. Traditionally, PM selects the suitable method of procuring construction works based on his/her intuition and past experience. In fact, misjudgment of the strategy and technical uncertainty may lead to failure of the activity. Therefore, it is very important to anticipate risks and degree of uncertainty while deploying the suitable technique to carry out construction process. The purpose of this study is to develop a decision-making model based on fuzzy logic to evaluate the performance of construction processes. The model aims to predict the probability of cost of failure due the risk impact on construction processes performance. The model provides the project managers with control tools to implement, modify, or update construction techniques and methods effectively and efficiently. In addition, the model provides project managers with a planning tool that might help in identifying critical risks associated with the construction processes that might contribute to the failures of the process. The model has been tested statistically by comparing the actual probability of cost of failure to predicted probability. The model is considered to be practical and its accuracy and consistency has been approved