To characterize the process of lead-time reduction in EPC project-based organizations, including the engineering, procurement, and construction activities, various elements such as organizational issues, firm resources, used methods and techniques, and performance measuring tools are important. In this study, the four mentioned elements are evaluated through a survey in different EPC project-based organizations. The survey is sent to only experts and managers who are involved in EPC projects, and the obtained data is used to test the relationship between the mentioned variables and the lead time of developing new products. This evaluation is followed by a set of generalized lessons learned and courses of action to improve the development process. Additionally, the attributes of performance measurement in such projects are scrutinized. Therefore, to analyze the impacts of the mentioned variables and their variations on the performance measurement, a mathematical model based on the fuzzy approach is developed. The results show that all of the four considered variables are correlated to the lead time and affect the quality perceived by the main client and the cost of the project. Moreover, data obtained from the proposed mathematical formulations illustrated that the fuzzy modeling approach is an effective method to predict the performance measurement level when the levels of the input variables are given.

Flexible robotic cells are used to produce standardized items at a high production speed. In this study, the scheduling problem of a flexible robotic cell is considered. Machines are identical and parallel. In the cell, there is an input and an output buffer, wherein the unprocessed and the finished items are kept, respectively. There is a robot performing the loading/unloading operations of the machines and transporting the items. The system repeats a cycle in its long run. It is assumed that each machine processes one part in each cycle. The cycle time depends on the order of the actions. Therefore, determining the order of the actions to minimize the cycle time is an optimization problem. A new mathematical model is presented to solve the problem, and as an alternative, a simulated annealing algorithm is developed for large-size problems. In the simulated annealing algorithm, the objective function value of a given solution is computed by solving a linear programming model which is the first case in the literature to the best of our knowledge. Several numerical examples are solved using the proposed methods, and their performances are evaluated.