Reliability optimization of tools with increasing failure rates in a flexiblemanufacturing system

摘要

Tool reliability is one of the most important issues in a flexible manufacturing system. If a tool fails to operate correctly, the performance of the manufacturing system is reduced, the due date may be violated, or the product quality falls behind the standards. This paper develops a bi-objective mathematical model for tool selection in a flexible manufacturing system in order to optimize both reliability and cost. The tools in these environments are considered to have increasing failure rates as they are used over time; a case closer to reality. This paper aims to evaluate the availability of different tools used in a production system, in which the reliability of a tool is dependent on the failure occurring to any other compatible tool. Two multi-objective genetic algorithms along with the -constraint method are proposed to solve the problem. The Taguchi method is also employed to calibrate the parameters of the proposed algorithms and to enhance their performances. Finally, a hybrid AHP-TOPSIS is utilized to prioritize the solution algorithms. The results indicate that while the -constraint is the best to solve small-size problems, the non-dominated rank genetic algorithm performs the best in solving large-size problems.