A novel model for production optimization with stochastic rework and failure-prone job shop schedule problem via hybrid simulation – heuristic optimization

Document Type : Research Note


1 Department of industrial engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran

2 Faculty of Entrepreneurship, University of Tehran, Tehran, Iran.


One way to increase productivity is to increase throughputs without using more resources. In this paper, the issue of the optimal sequence of products in a job shop scheduling is raised, which has many uncertainties such as downtime, development time, etc. One of the key factors which affect operation time is the number of reworks. The number of reworks based on metallurgical parameters, the number of their operations according to defects count, and process time are quite probable. The innovation is in dealing with job-shop scheduling in which there are reworks in particular, and the addition of this parameter increases the complexity of JSSP. Therefore, this parameter is added to the mathematical model and with a combined method via the statistical method. The problem has been solved with simulation for meeting uncertain constraints and a heuristics approach for optimization. Implementing this model in a high-tech casting shop with a large number of different products reduces the Work in Process (WIP) and capital sleep, which reduces the number of parts in the queues. Also, decreasing the queue length in bottleneck has reduced the lead time and increased agility and, above all, increased the number of productions by about 3.3 percent.