An Efficient Approach for Bottleneck Resource(s) Detection Problem in the Multi-objective Dynamic Job Shop Environments

Nowadays energy saving is one of the crucial aspects in decisions. One of the approaches in this case is efficient use of resources in the industrial systems. Studies in real manufacturing systems indicating that one or more machines may also act as the Bottleneck Resource/ Resources (BR). On the other hand, according to the Theory of Constraints (TOC), the efficient use of resources in manufacturing systems is limited by the capacity of the BR(s). Hence, in order to improve the performance of such systems, the BR(s) should be identified and assessed and improved using capacity of such resources to the greatest extent possible. Studies indicating that Bottleneck Resource Detection (BRD) problem in the ―Multi-Objective and the Dynamic conditions‖ of job-shop is an important issue which has not been studied so far due to its computational complexity. Hence, the development of an efficient approach to identify and assess BRs in Multi-objective Dynamic Job Shop (MODJS) has been considered as the subject of this paper. In this article, a BRD method based on the Taguchi method for MODJS (TM-MODJS) has been developed. This method takes the objectives of the MODJS as estimated indices and carries out typical and finite number of experiments by combining different suitable dispatching rules to detect BR(s) which have the greatest effect on the estimated index. Comparing the results indicates effectiveness of the developed method especially in scheduling which results in a reasonable time.