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Development and selection of hybrid dispatching rule for dynamic job shop scheduling using multi-criteria decision making analysis (MCDMA)

Publication Type : Journal Article

Publisher : International Journal for Quality Research,

Source : International Journal for Quality Research, Volume 14, Issue 2, p.487-504. (2020)

Url : http://oaji.net/articles/2020/452-1588696927.pdf

Keywords : ARENA, Discrete Event Simulation (DES), Job shop, MCDMA, Priority Dispatching Rule (PDR), Topsis

Campus : Coimbatore

School : School of Engineering

Department : Mechanical Engineering

Year : 2020

Abstract : A suitable sequencing and dispatching of jobs on machines is very much essential to improve the performance of any industry. Sequencing is the prioritizing of a set of jobs in a queue based on some decision rule to determine the order in which they will be processed. This paper aims at detailed study and analysis of hybrid rule selection to reduce lead time, waiting time and to increase machine utilization and throughput. In this study four static and eight hybrid dynamic rules were considered and prioritization of jobs is done using TOPSIS algorithm. The hybrid rules are obtained by combining certain dynamic rules. The data includes 47 jobs and 17 machines with different monthly order quantities. Discrete event simulation tool is used for the study and validation of actual data of a manufacturing plant. The results shows that the proposed hybrid dispatching rule, which is a combination of Earliest Creation time (ECT), Shortest waiting time (SWT) and Most work remaining time (MWRT) are very effective in minimizing lead time and maximizing throughput. The another hybrid dispatching rule, which is a combination of Longest Waiting Time (LWT), ECT and MWRT are effective in maximizing the machine utilization.

Cite this Research Publication : M. Thennarasu, K. Ramesh Kumar, Dr. Anbuudayasankar S. P., Arjunbarath, G., and P. Ashok, “Development and selection of hybrid dispatching rule for dynamic job shop scheduling using multi-criteria decision making analysis (MCDMA)”, International Journal for Quality Research, vol. 14, no. 2, pp. 487-504., 2020.

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