HYBRID PARTICLE SWARM ALGORITHM FOR SCHEDULING IN CELLULAR MANUFACTURING SYSTEM- A CASE STUDY

  • Muhammad Abas Department of Mechanical Engineering, Sarhad University of Science and Information Technology, Peshawar
Keywords: Cellular Manufacturing, Work in process, Machine utilization, Particle swarm optimization, Hybrid algorithm

Abstract

Cellular Manufacturing System (CMS) lies in the heart of lean manufacturing with goal of producing the wide variety of products as efficiently as possible. Increase in customer demand for more customized products had forced industries to shift to CMS. Once CMS has been established scheduling becomes one of the challenging task. So, in present work, a real case study based on scheduling problem in CMS is presented and a hybrid particle swarm optimization (PSO) algorithm is proposed to achieve an optimize sequence. The PSO is integrated with NEH algorithm to achieve an optimal sequence faster. A mathematical model is presented to evaluate two conflicting performance measures; minimization of work in process (WIP) and maximization of average machine cell utilization. Implementation of proposed algorithm had increased the utilization from 65% to 82 % while minimized the WIP to 6 parts from 25parts.

Author Biography

Muhammad Abas, Department of Mechanical Engineering, Sarhad University of Science and Information Technology, Peshawar

Department of Mechanical Engineering Lecturer

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Published
2019-06-28
How to Cite
Abas, M. (2019, June 28). HYBRID PARTICLE SWARM ALGORITHM FOR SCHEDULING IN CELLULAR MANUFACTURING SYSTEM- A CASE STUDY. JOURNAL OF ENGINEERING AND APPLIED SCIENCES, 38(1). https://doi.org/https://doi.org/10.25211/jeas.v38i1.2009