Title: Cell loading and manpower allocation with fuzzy multiple objectives in synchronised manufacturing cells

Authors: Dyah A. Hening; Can Celikbilek; Gürsel A. Süer

Addresses: Industrial and Systems Engineering Department, Russ College of Engineering and Technology, Ohio University, Athens, OH, 45701, USA ' Industrial and Systems Engineering Department, Russ College of Engineering and Technology, Ohio University, Athens, OH, 45701, USA ' Industrial and Systems Engineering Department, Russ College of Engineering and Technology, Ohio University, Athens, OH, 45701, USA

Abstract: This paper seeks to determine the feasibility of using fuzzy concepts in cell loading and manpower allocation to solve multiple objectives scheduling problems in a cellular manufacturing environment. Various manpower allocation levels were considered and then products were assigned to the cells and followed up by product sequencing and manpower allocation decisions in each cell by considering the fuzzy concept. The number of operators needed in a time bucket may be different based on the manpower requirement for each process. Fuzzy mathematical model for cell loading and cell sequencing were developed in multiple cells with multiple objectives. The objectives were to minimise the total manpower shortages simultaneously with the minimum number of time buckets with manpower allocation shortage. Then, additional manpower as floaters were considered to reduce the total number of manpower shortages. The results revealed that multiple objectives with fuzzy functions balanced the manpower allocation and minimised the total shortage.

Keywords: cellular manufacturing; fuzzy modelling; manpower allocation; cell loading; multi-objective scheduling; synchronisation; fuzzy logic; synchronised manufacturing cells; mathematical modelling; cell sequencing; manpower shortages.

DOI: 10.1504/AJMSA.2016.080469

Asian Journal of Management Science and Applications, 2016 Vol.2 No.3, pp.245 - 272

Received: 17 Sep 2014
Accepted: 12 Oct 2015
Published online: 25 Nov 2016 *

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