TY - JOUR ID - 4047 TI - Part-level Sequence Dependent Setup Time Reduction in CMS JO - Journal of Industrial and Systems Engineering JA - JISE LA - en SN - 1735-8272 AU - Sharifi, Shahram AU - Chauhan, Stayaveer.S. AU - Bhuiyan, Nadia AD - Department of Mechanical and Industrial Engineering, Concordia University, Quebec, Canada AD - John Molson School of Business, Concordia University, Quebec, Canada Y1 - 2011 PY - 2011 VL - 5 IS - 3 SP - 142 EP - 153 KW - Sequence-dependent KW - Setup time KW - Part-level KW - Cellular manufacturing system(CMS) KW - Genetic algorithm DO - N2 - This paper presents the idea of creating cells while reducing part-level sequence-dependent setup time in general cellular manufacturing systems (CMS). Setup time reduction in CMS has gained modest attention in the literature. This could be attributed to the fact that the fundamental problem in cell formation in CMS has been mainly related to material handling and machine utilization while setup time was assumed to implicitly decrease as a result of grouping similar parts in a manufacturing cell. Despite more than three decades of CMS’s history, it has been relatively recent that setup time has been included in cell formation problems and found a place in the existing models. However, sequence-dependent setup time in the literature has been dealt with mostly within the context of scheduling “part-families” in a single manufacturing cell or in the allocation of parts to flow line cells. The present model includes the three fundamental elements of a cell formation procedure: machine utilization, intercellular movement and setup time. This therefore provides a basic structure that would serve as a general sub-model for real manufacturing cell formation problems including any type of setup time and manufacturing cell. Due to computation time and complexity of the problem, a solution approach based on theGenetic Algorithm based (GA-based)heuristic has been discussed and the solution of a sample problem has been compared with that of conventional optimization software. The results indicate a reasonably satisfactory performance by the GAbased heuristic in terms of accuracy and computation time. UR - https://www.jise.ir/article_4047.html L1 - https://www.jise.ir/article_4047_e1c72c4605bb3a47770de355b5a4e86b.pdf ER -