Inter-cell and intra-cell facility layout models under different demand environments in cellular manufacturing systems

Facility layout aims to arrange the facilities, including aisles, machines, instruments and tools in the shop floor to provide an efficient layout. Efficiency of layout has tremendous effects on the performance of the system. Cellular Manufacturing System (CMS), as a promising manufacturing system has emerged to manufacture mid-variety, mid-volume products. In a CMS parts based on their similarities are classified into some groups named part families, and different machines are dedicated to produce these parts. The aim of implementation of a CMS is to take advantages of the similarities in the design and manufacturing of products. In the design of cellular manufacturing systems, two important decisions should be made; Cell Formation (CF), and Facility Layout (FL). Cell formation aims to group part families and dedicate each part family to one or more machine cells. The literature in the CF is extensive and abundant but layout models have not absorbed the attention of researchers as much as cell formation. Hence, in the first part of the study, a facility layout model in a CMS is developed that considers unknown locations for machine cells. The model minimizes both inter-cell and intra-cell material handling cost. To solve the model, an algorithm based on Simulated Annealing (SA) is developed in C/C++ namely SA1. Comparison of the results with an adapted algorithm from the literature, in terms of the quality of solutions (material handling cost) shows that the proposed algorithm produces better solutions with a maximum of 0.08% error compared to 0.12% error in the benchmarked algorithm. Moreover, the computation time (CPU Time) of the developed SA algorithm is significantly less than the benchmarked algorithm. In the worst case, the proposed algorithm finds good solutions about 50 times faster than the benchmarked. Cellular manufacturing system is an important technique in the planning and control of manufacturing systems. There are a lot of success stories about its implementation but rapid changes in manufacturing systems may cause a CMS not to perform well in every case. Therefore, it is quite important to investigate the effects of uncertainty of demand of products on the layout of facilities in a cellular manufacturing system. For this purpose, two mathematical models for layout in a CMS are proposed, which considers the stochastic nature of demand. One of the models considers a Normal distribution function for demand, and another one, a Uniform distribution function. In order to validate the models several cases are generated and demonstrated by two methods, Lingo 12.0 optimization software and an enumeration algorithm which is developed in C/C++. The results show that uncertainty in the demand of products can lead to changes in the arrangement of facilities. In a volatile manufacturing system, implementation of a CMS might not be applicable. In such a situation, the use of a Hybrid Cellular Manufacturing (HCM) seems to be more reasonable. Hence, in another part of this study, a model for layout of facilities in a HCM is developed that considers demand of products varies in the planning horizon. To solve the mathematical model, the SA1 is improved, and called SA2. Comparison of the results shows that the SA2 produces better solution quality in terms of the material handling cost with a maximum of 0.06% error compared to 0.08% error in the SA1. In addition, the computation time (CPU Time) of the SA2 is nearly half of the SA1.

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