Summary: This paper deals with the cellular manufacturing system (CMS) that is based on group technology (GT) concepts. CMS is defined as identifying the similar parts that are processed on the same machines and then grouping them as a cell. The most proposed models for solving CMS problems are focused on cell formation and intracellular machine layout problem while cell layout is considered in few papers. In this paper we apply the multiple attribute decision making (MADM) concept and propose a two-stage method that leads to determine cell formation, intracellular machine layout and cell layout as three basic steps in the design of CMS. In this method, an initial solution is obtained from technique for order preference by similarity to the ideal solution (TOPSIS) and then this solution is improved. The results of the proposed method are compared with well-known approaches that are introduced in literature. These comparisons show that the proposed method offers good solutions for the CMS problem. The computational results are also reported.
Scope and purpose
In the previous array-based clustering methods, arrays are defined by binary numbers that are indicated as the set of machines that process each part. The main problem of these methods is that grouping parts and machines are made regardless of production volume, operational sequences, production cost, inventory and other production system’s limitations.
In this paper we consider the previous common problems of array-based clustering methods and apply the logical idea of TOPSIS method for solving the cellular manufacturing system problem in which arrays in the part-machine incidence matrix are defined by operational sequences. The TOPSIS is a multiple attribute decision making (MADM) technique in which the alternatives are ranked by their distances between positive and negative ideal solution.