Comparison of layered cellular manufacturing system design approaches

In this study, a mathematical programming approach is proposed to design a layered cellular manufacturing system in highly fluctuated demand environment. A mathematical model is developed to create dedicated, shared and remainder cells with the objective of minimizing the number of cells. In contrast with classical cellular manufacturing systems, in layered cellular systems, some cells can serve to multiple part families. A five-step hierarchical methodology is employed: (1) formation of part families, (2) calculation of expected cell utilizations and demand coverage probabilities, (3) specification cell types as dedicated, shared, and remainder cells, (4) simulation of proposed layered systems to evaluate their performance with respect to average flowtime and work-in-process inventory, and (5) statistical analysis to find the best layered cellular design among alternatives. It is found that designs with higher number of part families tend to have less number of machines. Similar results are also observed with respect to average flowtime and work-in-process inventory measures. The results are also compared with a heuristic approach from the literature. None of the approaches is dominant with respect to all of the performance measures. Mathematical modeling approach performs better in terms of number of machines for most of the alternative designs. However, heuristic approach yields better average flowtime and work-in-process inventory for most of the designs.