Part-machine grouping using weighted similarity coefficients

The first step in the transition to cellular manufacturing is part-machine grouping. In this paper, grouping parts into families and machines into cells is done in two phases: by first grouping machines and then assigning parts. Limits both on the number of machines per cell and on the number of parts per family are considered. The number of cells is not fixed. A weighted sum of within-cell voids and out-of-cell operations is used to evaluate the part-machine grouping obtained. In Phase One, weighted similarity coefficients are computed and machines are clustered using a Tabu search algorithm. In Phase Two, part types are assigned to the previously formed groups using a linear minimum cost network flow model. The proposed approach is compared with three heuristics, namely ZODIAC, GRAFICS and MST, on a large number of problems.