Integrated use of fuzzy c-means and fuzzy INN for GT part family and machine cell formation

摘要

This paper presents new approach for GT part family and machine cell forma- tion. It involves the integrated use of two fuzzy clustering algorithms: c- means and fuzzy k-nearest neighbours. It is shown that the proposed approach performs better than using fuzzy c-means alone or FACT (Kamal and Burke) in terms of some commonly used measures such as grouping efficacy, grouping index, number of voids, number of exceptional elements, and number of bottle- neck machines.