An Integrated Approach for Fuzzy Set Based Part-Machine Cell Formation

The nature of cell formation is imprecise and uncertain which is fuzzy rather than crisp and/or random. The binary part–machine incidence matrix fails in reflecting the real world conditions such as design features, part demands, machine capacities and routing data. Using the non-binary part- machine incidence matrix, the relationships between parts and machines can be represented by fuzzy membership values based on the alternative process plans and machine capacity limitations. This paper presents an integrated approach for fuzzy set based part– machine cell formation. The proposed approach em ploys a fuzzy binary integer model and is capable of determining process plans of parts and fuzzy membership values in the non-binary incidence matrix considering part demands and machine capacities. The proposed approach is illustrated and tested on a numerical example. Results show that the proposed approach is valid and capable of reflecting real world conditions.