PSO based fuzzy interval type-2 c-means cell formation in cellular manufacturing

Cell formation is an essential stage in group technology system implementation leads to productivity promotion in a flexible manufacturing system. Fuzzy logic and its instruments facilitate ambiguous and uncertainty information handling which is hidden in manufacturing systems. This paper presents two novel methods to form cells in group technology systems based on interval type-2 fuzzy sets. Interval type-2 fuzzy c-means algorithm and hybrid fuzzy c-means clustering method with particle swarm optimization technique are two methods that are applicable for interval type-2 fuzzy sets. The main objective of the proposed models is optimal cell formation while five basic attributes in cell formation problem are considered as machines required for each part, part types demand, processing time, manufacturing cost and movement cost. A quantifying similarity measure based on Euclidean distances measurement between indices implemented for cell formation. Validation measurement took place by Modified Xie-Beni index. According to real experiment the results show that the hybrid PSO- FCM is superior and efficient method for cell formation problem while cover shortcoming of IT2FCM and traditional FCM methods.

کلیدواژه ها:

Group technology ، manufacturing cell formation ، Particle Swarm Optimization ، Interval type-2 fuzzy set ، Fuzzy C-means clustering ، Validity index