Improved similarity coefficient and clustering algorithm for cell formation in cellular manufacturing systems

Abstract

Cell formation plays an important role in the design of cellular manufacturing systems. Among many methods utilized to solve the cell formation problem, the similarity coefficient method is the most widely used owing to its high flexibility and low computational requirement. However, generalized similarity coefficients ignore material flow, which is closely related to operation sequence and repeated operations. Moreover, most similarity coefficient-based clustering algorithms focus on the number of inter-cell movements but disregard distinction of the movement effort. To overcome these limitations, this study improves the generalized similarity coefficient method to form part families. In addition, a new clustering algorithm is presented to assign machines to cells with minimum intensity of material inter-cell movement, which depends on the frequency, production volume and difficulty level of inter-cell movement. Experimental results demonstrate that the proposed method has superior sensitivity and effectiveness for solving the cell formation problem.

KEYWORDS:

• Cell formation
• similarity coefficient method
• clustering algorithm
• inter-cell movement
• cellular manufacturing system

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This research was supported in part by grants from the Natural Science Foundation of China [grant numbers 71702111, 71971143, 71571120 and 61772344] and the Natural Science Foundation of Guangdong Province [grant number 2018A030310567].