Future paths for integer programming and links to artificial intelligence
Computers and Operations Research - Special issue: Applications of integer programming
Single linkage versus average linkage clustering in machine cells formation applications
Computers and Industrial Engineering
Cell formation in group technology: review, evaluation and directions for future research
Computers and Industrial Engineering - Cellular manufacturing systems: design, analysis and implementation
Integer Programming Formulation of Traveling Salesman Problems
Journal of the ACM (JACM)
A systematic approach for product families formation in Reconfigurable Manufacturing Systems
Robotics and Computer-Integrated Manufacturing
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A reconfigurable cellular manufacturing system (RCMS) consists of multiple reconfigurable machining cells, each of which has one or more reconfigurable machine tools (RMTs), a setup station, and an automatic material handling and storage system. As part of the RCMS design process, similar parts must be grouped into part families and the RMTs must be arranged to form parallel cell configurations. A RCMS is designed at the outset for rapid changes in its components, allowing the production of multiple part families in each parallel cell. This paper proposes a new approach to simultaneously solve the cell formation and the scheduling of part families for an effective working of a RCMS. A new mixed integer linear programming model is used to represent both problems at the same time with the objective of minimizing production costs. Two types of production costs are considered: reconfiguration (i.e. setup) costs for changing from one family to the next one, and under-utilization costs for not using the RMT resources. A small size example is used to illustrate this integrated methodology. Computational experiments have been carried out adapting some larger instances from the literature on cellular manufacturing systems. Solving large instances optimally becomes prohibitive in terms of computational effort. That is why an approximate method, based on a Tabu search (TS) algorithm, has also been developed. Results show the ability of this algorithm to find good-quality production schedules of part families in a RCMS without requiring long computing times. It can be concluded that a RCMS can attain manufacturing flexibility without losing cost-effectiveness and that the approach proposed in this paper can efficiently solve real-world problems.