Modeling and Optimization of Cell Formation Problem Using Progressive Modeling and FactDesign
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Abstract
Cellular manufacturing is the most efficient manufacturing system design option in the mid-volume/mid-varietymanufacturing environments.Designing a cellular manufacturing system is a complex multi-level process consisting of four interdependent stages: 1) cell formation (CF), 2) inter and intra-cell layout design, 3) work scheduling and 4) resource allocation. In this thesis, our focus will be on cell formation stage, widely known in the literature as the Cell Formation Problem (CFP). In this study, a new comprehensive, user-friendly framework is proposed and developed to address a variety of problem formulations. A CFP could be simply modeled as a simple incidence matrix or as complex as data tables that can capture all the relevant data that may arise in a real-world system design setup. Several similarity indices have also beenimplemented to the data input/output logic to assist in solving both small- and large-scaleversions of the problem. The selected indices have been validated using several problems form the literature. A novel progressive algorithm is proposed to solve the simple case of the CFP using the novel representations of factory graphs. The efficiency and efficacy of the proposed algorithm have been demonstrated using several CFP problems in the literature.