TY - GEN
T1 - A cell formation algorithm incorporating multiple practical production factors
AU - Liu, Chen Guang
AU - Tanaka, Kazuyuki
AU - Yin, Yong
PY - 2008
Y1 - 2008
N2 - Numerous cell formation methods were designed to minimize the cost of the material flows between cells. However, most of them do not simultaneously take various production factors under consideration. In this paper, multiple key real-life production factors, namely production volume, batch size, alternative process routing and perfect coefficient of each routing, cell size, unit cost of intercell/intracell movement, and path coefficient of material flows are considered. Since the considering problem is NP-complete, a three-stage heuristic algorithm is developed to obtain the approximate solutions. The proposed algorithm comprise three stages: I) initially group the machines according to the alternative process routings of each part. 2) select the appropriate process routing of each part with respect to the over-all material movement cost, and 3) regularly form cells based on the chosen appropriate process routing. A simple numerical example and an industrial case are used to test the computational performance of the proposed algorithm. The test results imply that it is useful in generating cell configurations in both quality and speed.
AB - Numerous cell formation methods were designed to minimize the cost of the material flows between cells. However, most of them do not simultaneously take various production factors under consideration. In this paper, multiple key real-life production factors, namely production volume, batch size, alternative process routing and perfect coefficient of each routing, cell size, unit cost of intercell/intracell movement, and path coefficient of material flows are considered. Since the considering problem is NP-complete, a three-stage heuristic algorithm is developed to obtain the approximate solutions. The proposed algorithm comprise three stages: I) initially group the machines according to the alternative process routings of each part. 2) select the appropriate process routing of each part with respect to the over-all material movement cost, and 3) regularly form cells based on the chosen appropriate process routing. A simple numerical example and an industrial case are used to test the computational performance of the proposed algorithm. The test results imply that it is useful in generating cell configurations in both quality and speed.
UR - http://www.scopus.com/inward/record.url?scp=55849121924&partnerID=8YFLogxK
U2 - 10.1109/CSEW.2008.39
DO - 10.1109/CSEW.2008.39
M3 - 会议稿件
AN - SCOPUS:55849121924
SN - 9780769532578
T3 - Proceedings of the 11th IEEE International Conference on Computational Science and Engineering, CSE Workshops 2008
SP - 170
EP - 175
BT - Proceedings of the 11th IEEE International Conference on Computational Science and Engineering, CSE Workshops 2008
T2 - 11th IEEE International Conference on Computational Science and Engineering, CSE Workshops 2008
Y2 - 16 July 2008 through 18 July 2008
ER -