Scheduling in robotic cells: Complexity and steady state analysis |
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| Institution: | 1. The Ohio State University, USA;2. Faculti ties Sciences Economiques et de Gestion de Sfax, Tunisia;3. University of Toronto, Canada;1. Department of Statistics, Feng Chia University, Taichung 40724, Taiwan;2. Business Administration Department, Fujen Catholic University, Hsinpei City, Taiwan;1. Department of Business Administration, Chungnam National University, 79 Daehangno, Yuseong-gu, Daejeon 305-704, Republic of Korea;2. Department of Business Administration, Daejeon University, 96-3 Yongun-dong, Dong-gu, Daejeon 300-716, Republic of Korea;1. College of Sciences, China University of Mining and Technology, Xuzhou, Jiangsu 221116, PR China;2. School of Mathematics and Statistics, Zhengzhou University, Zhengzhou, Henan 450001, PR China |
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| Abstract: | This paper considers the scheduling of operations in a manufacturing cell that repetitively produces a family of similar parts on several machines served by a robot. The decisions to be made include finding the robot move cycle and the part sequence that jointly minimize the production cycle time, or equivalently maximize the throughput rate. We focus on complexity issues and steady state performance. In a three machine cell producing multiple part-types, we prove that in two out of the six potentially optimal robot move cycles for producing one unit, the recognition version of the part sequencing problem is unary NP-complete. The other four cycles have earlier been shown to define efficiently solvable part 'sequencing problems. The general part sequencing problem not restricted to any robot move cycle in a three machine cell is shown to be unary NP-complete. Finally, we discuss the ways in which a robotic cell converges to a steady state. |
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