Browsing by Author "Chung, I-Ping"

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An enhanced model for the integrated production and transportation problem in a multiple vehicles environment
(2016-04)
Kang, He-Yau
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Pearn, W. L.
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Chung, I-Ping
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Lee, Amy H. I.
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工業工程與管理學系
Solving an integrated production and transportation problem (IPTP) is a very challenging task in semiconductor manufacturing with turnkey service. A wafer fabricator needs to coordinate with outsourcing factories in the processes including circuit probing testing, integrated circuit assembly, and final testing for buyers. The jobs are clustered by their product types, and they must be processed by groups of outsourcing factories in various stages in the manufacturing process. Furthermore, the job production cost depends on various product types and different outsourcing factories. Since the IPTP involves constraints on job clusters, job-cluster dependent production cost, factory setup cost, process capabilities, and transportation cost with multiple vehicles, it is very difficult to solve when the problem size becomes large. Therefore, heuristic tools may be necessary to solve the problem. In this paper, we first formulate the IPTP as a mixed integer linear programming problem to minimize the total production and transportation cost. An efficient genetic algorithm (GA) is proposed next to tackle the problem when it becomes too complicated. The objectives are to minimize total costs, where the costs include production cost and transportation cost, under the environment with backup capacities and multiple vehicles, and to determine an appropriate production and distribution plan. The results demonstrate that the proposed GA model is an effective and accurate tool.
Collaborative production-distribution planning for semiconductor production turnkey service
(2007)
Chung, Shu-Hsing
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Chung, I-Ping
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Lee, Amy H. I.
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工業工程與管理學系
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Department of Industrial Engineering and Management
Semiconductor production turnkey service (SPTS) coordinates wafer fabrication with the outsourcing of the remaining processes including circuit probing testing (C/P testing), integrated circuit (IC) assembly and final testing for buyers. To reduce the production cost and lead time in the supply chain, wafer fabricators must be responsible for the production and distribution planning for the SPTS. Therefore, this research develops an integer-programming (IP) -based model of collaborative production-distribution planning. Under this model, multi-products, multi-stages, and multi-outsourcing factories with different processing capabilities are considered. However, the IP model cannot solve the problem within a polynomial time when the problem becomes as complicated as those in real practice. To confront this problem, we adopt and modify the generalized saving algorithm (GSA) so that the proposed algorithm can solve complicated real-world problems efficiently. The numerical results show that the proposed algorithm can significantly increase the solving efficiency.