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- W2891437434 abstract "With today's worldwide competition, manufacturing companies are faced with challenges to respond to volatile market demands quickly and flexibly while maintaining a cost-effective level of production. Capacity adjustment is one of the major approaches to cope with such uncertain fluctuations, balance capacity and load and improve the effectiveness of manufacturing control. Instead of flexible staffs, working time and outsourcing, in this paper, we consider a machinery-based capacity adjustment via Reconfigurable Machine Tools (RMTs) to compensate for unpredictable events. To include these tools effectively on the operational and tactical layer, we propose a complementing feedback approach using model predictive control (MPC) to identify the potential of RMTs for a better compliance with logistics objectives and a sustainable demand oriented capacity allocation. To this end, we formulate a reconfiguration rule for the determination of the triggered RMTs and propose three strategies for resolving the intege..." @default.
- W2891437434 created "2018-09-27" @default.
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- W2891437434 date "2018-09-17" @default.
- W2891437434 modified "2023-10-16" @default.
- W2891437434 title "Combining MPC and integer operators for capacity adjustment in job-shop systems with RMTs" @default.
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- W2891437434 doi "https://doi.org/10.1080/00207543.2018.1521022" @default.
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