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Planning Demand-Driven Disassembly for Remanufacturing

By: Langella, Ian M [author.].
Contributor(s): SpringerLink (Online service).
Material type: materialTypeLabelBookPublisher: Wiesbaden : DUV, 2007.Description: XXI, 121 p. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783835095953.Subject(s): Business | Production management | Business and Management | Operations ManagementDDC classification: 658.5 Online resources: Click here to access online
Contents:
Fundamentals -- Planning disassembly with deterministic yields -- Planning disassembly with stochastic yields -- Conclusion and outlook.
In: Springer eBooksSummary: Remanufacturing has received increasing attention in the recent past as more companies engage in product recovery management. Ian M. Langella examines the planning of disassembly for remanufacturing of used products, yielding components which are reassembled into “as good as new” items. Through a thorough analysis of the underlying planning problem, fundamental insights are attained and heuristic solution methods are developed and tested. Although the heuristics exhibit good performance, they remain simple enough to be applied to industrial-sized problems. The author considers both settings where yields are deterministic and stochastic and where the amount of returned products is constrained.
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Item type Current location Call number Status Date due Barcode Item holds
E books E books PK Kelkar Library, IIT Kanpur
Available EBK7337
Total holds: 0

Fundamentals -- Planning disassembly with deterministic yields -- Planning disassembly with stochastic yields -- Conclusion and outlook.

Remanufacturing has received increasing attention in the recent past as more companies engage in product recovery management. Ian M. Langella examines the planning of disassembly for remanufacturing of used products, yielding components which are reassembled into “as good as new” items. Through a thorough analysis of the underlying planning problem, fundamental insights are attained and heuristic solution methods are developed and tested. Although the heuristics exhibit good performance, they remain simple enough to be applied to industrial-sized problems. The author considers both settings where yields are deterministic and stochastic and where the amount of returned products is constrained.

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