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Multi-Period Production Capacity Planning for Integrated Product and Production System Design

dc.contributor.authorKazancioglu, Emreen_US
dc.contributor.authorSaitou, Kazuhiroen_US
dc.date.accessioned2011-11-14T16:31:20Z
dc.date.available2011-11-14T16:31:20Z
dc.date.issued2006-10-08en_US
dc.identifier.citationKazancioglu, E.; Saitou, K. (2006). Multi-Period Production Capacity Planning for Integrated Product and Production System Design." Proceedings of the IEEE Conference on Automation Science and Engineering: 3-8. <http://hdl.handle.net/2027.42/87270>en_US
dc.identifier.isbn1-4244-0310-3en_US
dc.identifier.urihttps://hdl.handle.net/2027.42/87270
dc.description.abstractThis paper presents a simulation-based method to aid multi-period production capacity planning by quantifying the trade-off between product quality and production cost. The product quality is estimated as the statistical variation from the target performances obtained from the output tolerances of the production machines that manufacture the components. The production cost is estimated as the total cost of owning and operating a production facility during the planning horizon. Given demand forecasts in future production periods, a multi-objective genetic algorithm searches for the optimal types and quantity of the production machines to be purchased during each period, which simultaneously maximize the product quality and minimize the production cost during the entire planning horizon. Case studies on automotive valvetrain production are presented as a demonstrationen_US
dc.publisherIEEEen_US
dc.titleMulti-Period Production Capacity Planning for Integrated Product and Production System Designen_US
dc.typeArticleen_US
dc.subject.hlbsecondlevelMechanical Engineeringen_US
dc.subject.hlbtoplevelEngineeringen_US
dc.description.peerreviewedPeer Revieweden_US
dc.contributor.affiliationumDepartment of Mechanical Engineeringen_US
dc.contributor.affiliationotherInstitute for Manufacturing, University of Cambridge, Mill Lane, Cambridge CB2 1RX, UK.en_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/87270/4/Saitou68.pdf
dc.identifier.doi10.1109/COASE.2006.326846en_US
dc.identifier.sourceProceedings of the IEEE Conference on Automation Science and Engineeringen_US
dc.owningcollnameMechanical Engineering, Department of


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