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dc.contributor.authorMustafa Fatih, Yegul
dc.date.accessioned2014-11-21 14:47:41 (GMT)
dc.date.available2014-11-21 14:47:41 (GMT)
dc.date.issued2014-11-21
dc.date.submitted2014
dc.identifier.urihttp://hdl.handle.net/10012/8946
dc.description.abstractWith the recent trend of re-shoring, transferring manufacturing systems from a workforce-intensive to a capital-intensive production environment becomes more common. One challenge multinational manufacturing companies may face in such an endeavor is reconfiguration of the transferred manufacturing system according to the availability of better machinery in the capital-intensive environment. In this dissertation, based on a real-life problem, I develop several simulation optimization methods for the problem of production line reconfiguration. The case is a reverse transfer of manufacturing system/technology, i.e. transfer from a workforce-intensive environment to a capital-intensive one. I investigate the performances of nine different simulation optimization approaches based on the real-life case in automotive industry to illustrate their relative strengths under different parameter scenarios. I also create a test-bed problem to determine the specifications of these methods, and further analyze their performances. Numerical results may guide the practitioners facing similar challenges in choosing a suitable solution approach depending on the problem size and solution time availability.en
dc.language.isoenen
dc.publisherUniversity of Waterlooen
dc.subjectAnt Colony Optimizationen
dc.subjectResponse Surface Metholologyen
dc.subjectSimulated Annealingen
dc.subjectProduction Line Configurationen
dc.subjectSimulation Optimizationen
dc.titleOptimal Reconfiguration of Complex Production Lines for Profit Maximization via Simulation Modelingen
dc.typeDoctoral Thesisen
dc.pendingfalse
dc.subject.programMechanical Engineeringen
uws-etd.degree.departmentMechanical and Mechatronics Engineeringen
uws-etd.degreeDoctor of Philosophyen
uws.typeOfResourceTexten
uws.peerReviewStatusUnrevieweden
uws.scholarLevelGraduateen


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