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An approximation for kanban controlled assembly systems

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dc.contributor.author Topan, Engin
dc.contributor.author Avşar, Zeynep Müge
dc.date.accessioned 2016-08-09T07:56:05Z
dc.date.available 2016-08-09T07:56:05Z
dc.date.issued 2011-01
dc.identifier.citation Topan, E., Avşar, Z.M. (2011). An approximation for kanban controlled assembly systems. Annals of Operations Research, 182(1), 133-162. http://dx.doi.org/10.1007/s10479-009-0560-1 tr_TR
dc.identifier.issn 0254-5330
dc.identifier.uri http://hdl.handle.net/20.500.12416/1197
dc.description.abstract An approximation is proposed to evaluate the steady-state performance of kanban controlled two-stage assembly systems. The development of the approximation is as follows. The considered continuous-time Markov chain is aggregated keeping the model exact, and this aggregate model is approximated replacing some state-dependent transition rates with constant rates. The approximate aggregate model is, then, decomposed into submodels and a product-form steady-state distribution is obtained for each submodel. Finally, the submodels are combined in such a way that the size of the problem becomes independent of the number of kanbans. This leads to the computational advantage in solving the combined model using numerical matrix-geometric solution algorithms. Numerical comparisons of the combined model with simulation, exact model, approximate aggregate model and an approximation in the literature show that the proposed approximation performs well in terms of accuracy and computational burden tr_TR
dc.language.iso eng tr_TR
dc.publisher Springer tr_TR
dc.relation.isversionof 10.1007/s10479-009-0560-1 tr_TR
dc.rights info:eu-repo/semantics/closedAccess
dc.subject Assembly Systems tr_TR
dc.subject Approximation tr_TR
dc.subject Performance Evaluation tr_TR
dc.subject Matrix Geometric Solution tr_TR
dc.subject Kanban Control tr_TR
dc.subject Steady-State Behavior tr_TR
dc.title An approximation for kanban controlled assembly systems tr_TR
dc.type article tr_TR
dc.relation.journal Annals of Operations Research tr_TR
dc.contributor.authorID 164129 tr_TR
dc.identifier.volume 182 tr_TR
dc.identifier.issue 1 tr_TR
dc.identifier.startpage 133 tr_TR
dc.identifier.endpage 162 tr_TR
dc.contributor.department Çankaya Üniversitesi, Mühendislik Fakültesi, Endüstri Mühendisliği Bölümü tr_TR


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