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dc.contributor.authorMoeeni, Farhad.
dc.creatorMoeeni, Farhad.en_US
dc.date.accessioned2011-10-31T17:57:39Z
dc.date.available2011-10-31T17:57:39Z
dc.date.issued1992en_US
dc.identifier.urihttp://hdl.handle.net/10150/186073
dc.description.abstractMany industries are in the process of adopting or considering adoption of the Just-In-Time philosophy and techniques. Most of these firms are not characterized by the type of environment which is required for transferring the philosophy, such as stable manufacturing factors. The adverse effect of environmental uncertainties on the operating phase of Just-In-Time systems in general and the performance of Kanban systems in particular has been well documented. This dissertation proposes a framework for designing robust Kanban systems, by adopting the product and process design approach pioneered by Genichi Taguchi. A robust Kanban systems is one whose performance is insensitive to environmental uncertainties. As part of our investigation, we illustrate how frequency domain experiments can be used in order to investigate the effect of noise factors and their interactions on the performance of a Kanban system. The technique allows us to examine simultaneously many factors that previous researchers have studied separately, and so explore and identify important interaction effects. We develop a general framework for designing a robust Kanban system that can be applied to different production configurations, and illustrate the robust design process via a simulation study of a three-stage manufacturing line.
dc.language.isoenen_US
dc.publisherThe University of Arizona.en_US
dc.rightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.en_US
dc.subjectDissertations, Academic.en_US
dc.subjectOperations research.en_US
dc.subjectIndustrial engineering.en_US
dc.titleA parameter design framework for designing robust Just-In-Time production systems with Kanban.en_US
dc.typetexten_US
dc.typeDissertation-Reproduction (electronic)en_US
dc.contributor.chairSanchez, Susan M.en_US
dc.identifier.oclc714879728en_US
thesis.degree.grantorUniversity of Arizonaen_US
thesis.degree.leveldoctoralen_US
dc.contributor.committeememberVakharia, Asoo J.en_US
dc.contributor.committeememberSlaten, Pamela E.en_US
dc.contributor.committeememberKannan, Pallassana K.en_US
dc.identifier.proquest9309033en_US
thesis.degree.disciplineBusiness Administrationen_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.namePh.D.en_US
refterms.dateFOA2018-08-23T09:51:40Z
html.description.abstractMany industries are in the process of adopting or considering adoption of the Just-In-Time philosophy and techniques. Most of these firms are not characterized by the type of environment which is required for transferring the philosophy, such as stable manufacturing factors. The adverse effect of environmental uncertainties on the operating phase of Just-In-Time systems in general and the performance of Kanban systems in particular has been well documented. This dissertation proposes a framework for designing robust Kanban systems, by adopting the product and process design approach pioneered by Genichi Taguchi. A robust Kanban systems is one whose performance is insensitive to environmental uncertainties. As part of our investigation, we illustrate how frequency domain experiments can be used in order to investigate the effect of noise factors and their interactions on the performance of a Kanban system. The technique allows us to examine simultaneously many factors that previous researchers have studied separately, and so explore and identify important interaction effects. We develop a general framework for designing a robust Kanban system that can be applied to different production configurations, and illustrate the robust design process via a simulation study of a three-stage manufacturing line.


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