Please use this identifier to cite or link to this item: http://ir.mu.ac.ke:8080/jspui/handle/123456789/5801
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dc.contributor.authorSsempijja, Maureen Nalubowa-
dc.contributor.authorNamango, Saul-
dc.contributor.authorOchola, Jerry-
dc.contributor.authorMubiru, Paul Kizito-
dc.date.accessioned2022-01-25T11:54:30Z-
dc.date.available2022-01-25T11:54:30Z-
dc.date.issued2021-
dc.identifier.urihttp://ir.mu.ac.ke:8080/jspui/handle/123456789/5801-
dc.description.abstractManufacturing is an essential aspect to the global economy and prosperity. Many Manufacturing systems operate in an uncertain environment which affects the system performance. Production planning is very key in improving the overall manufacturing system performance. Systems that apply production planning approaches not considering uncertainties yield inferior planning decisions as compared to those that explicitly account for the uncertainty. Markov chains can be used to capture the transition probabilities as changes occur. Some existing literature on application of Markov chains in manufacturing systems has been reviewed. The objective is to give the reader beginning points about uncertainty modelling in manufacturing systems using Markov chains.en_US
dc.language.isoenen_US
dc.subjectManufacturing systemsen_US
dc.subjectProduction planningen_US
dc.subjectMarkov chainsen_US
dc.titleApplication of Markov chains in manufacturing systems: A reviewen_US
dc.typeArticleen_US
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