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Application of Markov chains in manufacturing systems: A review

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dc.contributor.author Ssempijja, Maureen Nalubowa
dc.contributor.author Namango, Saul
dc.contributor.author Ochola, Jerry
dc.contributor.author Mubiru, Paul Kizito
dc.date.accessioned 2022-01-25T11:54:30Z
dc.date.available 2022-01-25T11:54:30Z
dc.date.issued 2021
dc.identifier.uri http://ir.mu.ac.ke:8080/jspui/handle/123456789/5801
dc.description.abstract Manufacturing 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.iso en en_US
dc.subject Manufacturing systems en_US
dc.subject Production planning en_US
dc.subject Markov chains en_US
dc.title Application of Markov chains in manufacturing systems: A review en_US
dc.type Article en_US


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