Discrete-event simulation of process control in low volume high value industries

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dc.contributor.authorCox, Steven
dc.contributor.authorGarside, John
dc.contributor.authorKotsialos, Apostolos
dc.date.accessioned2015-09-25T10:43:08Z
dc.date.available2015-09-25T10:43:08Z
dc.date.issued2013-09-19
dc.description.abstractThis paper presents a new method of process control for set-up dominant processes. This new method known as Set-up Process Algorithm (SUPA) was compared with existing industrial practices and statistical techniques in the literature. To test the method’s robustness, a generic discrete-event simulation model was built. This model was used to test four different statistical approaches to process control. It was concluded that SUPA offers a method of process control for set-up dominant processes, which is easier to apply than classically derived SPC approaches, by using simple rules and a traffic light system based on design specification. Simulation analysis shows that SUPA: is more sensitive, at detecting an incapable process as it will monitor more units when a process is less capable; is more sensitive than PRE-Control at detecting mean shifts in a process. SUPA is also a nonparametric methodology and therefore robust against processes with non-Gaussian distributions.en_UK
dc.identifier.citationCox S., Garside J. and Kotsialos A. (2013). Discrete-event simulation of process control in low volume high value industries. Proceedings of the 11th International Conference on Manufacturing Research (ICMR2013), Cranfield University, UK, 19th – 20th September 2013, pp 599-604en_UK
dc.identifier.isbn9781907413230
dc.identifier.urihttp://dspace.lib.cranfield.ac.uk/handle/1826/9516
dc.language.isoenen_UK
dc.publisherCranfield University Pressen_UK
dc.relation.ispartofseriesQuality and Performance Measurementen_UK
dc.relation.ispartofseries8en_UK
dc.subjectpre-controlen_UK
dc.subjectstatistical process controlen_UK
dc.subjectprocess set-upen_UK
dc.titleDiscrete-event simulation of process control in low volume high value industriesen_UK
dc.typeConference paperen_UK

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International Conference on Manufacturing Research (ICMR 2013)