Schedule performance measurement based on statistical process control charts

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dc.contributor.author Oleghe, Omogbai
dc.contributor.author Salonitis, Konstantinos
dc.date.accessioned 2017-03-27T11:13:47Z
dc.date.available 2017-03-27T11:13:47Z
dc.date.issued 2014-03-14
dc.identifier.citation Omogbai Oleghe and Konstantinos Salonitis. Schedule performance measurement based on statistical process control charts. International Journal of Engineering Management and Economics, 2014, Vol. 4, No. 3/4, pp194-212 en_UK
dc.identifier.issn 1756-5154
dc.identifier.uri http//dx.doi.org/10.1504/IJEME.2014.066940
dc.identifier.uri http://dspace.lib.cranfield.ac.uk/handle/1826/11658
dc.description.abstract In a job-shop manufacturing environment, achieving a schedule that is on target is difficult due to the dynamism of factors affecting the system, and this makes schedule performance measurement systems hard to design and implement. In the present paper, Statistical Process Control charts are directly applied to a scheduling process for the purpose of objectively measuring schedule performance. SPC charts provide an objective and timely approach to designing, implementing and monitoring schedule performance. However, the use of Statistical Process Control charts requires an appreciation of the conditions for applying raw data to SPC charts. In the present paper, the Shewart’s Individuals control chart are applied to monitor the deviations of actual process times from the scheduled process times for each job on a process machine. The Individuals control charts are highly sensitive to non-normal data, which increases the rate of false alarms, but this can be avoided using data transformation operations such as the Box-Cox transformation. Statistical Process Control charts have not been used to measure schedule performance in a job shop setting, so this paper uniquely contributes to research in this area. In addition, using our proposed methodology enables a scheduler to monitor how an optimal schedule has performed on the shop floor, study the variations between planned and actual outcomes, seek ways of eliminating these variations and check if process improvements have been effective. en_UK
dc.language.iso en en_UK
dc.publisher Inderscience en_UK
dc.rights Published by Inderscience. This is the Author Accepted Manuscript. This article may be used for personal use only. The final published version (version of record) is available online at DOI:10.1504/IJEME.2014.066940. Please refer to any applicable publisher terms of use.
dc.subject Performance measurement system en_UK
dc.subject job shop scheduling en_UK
dc.subject schedule performance en_UK
dc.subject statistical process control charts en_UK
dc.subject individuals controls chart en_UK
dc.title Schedule performance measurement based on statistical process control charts en_UK
dc.type Article en_UK


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