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dc.contributor.authorWibisono, D.*
dc.contributor.authorKhan, M. Khurshid*
dc.date.accessioned2016-08-10T13:11:40Z
dc.date.available2016-08-10T13:11:40Z
dc.date.issued2015-12
dc.identifier.citationWibisono D and Khan MK (2015) Performance measurement system for a manufacturing environment: KB/GAP/AHP approach. International Journal of Robotics and Mechatronics. 2(2): 65-76.
dc.identifier.urihttp://hdl.handle.net/10454/8766
dc.descriptionYes
dc.description.abstractDesigning and implementing Performance Measurement System (PMS) is an integral part of management control systems. This paper presents an original and novel approach to designing and benchmarking of PMSs for a manufacturing environment through a hybrid framework which overcomes the shortcomings of earlier models. A detailed review was taken of previous models and their limitations were identified. The present hybrid PMS model seeks to improve the earlier research models by the following novel approach: implementation of a Knowledge Based (KB) expert system, Gauging Absences of Pre-requisite (GAP) analysis and Analytic Hierarchy Process (AHP) methodology in an integrated KBPMS. The paper has shown that the present hybrid (KB-AHP-GAP) approach to developing a KBPMS model is a realistic methodology. The combination of the KB-AHP-GAP approach allows detailed benchmarking of the PMS existing within a manufacturing organisation. Furthermore, this approach can assist in identifying and prioritising the key decisions that need to be actioned to overcome the existing PMS shortcomings.
dc.language.isoenen
dc.rights© 2015 The Authors. This work is licensed under a Creative Commons Attribution Licence (http://creativecommons.org/licenses/by/3.0/ )
dc.subjectPerformance Measurement System (PMS)
dc.subjectKnowledge Based (KB)
dc.subjectExpert systems
dc.subjectGAP analysis
dc.subjectAnalytic Hierarchy Process (AHP)
dc.titlePerformance measurement system for a manufacturing environment: KB/GAP/AHP approach
dc.status.refereedYes
dc.typeArticle
dc.type.versionPublished version
dc.identifier.doihttps://doi.org/10.21535%2Fijrm.v2i2.866
dc.rights.licenseCC-BY
refterms.dateFOA2018-07-25T12:26:12Z
dc.openaccess.statusopenAccess
dc.date.accepted2015-12-27


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