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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.en_US
dc.identifier.urihttp://hdl.handle.net/10454/8766
dc.descriptionYesen_US
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.en_US
dc.language.isoenen_US
dc.relation.isreferencedbyhttp://dx.doi.org/10.21535%2Fijrm.v2i2.866en_US
dc.rights© 2015 The Authors. This work is licensed under a Creative Commons Attribution Licence (http://creativecommons.org/licenses/by/3.0/ )en_US
dc.subjectPerformance Measurement System (PMS); Knowledge Based (KB); Expert systems; GAP analysis; Analytic Hierarchy Process (AHP)en_US
dc.titlePerformance measurement system for a manufacturing environment: KB/GAP/AHP approachen_US
dc.status.refereedYesen_US
dc.date.Accepted2015-12-27
dc.typeArticleen_US
dc.type.versionpublished version paperen_US
refterms.dateFOA2018-07-25T12:26:12Z


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