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dc.contributor.advisorKhan, M. Khurshid
dc.contributor.advisorHussain, Khalid
dc.contributor.authorMoud Nawawi, Mohd Kamal*
dc.date.accessioned2009-08-24T15:33:29Z
dc.date.available2009-08-24T15:33:29Z
dc.date.issued2009-08-24T15:33:29Z
dc.identifier.urihttp://hdl.handle.net/10454/3353
dc.description.abstractThe automotive manufacturing facility is extremely complex and expensive system. Managing and understanding the dynamics of automotive manufacturing is a challenging endeavour. In the current era of dynamic global competition, a new concept such as Collaborative Lean Manufacturing Management (CLMM) can be implemented as an alternative for organisations to improve their Lean Manufacturing Management (LMM) processes. All members in the CLMM value chain must work together towards common objectives in order to make the LMM achievable in the collaborative environment. The novel research approach emphasises the use of Knowledge-Based (KB) approach in such activities as planning, designing, assessing and providing recommendations of CLMM implementation, through: a) developing the conceptual CLMM model; b) designing the KBCLMM System structure based on the conceptual model; and c) implementing Gauging Absences of Pre-requisites (GAP) analysis and Analytic Hierarchy Process (AHP) approach in the hybrid KBCLMM. The development of KBCLMM Model is the most detailed part in the research process and consists of five major components in two stages. Stage 1 (Planning stage) consists of Organisation Environment, Collaborative Business and Lean Manufacturing components. Stage 2 (Design stage) consists of Organisation CLMM Capability and Organisation CLMM Alignment components. Each of these components consists of sub-components and activities that represent particular issues in the CLMM development. From the conceptual model, all components were transformed into the KBCLMM System structure, which is embedded with the GAP and AHP techniques, and thus, key areas of potential improvement in the LMM are identified for each activity along with the identification of both qualitative and quantitative aspects for CLMM implementation. In order to address the real situation of CLMM operation, the research validation was conducted for an automotive manufacturer¿s Lean Manufacturing Chain in Malaysia. Published case studies were also used to test several modules for their validity and reliability. This research concludes that the developed KBCLMM System is an appropriate Decision Support System tool to provide the opportunity for academics and industrialists from the fields of industrial engineering, information technology, and operation management to plan, design and implement LMM for a collaborative environment.en
dc.description.sponsorshipUniversiti Utara Malaysia and Ministry of Higher Education of Malaysiaen
dc.language.isoenen
dc.rights<a rel="license" href="http://creativecommons.org/licenses/by-nc-nd/3.0/"><img alt="Creative Commons License" style="border-width:0" src="http://i.creativecommons.org/l/by-nc-nd/3.0/88x31.png" /></a><br />The University of Bradford theses are licenced under a <a rel="license" href="http://creativecommons.org/licenses/by-nc-nd/3.0/">Creative Commons Licence</a>.en
dc.subjectLean Manufacturing Management (LMM)en
dc.subjectAutomotive manufacturingen
dc.subjectKnowledge-Based (KB)en
dc.subjectCollaborativeen
dc.subjectGauging Absences of Pre-requisites (GAP)en
dc.subjectAnalytic Hierarchy Process (AHP)en
dc.subjectMalaysiaen
dc.titleThe development of a hybrid knowledge-based Collaborative Lean Manufacturing Management (CLMM) system for an automotive manufacturing environment: The development of a hybrid Knowledge-Based (KB)/ Analytic Hierarchy Process (AHP)/ Gauging Absences of Pre-Requisites (GAP) Approach to the design of a Collaborative Lean Manufacturing Management (CLMM) system for an automotive manufacturing environment.en
dc.type.qualificationleveldoctoralen
dc.publisher.institutionUniversity of Bradfordeng
dc.publisher.departmentSchool of Engineering, Design and Technologyen
dc.typeThesiseng
dc.type.qualificationnamePhDen
dc.date.awarded2009
refterms.dateFOA2018-07-18T14:15:15Z


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