The Development of a Hybrid Knowledge-Based System for Integrated Maintenance Strategy and Operations in an Automotive Industry Environment: The Development of a Hybrid Knowledge-Based (KB) System/ Gauging Absences of Pre-Requisites (GAP)/Analytic Hierarchy Process (AHP) Methodology for Integrated Maintenance Strategy and Operations in an Automotive Industry Environment
dc.contributor.advisor | Munive-Hernandez, J. Eduardo | |
dc.contributor.advisor | Khan, M. Khurshid | |
dc.contributor.author | Milana, Milana | |
dc.date.accessioned | 2019-11-14T13:05:08Z | |
dc.date.available | 2019-11-14T13:05:08Z | |
dc.identifier.uri | http://hdl.handle.net/10454/17446 | |
dc.description.abstract | The dependency of maintenance as a manufacturing logistic function has made the considerations of maintenance decisions complex in nature. The importance of maintenance has escalated significantly by the increasing of automation in manufacturing processes. This condition switches the traditional maintenance perspective of “fire-fighter” into the business competitive driver. As a consequence, maintenance needs to consider other related aspects of decision making to achieve competitive advantage. This research aims to develop a hybrid Knowledge-Based (KB) System/GAP/AHP methodology to support the integration of maintenance decision with business and manufacturing perspectives. It constructs over 2000 KB rules on Strategic Stage (business and manufacturing aspects) and Maintenance Operations Stage (maintenance aspects). Each aspect contains KB rules attached with GAP analysis to assess the gap between current and prerequisite condition. AHP analysis is then deployed to compare those aspects structurally in a pair-wise manner to identify the critical ones to be rectified. This hybrid KB system is useful in reviewing the existing maintenance system performance and provides reasonable recommendations to improve maintenance performance with respect to business and manufacturing perspectives. Eventually, it indicates the roadmap from the current state to the benchmark goals for the maintenance system. This novel methodology of KBS/GAP/AHP to support maintenance decision is developed for a particular application in the automotive environment. The validation is conducted in two automotive companies in Indonesia and one published case study in an automotive company. The result confirms that the developed KB system can provide the valid, reasonable and consistent result to propose structured recommendation for maintenance improvement priority. | en_US |
dc.language.iso | en | en_US |
dc.publisher | University of Bradford | en_US |
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>. | eng |
dc.subject | Integrated maintenance strategy and operations | en_US |
dc.subject | Business | en_US |
dc.subject | Manufacturing | en_US |
dc.subject | Automotive industry | en_US |
dc.subject | Knowledge management | en_US |
dc.subject | Knowledge-based expert system | en_US |
dc.subject | Gauging absences of pre-requisites | en_US |
dc.subject | Analytic hierarchy process | en_US |
dc.title | The Development of a Hybrid Knowledge-Based System for Integrated Maintenance Strategy and Operations in an Automotive Industry Environment: The Development of a Hybrid Knowledge-Based (KB) System/ Gauging Absences of Pre-Requisites (GAP)/Analytic Hierarchy Process (AHP) Methodology for Integrated Maintenance Strategy and Operations in an Automotive Industry Environment | en_US |
dc.type.qualificationlevel | doctoral | en_US |
dc.publisher.institution | University of Bradford | eng |
dc.publisher.department | Faculty of Management, Law and Social Sciences | en_US |
dc.type | Thesis | eng |
dc.type.qualificationname | PhD | en_US |
dc.date.awarded | 2018 | |
refterms.dateFOA | 2019-11-14T13:05:08Z |