No / The dependency of maintenance as a manufacturing logistic function has made the considerations and constrains of maintenance decisions complex in nature. The rapid growth of automation in manufacturing process has also increased the role of maintenance as an inseparable business partner. As consequence, maintenance strategy and operations should always be aligned with business and manufacturing perspectives within a holistic and integrated manner to achieve competitive advantage. This paper presents a framework of Knowledge Based System for Integrated Maintenance Strategy and Operation (KBIMSO) linked to business and manufacturing perspectives. The KBIMSO framework has novelty of simultaneously highlighting the elements of business, manufacturing and maintenance perspectives which contribute to direct maintenance performance and can be used by the companies to evaluate their existing maintenance system in relation to business competitive priorities and manufacturing process requirements in order to gain optimal maintenance performance as the competitive driver. / Support for this study is provided by the Directorate of Higher Education, Ministry of National Education, Republic of Indonesia and the University of Bradford, the United Kingdom. / The full text cannot be displayed due to the publisher's copyright agreement.

Yes / Designing 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.

The 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. / Universiti Utara Malaysia and Ministry of Higher Education of Malaysia

The 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.

The product development process for the automotive industry is normally complicated, lengthy, expensive, and risky. Hence, a study on a new concept for Low Volume Automotive Manufacturing (LVAM), used for niche car models manufacturing, is proposed to overcome this issue. The development of a hybrid Knowledge Based (KB) System, which is a blend of KB System, Gauging Absences of Pre-requisites (GAP), and Analytic Hierarchy Process (AHP) is proposed for LVAM research. The hybrid KB/GAP/AHP System identifies all potential elements of LVAM issues throughout the development of this system. The KB System used in the LVAM analyses the gap between the existing and the benchmark organisations for an effective implementation. The novelty and differences in the current research approach emphasises the use of Knowledge Based (KB) System in the planning and designing stages by suggesting recommendations of LVAM implementation, through: a) developing the conceptual LVAM model; b) designing the KBLVAM System structure based on the conceptual LVAM model; and c) embedding Gauging Absences of Pre-requisites (GAP) analysis and Analytic Hierarchy Process (AHP) approach in the hybrid KBLVAM System. The KBLVAM Model explores five major perspectives in two stages. Planning Stage (Stage 1) consists of Manufacturer Environment Perspective (Level 0), LVAM Manufacturer Business Perspective (Level 1), and LVAM Manufacturer Resource Perspective (Level 2). Design Stage (Stage 2) consists of LVAM Manufacturer Capability - Car Body Part Manufacturing Perspective (Level 3), LVAM Manufacturer Capability - Competitive Priorities Perspective (Level 4), and LVAM Manufacturer Capability - Lean Process Optimisation Perspective (Level 5). Each of these perspectives consists of modules and sub-modules that represent specific subjects in the LVAM development. Based on the conceptual LVAM model, all perspectives were transformed into the KBLVAM System structure, which is embedded with the GAP and AHP techniques, hence, key areas of potential improvement are recommended for each activity for LVAM implementation. In order to be able to address the real situation of LVAM environment, the research verification was conducted for two automotive manufacturers in Malaysia. Some published case studies were also used to check several modules for their validity and reliability. This research concludes that the developed KBLVAM System provides valuable decision making information and knowledge to assist LVAM practitioners to plan, design and implement LVAM in terms of business organisation, manufacturing aspects and practices.

The product development process for the automotive industry is normally complicated, lengthy, expensive, and risky. Hence, a study on a new concept for Low Volume Automotive Manufacturing (LVAM), used for niche car models manufacturing, is proposed to overcome this issue. The development of a hybrid Knowledge Based (KB) System, which is a blend of KB System, Gauging Absences of Pre-requisites (GAP), and Analytic Hierarchy Process (AHP) is proposed for LVAM research. The hybrid KB/GAP/AHP System identifies all potential elements of LVAM issues throughout the development of this system. The KB System used in the LVAM analyses the gap between the existing and the benchmark organisations for an effective implementation. The novelty and differences in the current research approach emphasises the use of Knowledge Based (KB) System in the planning and designing stages by suggesting recommendations of LVAM implementation, through: a) developing the conceptual LVAM model; b) designing the KBLVAM System structure based on the conceptual LVAM model; and c) embedding Gauging Absences of Pre-requisites (GAP) analysis and Analytic Hierarchy Process (AHP) approach in the hybrid KBLVAM System. The KBLVAM Model explores five major perspectives in two stages. Planning Stage (Stage 1) consists of Manufacturer Environment Perspective (Level 0), LVAM Manufacturer Business Perspective (Level 1), and LVAM Manufacturer Resource Perspective (Level 2). Design Stage (Stage 2) consists of LVAM Manufacturer Capability ¿ Car Body Part Manufacturing Perspective (Level 3), LVAM Manufacturer Capability ¿ Competitive Priorities Perspective (Level 4), and LVAM Manufacturer Capability ¿ Lean Process Optimisation Perspective (Level 5). Each of these perspectives consists of modules and sub-modules that represent specific subjects in the LVAM development. Based on the conceptual LVAM model, all perspectives were transformed into the KBLVAM System structure, which is embedded with the GAP and AHP techniques, hence, key areas of potential improvement are recommended for each activity for LVAM implementation. In order to be able to address the real situation of LVAM environment, the research verification was conducted for two automotive manufacturers in Malaysia. Some published case studies were also used to check several modules for their validity and reliability. This research concludes that the developed KBLVAM System provides valuable decision making information and knowledge to assist LVAM practitioners to plan, design and implement LVAM in terms of business organisation, manufacturing aspects and practices. / Universiti Malaysia Pahang and Ministry of Higher Education Malaysia

Supply chain operations of construction industry including road projects in disaster regions results in exceeding project budget and timelines. In road construction projects, supply chain with poor performance can affect efficiency and completion time of the project. This is also the case of the road projects in disaster areas. Disaster areas consider both natural and man-made disasters. Few examples of disaster zones are; Pakistan, Afghanistan, Iraq, Sri Lanka, India, Japan, Haiti and many other countries with similar environments. The key factors affecting project performance and execution are insecurity, uncertainties in demand and supply, poor communication and technology, poor infrastructure, lack of political and government will, unmotivated organizational staff, restricted accessibility to construction materials, legal hitches, multiple challenges of hiring labour force and exponential construction rates due to high risk environment along with multiple other factors. The managers at all tiers are facing challenges of overrunning time and budget of supply chain operations during planning as well as execution phase of development projects. The aim of research is to develop a Multiple Linear Regression Model (MLRM) and a Rule Based Decision Support System by incorporating various factors affecting supply chain management of road projects in disaster areas in the order of importance. This knowledge base (KB) (importance / coefficient of each factor) will assist infrastructure managers (road projects) and practitioners in disaster regions in decision making to minimize the effect of each factor which will further help them in project improvement. Conduct of Literature Review in the fields of disaster areas, supply chain operational environments of road project, statistical techniques, Artificial Intelligence (AI) and types of research approaches has provided deep insights to the researchers. An initial questionnaire was developed and distributed amongst participants as pilot project and consequently results were analysed. The results’ analysis enabled the researcher to extract key variables impacting supply chain performance of road project. The results of questionnaire analysis will facilitate development of Multiple Linear Regression Model, which will eventually be verified and validated with real data from actual environments. The development of Multiple Linear Regression Model and Rule Based Decision Support System incorporating all factors which affect supply chain performance of road projects in disastrous regions is the most vital contribution to the research. The significance and novelty of this research is the methodology developed that is the integration of those different methods which will be employed to measure the SCM performance of road projects in disaster areas.