Papers by Keyword: Multi Criteria Decision Making

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Authors: Nanang Fatchurrohman, Shamsuddin Sulaiman, S.M. Sapuan, Mohd Khairol Anuar Ariffin, B.T. Hang Tuah Baharudin
Abstract: Product development process involves conceptual design selection, which is an activity engaging with numerous types of data including technical-customer specifications and current design developments. This paper presents a conceptual design selection which employs a new technique which accommodates Concurrent Engineering (CE) – Multi Criteria Decision Making (MCDM) strategies. This new technique combines Concurrent Network (CE-ANP), Quality Function Deployment (QFD) and Analytical Hierarchy Process (AHP), referred as CoNQA. To illustrate this technique, a case study is presented involving aerospace application which is the selection of wing spar material. The result shows that the proposed new technique proved to be a sound method which considers product performance, product specification, technical specifications and selection of the best alternative in the selection process. This new method should be a useful aid for designers in collaboration with engineers to perform systematic and parallel technique involving early consideration of technical-customer requirements during conceptual design, hence to establish good product design and increase product competitiveness.
Authors: Ana Sakura Zainal Abidin, Rasli Muslimen, Rosnah Mohd Yusuff
Abstract: Competition dynamically pushes manufacturing ahead. Consequently, design capabilities identified as strategic weapon that offers tremendous opportunities. However, design capabilities development is a stringent challenge to an organization especially in high technology base like automotive. In Malaysia, especially vendors has limited capabilities consequently bound the development steps. There are numerous critical success factors (CSFs) involved in developing successful design capabilities. Thus, makes the development process more complicated. All important CSFs have to be determined and rank accordingly. The CSFs are then applied in a model, using multi criteria decision making approach to facilitate the development process.
Authors: Waled Alzober, Abdul Razak Yaakub
Abstract: A complex or unstructured problem is based on multi criteria not on a single criterion. A contractor selection problem is a multi-criteria problem. A correct decision-making is required for selecting the appropriate contractor for a construction project. Selection of a contractor is a key decision made by clients and the process of selection a contractor has become an important issue in construction projects. Many multi-criteria techniques have been proposed and applied to such problems solution. This paper aims to propose integrated model for MCDM. The integrated model contains two stages. First stage integrates two MCDM methods are AHP and ANN to prepare a shortlist of the best alternatives. Second stage apply statistical model COP to choose the optimum alternative from the best alternatives in a shortlist. Proposed model for tendering system provides automated a decision-making process that reduces the time and manpower requirements for processing tender
Authors: Waled Alzober, Abdul Razak Yaakub
Abstract: Project management considers theme as the most vibrant and dynamic multi-disciplinary. Project management includes situations of decision making that are complex, thus the discerning methods to make a sound decisions are required. AHP has been used as a managerial decision tool in many industries. For most cases in project management, AHP has been used as a standalone methodology. In an attempt to extend the use of integrated AHP applications to areas that regarding to project management issues, this paper aims to introduce the integrated AHP application for dealing with project management issues. Combined AHP with some meta-heuristics approaches will be suitable to solve the problem related of the project management.
Authors: Johannes Boehner
Abstract: Establishing energy management in manufacturing major challenge means to increase the energy efficiency of machinery in existing and future processes leading to both, a reduction of energy costs as well as to a reduction of the manufacturing-process-related environmental impacts. Therefore we developed a procedure to prioritize existing machinery for detailed machine examination in order to create a sustainable approach for machine operating companies to prioritise its assets for energy optimisation projects. By using fuzzy logic as method of artificial intelligence nominal and utilisation machinery data as well as inhouse expert knowledge is considered to enhance multi criteria decision making both. Applying this methodology in a series of industrial case studies in discrete manufacturing costs savings of up to 40 percent were realised.
Authors: Ilanthenral Kandasamy, Florentin Smarandache
Abstract: Double Refined Indeterminacy Neutrosophic Set (DRINS) is an inclusive case of the refined neutrosophic set, defined by Smarandache (2013), which provides the additional possibility to represent with sensitivity and accuracy the uncertain, imprecise, incomplete, and inconsistent information which are available in real world. More precision is provided in handling indeterminacy; by classifying indeterminacy (I) into two, based on membership; as indeterminacy leaning towards truth membership (IT) and indeterminacy leaning towards false membership (IF). This kind of classification of indeterminacy is not feasible with the existing Single Valued Neutrosophic Set (SVNS), but it is a particular case of the refined neutrosophic set (where each T, I, F can be refined into T1, T2, ...; I1, I2, ...; F1, F2, ...). DRINS is better equipped at dealing indeterminate and inconsistent information, with more accuracy than SVNS, which fuzzy sets and Intuitionistic Fuzzy Sets (IFS) are incapable of. Based on the cross entropy of neutrosophic sets, the cross entropy of DRINSs, known as Double Refined Indeterminacy neutrosophic cross entropy, is proposed in this paper. This proposed cross entropy is used for a multicriteria decision-making problem, where the criteria values for alternatives are considered under a DRINS environment. Similarly, an indeterminacy based cross entropy using DRINS is also proposed. The double valued neutrosophic weighted cross entropy and indeterminacy based cross entropy between the ideal alternative and an alternative is obtained and utilized to rank the alternatives corresponding to the cross entropy values. The most desirable one(s) in decision making process is selected. An illustrative example is provided to demonstrate the application of the proposed method. A brief comparison of the proposed method with the existing methods is carried out.
Authors: S. Prasanna Venkatesan, S. Kumanan
Abstract: In recent years, supply chains have become increasingly vulnerable to risks resulting in poor financial performance and customer service. Managing the supply chain risks is a challenging task. Resilience and responsiveness based strategies are being attempted to build a robust supply chain. To select the appropriate mitigation strategies, supply chain risks are to be prioritized. Supply chain risk prioritization is a Multi Criteria Decision Making (MCDM) problem. MCDM models for supply chain risk prioritization needs attention. In this research, a hybrid Analytic Hierarch Process (AHP) and Preference Ranking Organization METHod for Enrichment Evaluation (PROMETHEE) approach is proposed for supply chain risk prioritization. A case example of a typical tractor industry is presented to illustrate the performance of the proposed approach.
Authors: Muhd Ridzuan Mansor, S.M. Sapuan, Edi Syam Zainudin, A.A. Nuraini, Arep Ariff Hambali
Abstract: Multi criteria decision making (MDCM) methods are amongst the approaches available in aiding composite designers to make the final decision especially during the material selection process where multiple solutions are present and various requirements are required to be satisfied simultaneously. Thus, in this paper, material selection process of thermoplastic matrix using MDCM methods for hybrid natural fiber/glass fiber polymer composites is presented. The aim is to identify the most suitable type of thermoplastic matrix to be used in the hybrid polymer composites formulation. The Weighted Sum Method (WSM) is applied in the selection process of seven candidate thermoplastic matrix materials based on the product design specifications. The overall analysis highlights that low density polyethylene (LDPE) is the preferred matrix for the intended application based on the highest scores obtained compared to other candidate materials. A signal-to-noise (S/N) ratio analysis was further performed to validate the initial selection results where LDPE once again outperformed other candidate materials with highest S/N ratio score in the non-compensatory approach.
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