Volume V, Issue I, January 2016 IJLTEMAS ISSN 2278 – 2540 www.ijltemas.in Page 39 A Review of Multiple Criteria Decision Making Tools N.Senthil Kannan 1 , D.Naveen Prasad 2 , R. Nirmal Kumar 2 , R.S.Premvishnu 2 1 Assistant Professor, 2 U.G Students, Department of Mechanical Engineering Sri Ramakrishna Engineering College, Coimbatore, Tamil Nadu, India. Abstract: Multiple-criteria decision making (MCDM) is a division of operations research that explicitly evaluates multiple criteria in decision making environment. In our day to day life there are typically multiple criteria that need to be solved in making decisions. Cost always stands first inthe criteriafor making decisions. Quality is the criterion that conflicts with the cost. Cost and customer satisfaction are the other two conflicting criteria. In management we are interested in getting high returns at the same time reducing our risk. The stocks that have potential of bringing high returns typically also carry a high risks of investment. Failure mode and effect analysis (FMEA) was one of the first systematic techniques for failure analysis. It was developed by an engineers in the late 1950s to study problems that may arise from miss using of military systems. FMEA is a first step of effectiveness study of a system. It involves in reviewing as many components and subsystem as possible for identifying the failure modes and their causes and effects. FMEA deals with the qualitative aspects of a system. Quality function deployment (QFD) is a tool to transform user demands from qualitativeinto quantitative parameters. QFD is designed to back up the planning process and to focus on features of a new product, market segments, and company or technology development needs. Key words: MCDM tools, FMEA, QFD I. INTRODUCTION MEA is an effective tool or methodology for the failure analysis and is the backbone in reliability, safety and quality engineering. Quality management and development process is primly concerned with a process type of FMEA. A FMEA analysis helps to sort out the potential failure modes. It is extensively employed in improvising industries in multiple phases in the life cycle of the product. Effects and analysis phase deals with the process of studying the concept of those failures on different grounds. Functional analyses are required as an input to correct failure modes at all the levels for functional FMEA. FMEA is used to catalyse the risk reduction based on the failure mode effect severity reduction and lowering the failure. The FMEA is the principle used in inductive analysis performed by understanding the failure mechanism. FMEA can also be used as a design phenomenon that can be employed in systematically analysing component failures and to find the consequences on the operations. The analysis is classified into two sub-analyses, the first phase is the FMEA and next stands the critical analysis. In thedevelopment process of FMEA the analyst may requireall the possible failure modes of the system, which is under analysis. FMEA can be carried out at the system, assembly, process and part level. FMEA should be properly documented before the hardware design process. FMEA can help in guiding decision making process. It is probably the most important consideration. In some case, the FMEA would be of low value where decision making process or the analysis is processed after the completion of hardware design or process. Once when the FMEA is performed considering all possible modes of failure, it is first and foremost benefit inthe early identification of all critical system for failure so they can be rejected or minimised through design modification in the beginning stages of the product development process, which means that the FMEA should be carried out in the system level as soon as the design information is available to the preliminary level of production, as design process continues. Quality function deployment (QFD) is a tool to transform user demands which are available in qualitative terms to quantitative terms, which can be easily interpreted, to deploy the functions affecting quality and to change the methods for achieving the design quality in subsystems in manufacturing process. QFD is designed to perform planners focus on characteristics of a new component from viewpoints of market and company segments that technology development is needed. The techniques which gives charts or graphs and matrices, with the assistance of the tools from fuzzy sets and their concepts can approximate data to a numeric precision. Traditional FMEA analysis has shortcomings which affects the risk evaluation process and the appropriate correct actions. It is very difficult to achieve very accurate results using traditional FMEA. The problem is solved by using RPN (risk priority number). It can be obtained or solved by different combination of three factors. So the fuzzy logics is used in the traditional FMEA. It can be applied to solve any type of problem. The rating factor is given as triangular fuzzy number and the relative importance among them O (occurrence), S (severity) and D (decision) is also a triangular number so that the new fuzzy FMEA method is introduced. II. LITERATURE REVIEW B. Almannai, et al(2008) developed an integrated approach for a manufacturing automation technologies involving QFD and FMEA. They used QFD to find the best manufacturing alternative and FMEA to identify the risks involved in the system design and during implementation. The stages involved linking of investments in automation based on evaluation criteria. This was computed using the QFD matrix. In the second stage, the alternative solution was selected by transforming the first QFD matrix to a second F