Q-analysis in Materials Selection
Orchi Bhattacharyya, Shankar Chakraborty
Abstract
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Orchi Bhattacharyya, Shankar Chakraborty
Abstract
Open-access reader
The designers often face the problem of choosing the best fitted material for a specific application from a huge array of available alternatives while simultaneously fulfilling all the given design requirements.For dealing with the material selection problems, a systematic and efficient approach is thus necessary.Selection of an optimal material from among various alternatives based on different conflicting subjective as well as objective attributes can be defined as a typical multi-criteria decision-making (MCDM) problem.The material selection problems for diverse engineering applications have already been solved by the past researchers employing different MCDM approaches.In this paper, the feasibility of Q-analysis technique as an MCDM tool is explored for arriving at the most appropriate decision regarding materials selection.Its applicability is demonstrated with the help of four illustrative examples and its capability to provide almost accurate material selection decisions is also validated.
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The designers often face the problem of choosing the best fitted material for a specific application from a huge array of available alternatives while simultaneously fulfilling all the given design requirements.For dealing with the material selection problems, a systematic and efficient approach is thus necessary.Selection of an optimal material from among various alternatives based on different conflicting subjective as well as objective attributes can be defined as a typical multi-criteria decision-making (MCDM) problem.The material selection problems for diverse engineering applications have already been solved by the past researchers employing different MCDM approaches.In this paper, the feasibility of Q-analysis technique as an MCDM tool is explored for arriving at the most appropriate decision regarding materials selection.Its applicability is demonstrated with the help of four illustrative examples and its capability to provide almost accurate material selection decisions is also validated.
Key concepts: Multiple-criteria decision analysis, Selection (genetic algorithm), Material selection, Computer science, Management science, Risk analysis (engineering), Biochemical engineering, Operations research