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Top1. Introduction
Material selection is one of the decision-making processes that take place in manufacturing organizations. It is a difficult and critical role in product development for the success and competitiveness of manufacturing organizations. The proper material selection for manufacturing can reduce manufacturing time, increase process efficiency, and thus increase productivity (Darji and Rao, 2014). Any improper material selection can have a negative impact not only on productivity but also on profitability and an organization's credibility (Chatterjee and Chakraborty, 2012). In reality, material selection is the process of selecting the best material for a product from a limited set of available materials based on specific criteria. There are numerous options and criteria that influence the material selection for a specific product.
The criteria typically include mechanical, physical, and electrical properties, as well as economic considerations for the materials. Material selection becomes a difficult and subtle task due to the availability of a large number of materials as well as complex relationships between various attributes for selection. For an engineering application, the material selection process entails selecting a material from two or more alternatives based on several criteria; thus, the material selection problem can be classified as a multi-criteria decision making (MCDM) problem (Athawale et al., 2011).
The current study uses TOPSIS to identify an appropriate carbon Fibre Reinforced Polymer (CFRP) material for underwater structural applications (technique for order preference by similarity to ideal solution). TOPSIS is quite capable and computationally easy to evaluate and select a suitable material under MCDM environment (Mousavi-Nasab, S. H., & Sotoudeh-Anvari, A. 2017). The calculation of weightages for criteria is an important task when using TOPSIS to select the best material. For identifying the best composite among the proposed CFRPS, six evaluation criteria were considered in this work: tensile strength, compression strength, flexural strength, impact strength, damping ratio, and ILSS. The part of data (impact strength, compression strength and damping ratio) of these properties are taken from published research article of Rao, Y. A. et al (2019) and remaining data (ILSS, tensile strength and flexural strength) from unpublished research work.
In order to obtain more suitable weights for the parameters, a compromised weighting approach was used in this study by considering subjective and objective weights of the criteria using the Analytic Hierarchy Process (AHP) and Shannon entropy techniques, respectively. AHP is an effective technique for dealing with performance-related issues (Shaout, A and Yousif, M. K. 2014) and for taking into account the views of various experts in the area. The weightages are calculated by the AHP using pair wise comparisons based on expert subjective opinions. The principal eigenvectors are used to calculate the weightages for the criterion. Despite the fact that AHP provides numerical priority vectors for material selection parameters, it has some flaws. The feedback for AHP implementation is mostly based on subjective judgement, which may or may not be effective or reliable for quantitative criteria where any amount of relevant data is available. In such cases, decision-makers need objectively weighted criteria based on relevant decision data.
Since it offers objective criteria weights, the Shannon entropy (SE) technique can be used to supplement the functions of AHP based on decision criteria categorization (Al-Aomar, 2010). Combining the AHP and SE methods can be able to compensate for the shortcomings of each approach while also defining a priority framework for material selection criteria. As a result, for the parameters, the current study uses synthesis weights, which are a mixture of weightages obtained from AHP and SE. The synthesis weights are also used in the TOPSIS method to determine the best CFRP material.
The rest of this paper is laid out as follows. The basic procedures of the MCDM techniques used in designing the proposed MCDM model are concisely outlined after a brief literature review on research using MCDM approaches for material selection.