A decision support system for materials selection using proximity indexed value method

• Published in: Materials today : proceedings Vol. 66; pp. 2431 - 2437
• Main Authors: Ajith, S., Vikas Sharma, S., Bharath, N., Babu, Jalumedi, Balasubramanyan, R.
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 2022
• Subjects: Decision support system; Material selection; Proximity indexed value; Spearman rank correlation coefficient; Material selection; Proximity indexed value; Spearman rank correlation coefficient; Decision support system
• ISSN: 2214-7853; 2214-7853
• DOI: 10.1016/j.matpr.2022.06.341

The selection of a material plays a key place during the design stage and subsequent production. The decision of selecting the correct material can decrease the manufacturing cost and time. On the other hand, a wrong selection cause increases the production cost and time and may also cause poor performance. The selection of particular materials for a part/product depends on the properties of the material that match the product requirements. At present, there are a more expansive range of materials with diversified properties available, making this decision process crucial. The present study aims to evolve a decision support system for this tedious material selection process. However, literature presents several mathematical formulations and tools or techniques to aid this selection of materials decision-making process, each of these techniques have advantages and disadvantages. This study proposes an innovative approach, i.e., proximity index value, to solve two examples of real-world material selection issues for a gear material and material for load gearing wagon walls. A ranking sequence of materials by this proposed method compared with those obtained by other approaches presented in the literature for the validity of the proposed method. Results revealed that present method shows a higher rank correlation coefficient indicating the suitability of the proposed method. Hence this method can be used to aid the decision-making process for the material selection process.