Application and comparative study of new optimization method for performance ranking of friction materials. (February 2018)

• Record Type: Journal Article
• Authors: Mahale, Vishal; Bijwe, Jayashree; Sinha, Sujeet
• Is Part Of: Proceedings of the Institution of Mechanical Engineers. Volume 232:Number 2(2018:Feb.)
• Page Start: 143
• Page End: 154
• Publication Date: 2018-02
• Subjects: Multiple criteria decision model -- extension evaluation method -- multiple objective optimization on the basis of ratio analysis -- friction materials; Tribology -- Periodicals; 621.89
• DOI: 10.1177/1350650117708479
• Languages: English
• ISSNs: 1350-6501

Abstract

Good friction materials should satisfy diverse and contradictory performance requirements such as adequate friction ( µ ≈ 0.35–0.45), resistance to wear, fade, squeal, judder, etc. in consort with good recovery and less noise producing tendency. To achieve center point of all these conflicting criteria and selection of best overall performing friction material is multiple criteria decision making (MCDM) problem and very difficult task. Decision maker can easily make decision with single criteria without the help of any optimization tool by maximizing beneficial criteria and minimizing non-beneficial criteria. However, it is extremely challenging task if decision making involves several number of conflicting criteria. Few techniques are reported in the literature such as 'multiple criteria decision model', 'Multi-attribute decision model', 'extension evaluation method' (EEM), etc. for performance ranking of friction materials. However, the simplicity, reliability, applicability, time devoted for the analysis, etc. are always most important aspects of selecting a right tool for the analysis. In this paper application of a technique 'multiple objective optimization on the basis of ratio analysis' (MOORA) has been first time employed for performance ranking of friction materials. A comparative study of MOORA and currently used methods MCDM and EEM are also presented. MOORA proved to be the best tool based on the criteria such as simple to use, fast, flexible, and efficient one.