Wear behavioral assessment of Al-CSAp-MMCs using grey-fuzzy approach. (July 2019)

• Record Type: Journal Article
• Authors: Siva Sankara Raju, ; Srinivasa Rao, G.; Samantra, Chitrasen
• Is Part Of: Measurement. Volume 140(2019)
• Page Start: 254
• Page End: 268
• Publication Date: 2019-07
• Subjects: Wear -- CSA -- Coefficient of friction -- GRG -- GFRG; Weights and measures -- Periodicals; Measurement -- Periodicals; Measurement; Weights and measures; Periodicals; 530.8
• DOI: 10.1016/j.measurement.2019.04.004
• Languages: English
• ISSNs: 0263-2241

Abstract

Graphical abstract: Highlights: Preparation of AMCs with coconut shell ash particles. Analyzed the tribological effects of Al-CSA composites. Development of correlation for GRG using statistical analysis. Uncertainty is handled by fuzzy-logic. Grey-Fuzzy Approach is used for optimizing the multiple responses. Abstract: This paper presents an optimization of the wear behaviour of aluminium metal matrix composites (AMC) reinforced with coconut shell ash (CSA) on pin-on-disc setup. The analysis is carried out with load (N), percentage (%) of CSA (% of volume) and sliding distance (m) which is considered as three process parameters; and wear (µm), wear rate (mm 3 /m) and coefficient of friction are taken as three measurable responses. A hybrid grey-fuzzy reasoning methodology has been adopted to optimize the multiple responses. Fuzzy logic concept has been used to handle the uncertainty that arises due to the physical variability of the process parameters. From the ANOVA test, it has been observed that load has the significant effect followed by sliding distance and % of CSAp to the overall wear behavioral performance. Thereafter, a confirmation test has been conducted to validate the optimal condition. Finally, the obtained results of proposed approach (GFRA) are compared with the results of desirability functional analysis (DFA), grey relational analysis (GRG) and fuzzy logic to check the reliability and consistency.