灰色关联分析
粒子群优化
模糊逻辑
复合数
材料科学
摩擦学
计算机科学
人工智能
冶金
复合材料
数学
机器学习
统计
作者
Abhijit Bhowmik,Biplab Bhattacharjee,P. Satishkumar,Prasanta Majumder,Jayant Giri,Praveen Kumar,Jitendra Kumar Katiyar
标识
DOI:10.1177/13506501241246845
摘要
The utilization of TiB 2 particle reinforcement in aluminium matrix composites, particularly with Al6063, has been explored in this study for its resilience to mechanical erosion, low oxidation rate, and excellent heat conductivity. The composite was produced using stir casting with 9 wt% TiB 2 . The investigation focuses on wear behaviour, examining three key process parameters such as load, sliding speed, and covering sliding distance across four settings to identify the optimal combination for achieving a favourable wear rate. Statistical analysis of variance reveals significant differences among the tested parameters. Conclusively, the study highlights the superiority of the grey-fuzzy approach over a simple grey relational grade in validating decision-making for wear performance attributes. The research identifies the ost significant grey relational grade and grey fuzzy grade values as 0.913 and 0.902, respectively. These values correspond to optimal operating conditions, specifically a 15 N load, a sliding speed of 15 m/s, and a sliding distance of 1200 m. The findings underscore the efficacy of the grey-fuzzy technique in authenticating decision-making processes related to wear performance characteristics, emphasizing its superiority over relying solely on a plain grey relational grade.
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