Optimization of tribological performance of TiB2-reinforced Al6063 composite using grey-fuzzy tool

Author:

Bhowmik Abhijit12ORCID,Bhattacharjee Biplab3ORCID,Adewale Akinwande Abayomi4ORCID,Majumder Prasanta5,Giri Jayant6,Satish Kumar P7,Katiyar Jitendra Kumar8ORCID

Affiliation:

1. Department of Mechanical Engineering, Dream Institute of Technology, Kolkata, India

2. Chitkara Centre for Research and Development, Chitkara University, Pinjore, Himachal Pradesh, India

3. Centre for Additive Manufacturing, Chennai Institute of Technology, Kundrathur, Tamilnadu, India

4. Department of Metallurgical and Materials Engineering, Federal University of Technology Akure, Akure, Ondo State, Nigeria

5. Department of Autotronics, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Chennai, Tamil Nadu, India

6. Department of Mechanical Engineering, Yeshwantrao Chavan College of Engineering, Nagpur, Maharashtra, India

7. Department of Mechanical Engineering, Rathinam Technical Campus, Coimbatore, Tamilnadu, India

8. Centre for Research Impact and Outcome, Chitkara University, Rajpura, Punjab, India

Abstract

The utilization of TiB2 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% TiB2. 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.

Publisher

SAGE Publications

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