Decision-making approach for tribological optimization of self-lubricated hybrid composites

Purpose This study aims to investigate the tribological performance of 95% Al6061 reinforced with 4% B4C and 1% self-lubricated MoS2 in hybrid metal matrix composites fabricated via stir casting. Pin-on-disk experiments were conducted under varying loads, sliding velocities and temperatures to evaluate wear loss and coefficient of friction (COF). Design/methodology/approach To identify optimal operating conditions, a multicriteria decision-making strategy was adopted using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) alongside its fuzzy-based formulation, enabling comprehensive ranking of experimental trials. Findings In the fuzzy TOPSIS evaluation indicate that experimental tribological condition with normal load, sliding velocity and temperature having A5 (10 N, 1.25 m/s, 50 °C) achieved the highest overall coefficient value (0.7465), whereas experiment A2 recorded the lowest (0.0275). A comparative assessment revealed that fuzzy TOPSIS provided greater robustness by effectively incorporating uncertainty and subjective judgment, which are often overlooked by conventional crisp methods. In fuzzy TOPSIS compared to alternative A2, alternative A5 demonstrates a significant enhancement in tribological performance, with approximately 93.6% reduction in wear loss and 50.1% reduction in COF, confirming its superior wear and friction characteristics. These findings demonstrate that fuzzy TOPSIS serves as a more reliable decision-making tool for optimizing pin-on-disk test parameters. Originality/value This study presents a structured comparison between classical and fuzzy TOPSIS methodologies for the tribological optimization of self-lubricating Al6061/B4C/MoS2 hybrid composites, an area that has received limited attention in prior studies. The findings demonstrate that the fuzzy decision-making framework more effectively determines optimal test parameters, resulting in notable reductions in wear loss and frictional response. Such improvements enhance composite durability and performance reliability, with potential implications for environmentally sustainable engineering applications.

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Publication Details

Journal
Industrial Lubrication and Tribology
Published
2026-02-14
DOI
https://doi.org/10.1108/ilt-10-2025-0477
Primary Topic
Aluminum Alloys Composites Properties
Type
article
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article

Decision-making approach for tribological optimization of self-lubricated hybrid composites

Manoj Sahni, Deepali Chauhan
Industrial Lubrication and Tribology
Aluminum Alloys Composites Properties
article

Decision-making approach for tribological optimization of self-lubricated hybrid composites

Manoj Sahni, Deepali Chauhan
article en

Abstract

Purpose This study aims to investigate the tribological performance of 95% Al6061 reinforced with 4% B4C and 1% self-lubricated MoS2 in hybrid metal matrix composites fabricated via stir casting. Pin-on-disk experiments were conducted under varying loads, sliding velocities and temperatures to evaluate wear loss and coefficient of friction (COF). Design/methodology/approach To identify optimal operating conditions, a multicriteria decision-making strategy was adopted using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) alongside its fuzzy-based formulation, enabling comprehensive ranking of experimental trials. Findings In the fuzzy TOPSIS evaluation indicate that experimental tribological condition with normal load, sliding velocity and temperature having A5 (10 N, 1.25 m/s, 50 °C) achieved the highest overall coefficient value (0.7465), whereas experiment A2 recorded the lowest (0.0275). A comparative assessment revealed that fuzzy TOPSIS provided greater robustness by effectively incorporating uncertainty and subjective judgment, which are often overlooked by conventional crisp methods. In fuzzy TOPSIS compared to alternative A2, alternative A5 demonstrates a significant enhancement in tribological performance, with approximately 93.6% reduction in wear loss and 50.1% reduction in COF, confirming its superior wear and friction characteristics. These findings demonstrate that fuzzy TOPSIS serves as a more reliable decision-making tool for optimizing pin-on-disk test parameters. Originality/value This study presents a structured comparison between classical and fuzzy TOPSIS methodologies for the tribological optimization of self-lubricating Al6061/B4C/MoS2 hybrid composites, an area that has received limited attention in prior studies. The findings demonstrate that the fuzzy decision-making framework more effectively determines optimal test parameters, resulting in notable reductions in wear loss and frictional response. Such improvements enhance composite durability and performance reliability, with potential implications for environmentally sustainable engineering applications.

Industrial Lubrication and Tribology
Pandit Deendayal Energy University (IN)
Peace, Justice and strong institutions
Openalex Percentile: Top 56%
Aluminum Alloys Composites Properties
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