Multiresponse Tribological Ranking Alternatives of Al–Cu Alloys via an Integrated Taguchi Experimental Design, <scp>AHP</scp> Weighting, and <scp>WASPAS</scp> Decision Framework

ABSTRACT This study aims to optimize Al–Cu alloy compositions and tribological parameters to enhance wear performance using a hybrid multicriteria decision‐making framework. Al–5Cu (wt.%) alloys were fabricated via die casting and evaluated under pin‐on‐disc conditions with varying normal loads, sliding speeds, sliding distances, and lubrication types. A hybrid Taguchi–AHP–WASPAS methodology was applied to integrate design of experiments, expert‐weighted prioritization, and multiresponse ranking into a comprehensive optimization workflow. Trial 8 (900 N, 5 m/s, 15 m, grease) delivered the best performance, with the lowest wear rate (0.0037 mm 3 /N·m), COF (0.21), and material loss (15.32 mg), along with reduced frictional force (106.7 N), wear scar diameter (0.29 mm), and temperature rise (37°C). Trial 2 (500 N, 5 m/s, 30 m, synthetic oil) recorded the worst performance, with a wear rate of 0.0039 mm 3 /N·m, COF of 0.22, and material loss of 15.8 mg. Compared to the average of all nine trials, Trial 8 showed improvements: wear rate reduced by 29.2%, COF by 20.2%, material loss by 29.4%, frictional force by 44.0%, wear scar diameter by 16.7%, and temperature rise by 24.2%. The study is limited to specific Al–Cu alloy compositions and test conditions; findings may not extend to all loading or lubrication regimes. The optimized Al–Cu system offers a cost‐effective and durable solution for automotive, aerospace, and mechanical applications requiring enhanced wear resistance and friction stability. This work introduces an integrated multicriteria optimization framework combining Taguchi design, AHP, and WASPAS, offering a comprehensive approach to improving tribological performance under realistic operating conditions.