Optimization of Tribological Properties of Shot-Peened Surfaces via Multi-Criteria Decision-Making Using TOPSIS and GRA

The article presents a comparative analysis of experimental results from tribological tests conducted using a ball-on-disc system, applying two multi-criteria decision-making methods: Grey Relational Analysis (GRA) and TOPSIS (Technique for Order Preference by Similarity to Ideal Solution). The aim of the study was to identify the most advantageous combinations of input parameters-load, sliding speed, and sliding distance-while simultaneously evaluating three output criteria: volumetric wear (VD), coefficient of friction (CoF), and weight loss (WL). The analysis covered 27 test variants, with different weighting factors assigned to each criterion to reflect their practical significance (0.35 for VD, 0.45 for CoF, and 0.2 for WL). The results obtained using the GRA method showed good agreement with the TOPSIS rankings in identifying the best-performing variants, although differences were observed due to the distinct algorithms used to evaluate trade-offs. The optimal solutions were characterized by low wear, a low coefficient of friction, and minimal weight loss. The study demonstrates the effectiveness of both methods for tribological analysis and suggests that their combined use can serve as a robust tool for optimizing the operating conditions of friction nodes.