High temperature sliding wear performance of 3D printed biocomposites: An integrated mathematical approach for optimal material selection

Five different types of alternatives as biocomposites were developed by reinforcing fruit waste-derived biofillers namely, banana (Musa spp.) peel powder in varying proportions of 0, 5, 10, 15 and 20 (wt.%) with polylactic acid (a biopolymer). The workability of the biocomposites varies irregularly with compositions making optimal material selection difficult task. The research aimed to develop a multi-criteria decision making based mathematical model for optimal materials selection of 3D biocomposites. Therefore, the research developed Triangular Fuzzy Weighted Bonferroni Mean Operator (TFWBMO) based integrated Analytic Hierarchy Process (AHP) - Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) model for ranking of 3D-printed biocomposites. The developed biocomposites were intended for tribological applications therefore, coefficient of friction ( C1 ), glass transition temperature ( C2 ), melting point ( C3 ), specific wear rate ( C4 ), and surface roughness ( C5 ) were considered as criteria. The integrated TFWBMO-AHP method has identified the criteria C1 and C4 as the most and least significant, respectively. Furthermore, the alternative A5 has demonstrated a minimum coefficient of friction of 0.149 for the most significant non-beneficial criteria C1 having an optimal weightage of 0.4709. The comparative analyses of the ranking results against well-known multi-criteria decision-making techniques has verified the reliability and accuracy of the proposed mathematical model. The good Spearman's rank correlation coefficient (r_s) ranges of 0.8 to 1 has verified the robustness of the proposed approach.