Multi-criteria decision-making approach for selection of nano-additives in tribological applications using TOPSIS and SAW methods

The choice of appropriate nano additives for tribological purposes has many factors and requirements to be met. These include: lower friction; better wear properties; formation of protective tribofilms; good dispersibility in lubricant; and good thermal oxidation stability. In this paper, an MCDM (Multi-Criteria Decision Making) framework is presented for evaluating/ranking different types of nano additives used in the tribological field. Specifically, MoS₂, WS₂, MoO₃, TiO₂, Al₂O₃, SiO₂, and glycerol were evaluated. To select the best nano additive, a comparison was made with each other based on how close they came to the "ideal" solution. This comparison was done using the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution). 

A decision matrix was prepared from published experimental data. Then, after normalizing each criterion and assigning weights to each one, the results were ranked. Finally, to validate the rankings obtained from the TOPSIS analysis, a second decision-making technique called SAW (Simple Additive Weighting) was applied. The rankings from both decision-making techniques were consistent and confirmed the effectiveness of the multi-criteria decision-making approach. From the TOPSIS analysis, it could be concluded that MoS₂ achieved the greatest value for closeness to the "ideal" solution which indicates that MoS₂ exhibited the most favorable behavior when considering all criteria. Additionally, it appears that MoO₃ and WS₂ will serve as possible candidates for use in future studies or as substitutes in certain applications where high temperatures and/or heavy loads exist.