Determination of an efficient power equipment oil through a multi-criteria decision making analysis

Abstract

Introduction/purpose: Several studies in the area of the development of nanofluids for power equipment have left a gap unfilled as to how to determine the best oil among the produced oils for power equipment application. Therefore, this study presents a multi-criterial decision making analysis to determine the best oil for power equipment. Methods: The Grey relational analysis (GRA) and the Probability based multi-objective optimization techniques were employed as the multi-criterial decision making analytical tools for the optimization. Dielectric strength, dielectric loss, viscosity, and flash point were analyzed as multiple performance characteristics of different oils, after which different oil candidates were ranked based on their performance. Results: Interestingly, the GRA and the Probability based multi-objective optimization techniques revealed that Jatropha oil + Neem nanofluid is the best oil candidate for power equipment and it is better than conventional mineral oil. The Probability based multi-objective optimization technique places Jatropha nanofluid over mineral oil, but not for the GRA technique. Also, mineral oil and ordinary Jatropha nanofluids are at a competitive level. Meaning, if Jatropha nanofluid is further worked on, it can beat mineral oil. Conclusion: The two techniques substantially established that when Jatropha oil is mixed with Neem oil together with nanoparticles, there will be better power equipment performance compared to mineral oil. It can be recommended that a further analysis should be conducted in the area of direct application of Jatropha + Neem nanofluid for power equipment to understand the overall behavior of power equipment compared to the conventional mineral oil