Selection of engine oil using multi-attribute decision-making methods

Akash Salunke, Ajit Lokhande, Akash Neharkar, Rupesh Satpute and Avinash Kamble

International Journal of Industrial and Systems Engineering, 2022, vol. 42, issue 1, 96-117

Abstract: The role of internal combustion engines in automobile industry has already been well recognised. It is made with closer precisions thus involve higher costs and also, it is crucial to ensure efficient working of its various components. Engine oil of specific grades is used for reducing wear and tear of components and cooling of parts of the engine. Choice of appropriate engine oil for engines is critical task for designers. Designers need to identify oils with specific properties and functionalities in order to fulfil end requirements and desired functionalities of the engine. The different oils possess different properties. Systematic approach must be used for selection of oil. Thus, the present work focuses on the selection procedure for best engine oil using four criteria selected by using multi-attribute decision-making method. The proposed methods help to evaluate and rank different engine oils in order to assist the decision maker in selecting appropriate engine oil.

Keywords: multi-attribute decision-making method; engine oils selection; preference ranking organisation method for enrichment evaluation; additive ratio assessment method; organisation rangement et synthese de donnes relationnelles method; elimination and choice translating reality method; analytical hierarchy process. (search for similar items in EconPapers)
Date: 2022
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