Gear material selection with uncertain and incomplete data. Material performance indices and decision aid model

Abstract

First, a set of major gear design criteria are used to develop six material performance indices for material selection purposes. They are, a surface fatigue limit index, a surface fatigue lifetime index, a bending fatigue limit index, a bending fatigue lifetime index, an abrasive wear index, and a machinability index. A modified decision matrix in the presence of data uncertainties and incompleteness is then proposed to show the effect of the developed indices. It is shown that using individual material properties and approximations among them may not satisfy specific design goals for a specific application. Next, the ELECTRE III multiple criteria decision aid (MCDA) model is applied to rank the best compromised candidate materials, while considering criteria tradeoffs, designers’ preference information, data uncertainties and incompleteness. An effort is made to reconcile mathematically motivated model thresholds (namely, the indifference, strict preference, and veto thresholds) with experimentally motivated characteristics such as upper and lower limits of measured material properties. It is shown that the proposed multi-criteria approach may also be useful in revealing incomparable and/or indifferent alternatives that would not be distinguishable otherwise. To ensure rank stability of the chosen materials, the effect of potential uncertainties in designers’ opinions during criteria weighting is introduced by means of a dilation and concentration sensitivity analysis process. The main originality lies in resolving a non-compensatory, application-specific, and uncertainty-based multiple criteria material selection problem in gear design optimization.