Development of a hybrid meta-model for material selection using design of experiments and EDAS method

Selection of materials for a specific application is one of the extremely demanding problems in a synchronised manufacturing environment as it directly determines perceptible quality and cost of the product. Material selection is a complex process, intending to choose the best material while satisfying a pre-decided set of requirements. Material selection decision is made during preliminary product design stage. An improperly chosen material leads not only to an early component failure but also to a redundant cost involvement. There are numerous materials and various criteria influencing the material selection process for a particular application. Although a good amount of multi-criteria decision-making (MCDM) methods are available to deal with this type of selection applications, this paper aims to propose a hybrid method of design of experiments (DOE) and evaluation based on distance from average solution (EDAS) to solve material selection problems in current industrial applications. DOE and EDAS are used jointly to determine the critical material selection criteria and their interactions by fitting a polynomial to the experimental data in a multiple linear regression analysis. A gear material selection problem is demonstrated to establish the application competence of the DOE-EDAS method. Application results were validated with the results of the previous researchers and they indicate that the proposed DOE-EDAS hybrid model is straightforward, robust and practical in solving complex MCDM problems.

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Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).