Selection of Crash-Box Manufacturing Process : Integration of Electre-Idat with Monte Carlo Simulation

Uncertainty plays an indispensable role in decision-making problems. Numerous criteria, such as time and costs, typically do not have exact values, leading the stakeholders to rely on indefinite information or data. This paper employed a set of techniques to deal with such uncertainties in the selection of manufacturing processes. The problem of selecting promising manufacturing processes and materials for automobile safety devices, as the case study of this study, has been considered an essential step of product development. The modified version of the ELECTRE-IDAT method, which can handle interval data, was employed in this paper; however, the skewness of the data inside the interval range reveals the need for additional supporting tools. The Monte Carlo simulation was accompanied by the ELECTRE-IDAT approach to give the decision-makers or designers more control over the data, whereas the majority of researchers rely on exact or precise data for their decision-making problems. In addition to considering the data for some criteria as an interval, Monte Carlo emphasized the part of the interval with the highest probability. The alternatives for the manufacturing process selection of the safety devices known as crash-boxes were a combination of two different designs with 12 process sets. Furthermore, cost, time, and the environment, as well as the product's structural performance, were evaluated as problem criteria.The ultimate solution (optimum) was the conical aluminum tube using a combination of casting and CNC machining. The Monte Carlo simulation was also able to apply more control over the input data, resulting in a slight variation in the final results. This paper presents a combination of Monte Carlo and an MCDM method to provide managers/designers greater control over uncertain data