Multi-criteria decision making (MCDM) is a research area that entails analyzing various available options in a situation involving social sciences, medicine, engineering, and many other fields. This is due to the fact that it is used to select the best solution from a set of alternatives. The MCDM methods have been applied not only in economics, medicine, transportation, and the military, but also in mechanical processing processes to determine the best machining option. In this study, determining the best dressing mode for external grinding SKD11 tool steel using an MCDM method—the MABAC (multi-attributive border approximation area comparison) method—was introduced. The goal of this research is to find the best dressing mode for achieving the minimal surface roughness (RS), the maximum wheel life (T), and the minimal roundness (R) all at the same time. To perform this work, an experiment was carried out with six input parameters: the fine dressing depth, the fine dressing passes, the coarse dressing depth, the coarse dressing passes, the non-feeding dressing, and the dressing feed rate. In addition, the Taguchi method and an L16 orthogonal array were used to design the experiment. Furthermore, the MEREC (method based on the removal effects of criteria) and entropy methods were used to determine the weight of the criteria. The best dressing mode for external cylindrical grinding has been proposed based on the results. These findings were also confirmed by comparing them to the TOPSIS (technique for order of preference by similarity to ideal solution) and MARCOS (measurement of alternatives and ranking according to compromise solution) methods.
This paper introduces a novel approach to deal with the multi-objective optimization of a two-stage bevel helical gearbox by applying the Taguchi method and Grey Relation Analysis (GRA). The goal of the study is to find optimal main design factors that minimize the gearbox volume and maximize the gearbox efficiency. To accomplish this, five main design parameters were selected: the coefficients of wheel face width (CWFW) of the bevel and the helical gear sets, the allowable contact stresses (ACS) of the first and the second stages, and the gear ratio of the first stage. Furthermore, two single targets were investigated: minimum gearbox volumes, and maximum gearbox efficiency. Also, the multi-objective optimization problem is solved through two steps: Step 1 for closing the gap between variable levels and Step 2 for determining the optimal main design factors. The study’s findings were used to introduce the optimum values of five major design parameters for designing a two-stage helical gearbox.
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