Determination of Best Input Parameters for Internal Grinding SKD11 Tool Steel using MCDM

This article presents the results of an optimization study on the determination of the best input parameters for the internal grinding process when processing cylindrical-shaped parts of SKD11 tool steel. For this purpose, three Multi-Criteria Decision Making (MCDM) methods including the Evaluation based on Distance from Average Solution (EDAS), Multi-Attributive Border Approximation Area Comparison (MABAC), and Multi Attribute Utility Theory (MAUT) were used to solve the MCDM problem, while the entropy method was applied to find the criteria weights. Three objectives, namely the Surface Roughness (SR), Material Removal Rate (MRR), and wheel life (Tw), were also investigated. Six input factors, involving the coarse dressing depth (ar), coarse dressing times (nr), fine dressing depth (af), fine dressing times (nf), non-feeding dressing (n0), and dressing feed rate (Sd), were examined. Additionally, the Taguchi method with the L16 (44+22) design and the Minitab R19 program were deployed to design this study’s experiment and investigate its outcomes. The MCDM work was successfully solved and the best process factors are proposed.