Robust weighting applied to optimization of AISI H13 hardened-steel turning process with ceramic wiper tool: A diversity-based approach

A mixed ceramic is a type of cutting-tool material widely employed for machining hardened steels. The usage of a mixed ceramic along with a wiper geometry can help double the feed rate, thereby increasing productivity while keeping the surface roughness (Ra) as low as possible. Analyses of manufacturing processes, such as a machining process, show that the various possible controlled parameters can be modeled by multiobjective mathematical models to ensure their optimization. Hence, the aim of this study was optimize a hard turning process using a robust weighting based on diversity to choose the final Pareto optimal solution of the multiobjective problem. The responses of the material removal rate (MRR), Ra parameter, and cutting force (Fc) were modeled by using the response surface methodology; in this methodology, decision variables, such as the cutting speed (Vc), feed rate (f), and depth of cut (d), are employed. The diversity index, as a decision-making criterion, proved to be useful in mapping the regions of minimum variance within the Pareto optimal responses obtained in the optimization process. Hence, the study demonstrates that the weights used in the multiobjective optimization process influence the prediction variance of the obtained response.