Abstract This paper focuses on a comparative study of the machinability of two semi-crystalline polymers (POM-C) and (PA-6), during dry turning operations. The aim is to experimentally examine the impact of cutting parameters, namely cutting speed, feed, and depth of cut on surface roughness, cutting force, cutting power, and material removal rate. A series of experiments according to a Taguchi L18 plan was implemented. The ANOVA analysis revealed that the type of material a substantial effect on surface roughness, followed by feed, whereas cutting force and cutting power are more affected by depth of cut. Linear regression models with interactions proved effective in predicting the studied responses, and single-objective optimization using SA and GA methods were applied to optimize each response. The GRA and COPRAS methods coupled with weighting methods CRITIC, ROC, SWARA, and Entropy are used for multi-objective optimization of the considered responses. The results showed that the combination of the COPRAS method with the SWARA method provides a better compromise, which is of crucial interest for researchers in the field of optimization in polymer material machining.
