Multi-Objective Optimization of Material Removal Rate and Tool Wear in Rough Honing Processes

This study focuses on obtaining regression models for material removal rate and tool wear in rough honing processes. For this purpose, experimental tests were carried out according to a central composite design of experiments. Five different parameters varied: grain size or particle abrasive, density abrasive concentration, pressure the stones against cylinder internal surface, tangential speed (in case, corresponding rotation cylinder), linear head. In addition, multi-objective optimization was with aim maximizing minimizing wear. The results show that, within range studied, depends mainly speed, followed by pressure. Tool is directly influenced pressure, size. According optimization, if two responses are given same importance, it recommended that high size, density, low be selected. Linear has less influence both studied. If considered more preponderant than wear, then values should considered, except preponderant, lower 128 (ISO 6106) selected, approximately 166 min−1. other variables, would not change significantly from first situation.