The classical design of experiments (DoE) method can optimize systems with one technical response and multiple inputs. The objective of this study is to optimize multiple technical responses at the same time by integrating fuzzy logic transformation into a DoE system. The transformation from technical responses to the individual fuzzy responses and the overall fuzzy response are first defined, and the fuzzy response system is established. The method used to optimize the overall fuzzy response is introduced and discussed. The results show that the established fuzzy response system can optimize systems with multiple technical responses and multiple inputs.

For precision machining, the hard turning process is becoming an important alternative to some of the existing grinding processes. This paper presents an analytical model for predicting cutting forces in hard turning of 51CrV4 with hardness of 68 HRC. The cutting tool used is made from cubic boron nitride (CBN) with a wiper cutting edge. Formulas for differential chip loads are derived for three different situations, depending on the radial depth of cut. The cutting forces are determined by integrating the differential cutting forces over the tool-workpiece engagement domain. For validation, cutting forces predicted by the model were compared with experimental measurements, and most of the results agree quite well.