Empirical modeling of surface roughness in turning process of 1060 steel using factorial design methodology

Surface quality is of great importance for the functional behavior of mechanical parts. Surface roughness in addition to tolerances imposes one of the most critical constrains for cutting parameters selection in manufacturing process planning. Productivity for the finish turning can be improved by optimal selection of related parameters. The attempt of this study is to develop an imperial model with the use of response surface methodology that is widely adapted tool for the quality engineering field. The established predictive model shows that the feed rate was found to be main influencing factor on the surface roughness. It is increased with increasing the feed rate. But decrease with increasing cutting speed. The results for analysis of variance show that the first order term of depth of cut is not significant. But the first order term of cutting speed and feed rate are significant. © 2007 Asian Network for Scientific Information.