Surface roughness prediction in the turning of high-strength steel by factorial design of experiments

This paper discusses the development of surface roughness prediction models for turning EN 24T steel (290 BHN) utilising response surface methodology. A factorial design technique has been used to study the effects of the main cutting parameters such as cutting speed, feed, and depth of cut, on surface roughness. The tests have been carried out using uncoated carbide inserts without any cutting fluid. A first-order prediction model within the speed range of 36-117 m min(-1) and a second-order model covering the speed range of 28-150 m min(-1) have been presented. The results reveal that response surface methodology combined with factorial design of experiments is a better alternative to the traditional one-variable-at-a-time approach for studying the effects of cutting variables on responses such as surface roughness and tool life. This significantly reduces the total number of experiments required. (C) 1997 Elsevier Science S.A.