Modelling and experimental validation of surface roughness in precision turning of dual-phase materials considering process uncertainties

This paper presents the development and experimental validation of a model to predict the surface roughness generated during precision turning. In particular, in addition to the kinematic parameters of the turning process, the proposed model also takes into consideration the effects of the minimum chip thickness and elastic recovery together with uncertainties attributable to the blend nature of dual-phase materials. The aim of the model is to minimise the contribution of uncertainty errors due to the stochastic distribution of the phases present within the material microstructure, to better predict surface roughness under different cutting conditions. The developed model was experimentally validated by machining two different dual-phase materials, brass 6040 and medium carbon steel AISI 1045, under a range of processing parameters. The roughness of the generated surface was measured and compared with those predicted by the model for similar conditions. Preliminary results indicated that the trend of model’s predictions agreed relatively well with the experimental results. However, the proposed model was then experimentally calibrated and lower differences between measured and predicted values were obtained, these varied between 16.5 and 23.3%. If results obtained at very low feed rates were excluded, the average differences for brass 6040 were substantially reduced from 20.5 and 16.5 to 11.2 and 10.3%, using cutting tools with nose radii of 200 and \(400 \, {\upmu }\hbox {m}\), respectively. Similarly, when machining medium carbon steel AISI 1045 using 200 and \(400 \, {\upmu }\hbox {m}\) nose-radii cutting tools, the average differences decreased substantially, from 23.3 and 18.8 to 18.5 and 14.6%, respectively. Simulation-based study of the surface generation process in precision turning of dual-phase materials was conducted, and the results of the simulation trials have been utilised to optimise the cutting process.