Title: Optimisation of process parameters in solid lubricant (MoS2) assisted machining of AISI 1040 steel by response surface methodology
Authors: Rajeev Srivastava, R.K. Srivastava
Addresses: Department of Mechanical Engineering, Motilal Nehru National Institute of Technology, Allahabad, UP, India. ' Department of Mechanical Engineering, Motilal Nehru National Institute of Technology, Allahabad, UP, India
Abstract: The machining of materials has received substantial attention due to the increasing use of machining processes in various industrial applications. Machining leads to high friction between tool and work piece interface and can result in high temperatures, impairing the dimensional accuracy and the surface quality of products. The conventional machining has problem, like high machining zone temperature which may lead to poor surface quality. Machining fluids are applied in different forms to control such high temperature but they are partially effective within a narrow working range, recent studies also indicate their polluting nature. Solid Lubricant Assisted Machining (SLAM) is a novel concept to control the machining zone temperature without polluting the environment. In this study, the experimental set-up for the solid lubricant powder feeder arrangement is designed and fabricated on the lathe machine. The application of Response Surface Methodology (RSM) and Central Composite Design (CCD) for modelling the influence of operating variables on the performance of surface roughness during SLAM are studied. The mathematical model equations were developed for surface roughness using set of experimental data by computer simulation applying least squares method. The developed equations are third-order response functions representing surface roughness of AISI 1040 steel, as functions of four operating variables of SLAM. The predicted values of surface roughness were found to be in good agreement with experimental values for third order model when compared to second order model. The obtained coefficients of multiple regression (R2) values are 0.8686 and 0.9930 for second and third order model, respectively. The 3D response surfaces and contours were plotted using MATLAB7.0.1 with experimental data to obtain the desired set of process parameters within the operating range of process variables during SLAM of AISI 1040 Steel.
Keywords: SLAM; solid lubricant assisted machining; CCD; central composite design; RSM; response surface methodology; ANOVA; analysis of variance; approach angle; surface finish; process parameters; steel machining; mathematical modelling; simulation; surface roughness.
International Journal of Machining and Machinability of Materials, 2008 Vol.4 No.1, pp.111 - 128
Published online: 24 Oct 2008 *Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article