Title: Optimisation of honing process parameters for reducing surface roughness and power consumption on grey cast iron (FG-260I)

Authors: Umesh Kumar Vates; Shubham Sharma; Varinder Kumar Mittal

Addresses: Department of Mechanical Engineering, Amity School of Engineering and Technology, Amity University, Uttar Pradesh, Noida – 201313, India ' Department of Mechanical Engineering, Amity School of Engineering and Technology, Amity University, Uttar Pradesh, Noida – 201313, India ' Department of Mechanical Engineering, Amity School of Engineering and Technology, Amity University, Uttar Pradesh, Noida – 201313, India

Abstract: Optimisation of cylinder liner surface characteristics is being done in honing process for (FG-260I) grey cast iron. Response surface methodology (RSM) and design of experiment (L54) has been used with six input variables to conduct the experiments. The parameters influencing the surface finish and corresponding power consumptions were selected on the basis of available extent literature. Second order RSM approach has been applied to develop a suitable model in honing process having six inputs and single output parameters (R_a). The significant effect of input parameters on surface roughness with corresponding power consumptions has been analysed using combined effort of RSM modelling and analysis of variance (ANOVA). The RSM modelling for the honing process on FG-260I gives significant correlation coefficient (R²) of 96.7% and adjusted correlation coefficient (R_adj)2 96.5 %. The minimum surface roughness has been found by optimal parametric combinations using root mean square error (RMSE) approach. The optimised process parameters will yield acceptable surface finish at least power consumption.

Keywords: honing process; surface finish; FG-260I; response surface methodology; RSM; analysis of variance; ANOVA; root mean square error; RMSE; optimisation; process parameters; surface roughness; surface quality; energy consumption; grey cast iron; cylinder liner surfaces; design of experiments; modelling.

DOI: 10.1504/IJASMM.2017.082987

International Journal of Additive and Subtractive Materials Manufacturing, 2017 Vol.1 No.1, pp.67 - 81

Received: 04 Jan 2016
Accepted: 02 Sep 2016
Published online: 17 Mar 2017 *