ANALYSIS AND OPTIMIZATION OF PARAMETER AFFECTING BORE DEVIATION IN BORING PROCESS

This investigation applies a full factorial orthogonal table, integrating response surface methodology (RSM) to optimize parameters of a finish boring process using a computer numerical control (CNC) machine VA-50 for the finishing operation of engine crank case tappet bore. The main scope of this research work is to study the effects of various operational parameters like cutting speed, feed rate and cutting allowance on bore diameter of engine crankcase tappet bore. It is found that with the increases of cutting speed and feed the bore deviation (BD) decreases. The result of the experiment then was analyzed using DESIGN EXPERT (DOE) 9.0 software. This was done by using the FULL FACTORIAL technique with optimal (custom) design and ANOVA analysis. In this study, randomization of the run order to be carried out and analysis sequences were carried out according to the run order by Design Expert software. Full factorial with optimal design of three factors with two factor have three levels and one factor has two level was conducted which consist of 18 runs. The machining responses that were analyzed is Bore deviation (BD).All data obtained were then used as input to the Design Expert software for further analysis, according to steps outline for full factorial design. As speed and feed increased a decrement of Bore deviation approximately 40 % was observed. By applying RSM analysis, the predictive mathematical model of the bore deviation average was developed in terms of the cutting speed, feed rate, and cutting allowance. The error analysis and experimental results indicate that the proposed predictive mathematical models could adequately describe the performance indicators within the limits of the factors that are being investigated. In addition, the analysis of variance (ANOVA) was implemented to identify the significant factors and the response surface contours were constructed for determining the optimum conditions of finish boring processes using CNC machine operations

EMPIRICAL MODELING OF SURFACE ROUGHNESS AND METAL REMOVAL RATE IN CNC MILLING OPERATION

Surface finish and material removal rate are two important factors in the manufacturing organization which affect acceptability of the product which in turn reflects on the profitability of the organization. Ability of the production setup to produce the components with high material removal rate without sacrificing the surface requirements can play vital role in sustainability and profitability of the organization. In this paper, the effect of process parameters on metal removal rate and surface roughness has been investigated in milling of SAE52100 tool steel. Cutting speed, feed and depth of cut have been taken as input factors in three level full factorial orthogonal arrays used for experimentation. Mathematical models have been developed using response surface methodology to predict surface finish, and metal removal rate in term of machining parameters.  Depth of cut and feed rate are found to be a dominant parameter for surface roughness; whereas feed rate mainly effects the metal removal rate. The results of mathematical models have been compared with the experimental and found to be in good agreement. The results of predicted model can be used in selection of process parameters to insure desired quality and improved productivity