Optimization of Process Parameters of Surface Roughness and Material Removal Rate in Orthogonal Turning of AISI 1045 Carbon Steel Using Taguchi Technique

O G Ehibor ,Blessıng Ngozı Goodluck Aliemeke

doi:10.7176/iel/11-1-03

Abstract

In today’s manufacturing market, quality and productivity play significant role. This study is aimed at evaluating the best process environment which could simultaneously satisfy requirements of both quality and as well as productivity. This study investigates the effects of various parameters such as depth of cut, speed and feed on the material removal rate and surface roughness in a HMT (Hindustan Machine Tools) LB25 Lathe Machine. A plan of experiments based on Taguchi’s technique has been used to acquire the data. An orthogonal array, the signal to noise (S/N) ratio and the analysis of variance (ANOVA) were employed to investigate the cutting characteristics of 1045 carbon steel using tungsten coated carbide cutting tool. The effectiveness of the predicted values with the experimental values in the analysis was carried out by confirmation tests. The analysis of results shows that the combination of process parameters for minimum surface roughness is obtained at 330 rpm spindle speed, 0.2 mm/rev feed and 0.6mm depth of cut for minimum surface roughness. It is observed that feed rate plays an important role in minimizing surface roughness. For maximum material removal rate, the optimum values are spindle speed of 630 rpm, feed rate of 0.4 mm/ rev and depth of cut of 1.0 mm. Finally, the relationship between cutting parameters and responses were developed by using the Minitab 18.1 software and regression equations were developed. Keywords :Taguchi, ANOVA, Signal to Noise Ratio, Minitab and Surface Roughness. DOI: 10.7176/IEL/11-1-03 Publication date: May 31 st 2021

Highlights

Machining is one of the most important and widely used manufacturing processes in engineering industry
Today, increasing the productivity and the quality of the machined parts in terms of workpieces dimensional accuracy, good surface finish, less tool wear on the cutting tools, high metal removal rate and economy of machining in terms of time per component, cost per component and the performance of the product are the main challenges of metal cutting industry during machining process(Das et al, 2012)
Most researches on machining show that the most widely considered machining performances by researchers are surface roughness, tool life, good cutting temperature followed by machining/production cost and material removal rate (Yusupet al, 2012).The focus of this study is to develop a statistical model for using the main cutting parameters of cutting speed, feed rate and depth of cut on 1045 carbon steel workpiece

Summary

Introduction

Machining is one of the most important and widely used manufacturing processes in engineering industry. A manufacturing engineer or machine setup technician is often expected to utilize experience and published shop guidelines for determining the proper machining parameters to achieve a specified level of different response parameters. In this situation, it is prudent for the engineer or technician to use past experience to select parameters which will likely yield an optimum response, and perhaps make some parameters adjustment as time allows or quality control requires. Today, increasing the productivity and the quality of the machined parts in terms of workpieces dimensional accuracy, good surface finish, less tool wear on the cutting tools, high metal removal rate and economy of machining in terms of time per component, cost per component and the performance of the product are the main challenges of metal cutting industry during machining process(Das et al, 2012)

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