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The IUP Journal of Mechanical Engineering

Machining Parameters Optimization of AISI 4340

Article Details

Pub. Date	:May, 2019
Product Name	: The IUP Journal of Mechanical Engineering
Product Type	: Article
Product Code	: IJME31905
Author Name	: Jignesh Khara, Manojkumar V Sheladiya and G D Acharya
Availability	: YES
Subject/Domain	: Management
Download Format	: PDF Format
No. of Pages	: 22

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Abstract

The paper focuses on the experimental assessment of the machinability aspects (surface roughness (Fa), cutting forces (Fc) and temperature (T)) while turning AISI 4340 alloy steel utilizing carbide tools. Optimization of machining parameters that have an impact on machinability aspects is exceptionally valuable to reduce production cost and time for machining part at the required surface quality. The experimental study is based on Design of the Experiment (DoE) using general full factorial approach and analyzes the parameters that influence the response variables. Analysis of Variance (ANOVA), regression analysis and Gray Relational Analysis (GRA) are employed to study the effects, significance, percentage contribution, modeling and optimum setting of the given process parameters.

Description

The physical properties of the workpiece material have a straight effect on the machinability of a workpiece material. Operating parameters, tool material, tool geometry and workpiece requirements have indirect influence on machinability and can often be used to overcome difficult conditions presented by the workpiece material. The selection of process parameters plays a crucial role in product quality, cost of production and times of production. The quality of the product and cost are much close to tool life, surface finish and cutting temperature and forces of cutting, which are machinability aspects and process parameter functions. A comprehensive grasping of variables or factors affecting machinability helps in the selection of workpiece designs, cutting tool material and in achieving the most favorable machining combination critical to maximum productivity (George, 2001).