This paper depicts the experimental study the input parameters of EDM i.e. current, pulse on time and pulse off time on output parameters material removal rate (MRR), tool wear rate (TWR) and surface roughness (SR). The workpiece materials selected was AISI D2. The aluminium used as tool electrode and EDM oil as dielectric fluid. Taguchi, method was used to perform experiments, L9 orthogonal array was applied using MINITAB software. Signal to Noise (S/N) ratio and ANOVA were employed for parameter optimization and to achieve max MRR, min SR and TWR. The results indicate that the most prompting factor for MRR is Pulse off time. For TWR, the most influencing factor is current. For SR, the most prompting factor is pulse on time. Optimization is done by using Taguchi method on MINITAB 17 software.
Table of Contents
1. Introduction
2. Workpiece and Electrode Material
3. Evaluation of parameters
3.1 Evaluation of MRR
3.2 Evaluation of TWR
3.3 Signal to noise (S/N) ratio
4. Design of Experiments
5. Results and Discussions
6. Conclusion
Research Objectives and Themes
The primary objective of this research is to experimentally investigate the effects of varying input parameters—specifically current, pulse on time, and pulse off time—on the performance characteristics (MRR, TWR, and SR) of an AISI D2 steel workpiece when machined via Electric Discharge Machining (EDM) using an aluminium electrode.
- Application of the Taguchi method and L9 orthogonal array for experimental design and parameter optimization.
- Evaluation of material removal rate (MRR) based on weight loss during the machining process.
- Analysis of tool wear rate (TWR) using copper and aluminium electrode performance comparisons.
- Determination of optimal machining parameters to maximize MRR while minimizing surface roughness (SR) and TWR using MINITAB 17 software.
Excerpt from the Book
1. Introduction
Electric Discharge Machine (EDM) is a non-traditional machining process. It has number of applications in die making, punches and molds industry. It also finds application in manufacturing of finished parts in automobile, also in manufacturing of surgical components. In EDM, electric spark is produced between workpiece and electrode and due to this spark material gets eroded from workpiece and tool electrode [1]. So this process can be successfully employed to materials which are electrically conductive. Hardness, shape, toughness and brittleness don’t cause any restrictions [2]. In die sinking EDM, the shape which is to be produced on workpiece, the tool should be replica of that shape. Both tool electrode and workpiece are dipped in a dielectric fluid like EDM oil, Kerosene etc. The workpiece and electrode are placed at a very close distance and it depends on operating conditions and called as spark gap [3]. Modern era of EDM, i.e. from 1995 to till date. Many new aspects has been developed, namely micro-machining by EDM and dry EDM i.e. EDM without dielectric fluid. Now a days EDM is most acceptable technique for MRR [3]. For micro machining, ultrasonic vibration method is apt, dry machining is economical and water EDM is safe and conductive working environment, Powder mixed EDM is concerned more on improving surface quality [4]. The viability of machining Tungsten carbide ceramics by EDM with a graphite electrode using Taguchi method is studied and concluded that the current mainly effects the EWR and SR. The pulse duration is the most influencing factor for MRR [5].
Summary of Chapters
1. Introduction: Provides an overview of the EDM process, its industrial applications, and a literature review on various machining parameters and their effects on workpiece materials.
2. Workpiece and Electrode Material: Details the chemical composition of AISI D2 steel and discusses the physical properties of the aluminium electrode utilized in the study.
3. Evaluation of parameters: Defines the mathematical formulas used to quantify material removal rate (MRR), tool wear rate (TWR), and the logic behind the Signal-to-Noise (S/N) ratio calculations.
4. Design of Experiments: Describes the implementation of the Taguchi technique, specifically the use of an L9 orthogonal array and the selection of three control parameters at three distinct levels.
5. Results and Discussions: Presents the analysis of the experimental data through main effects plots for S/N ratios and means to determine the optimal machining conditions.
6. Conclusion: Summarizes the findings regarding the most influencing factors for MRR, TWR, and SR and provides the specific optimal parameter settings for the AISI D2 steel machining process.
Keywords
Electric Discharge Machine, Aluminium Electrode, AISI D2 steel, MRR, TWR, Surface Roughness, Taguchi Method, MINITAB, Optimization, Dielectric Fluid, Non-traditional Machining, Signal to Noise Ratio, Parameter Analysis.
Frequently Asked Questions
What is the core focus of this research paper?
The paper focuses on the experimental optimization of EDM machining parameters (current, pulse on time, and pulse off time) to improve the performance of AISI D2 steel machining using an aluminium electrode.
What are the primary performance indicators measured in this study?
The study evaluates three main output parameters: Material Removal Rate (MRR), Tool Wear Rate (TWR), and Surface Roughness (SR).
What is the primary objective of this work?
The goal is to determine the optimal combination of input parameters that maximizes MRR while minimizing TWR and Surface Roughness for AISI D2 steel.
Which scientific methodology is employed for this research?
The authors employ the Taguchi method, specifically an L9 orthogonal array, to reduce the number of required experimental trials and optimize the machining system.
What does the main body of the paper cover?
The main body covers the theoretical definitions of the parameters, the experimental design, the observation tables containing raw data, and the response tables used for statistical analysis.
Which keywords best describe this study?
Key terms include Electric Discharge Machine, AISI D2 steel, Aluminium Electrode, Taguchi Method, MRR, and Parameter Optimization.
How does the pulse off time affect the Material Removal Rate?
According to the results, pulse off time is identified as the most prompting factor affecting the Material Removal Rate (MRR) in the experimental setup.
What is the recommended optimum condition for SR in this study?
The study concludes that for minimizing Surface Roughness (SR), the optimal condition is a current of 6A, a Pulse on time of 50 µs, and a Pulse off time of 8 µs.
- Arbeit zitieren
- Sidhant Gupta (Autor:in), S.K. Jain (Autor:in), Gurpinder Singh (Autor:in), 2016, Experimental Study of MRR, TWR, SR on AISI D2 steel, München, GRIN Verlag, https://www.grin.com/document/340653
