Machining performance optimization for electro-discharge machining of Inconel 601, 625, 718 and 825: an integrated optimization route combining satisfaction function, fuzzy inference system and Taguchi approach

Machining performance optimization for electro-discharge machining of Inconel 601, 625, 718 and... Nickel-based super alloy (such as Inconel) is widely used in aerospace, nuclear, and chemical industries because of its excellent mechanical and chemical properties at elevated temperatures. Inconel comes under the category of “difficult-to-cut” materials. Difficulty is faced whilst machining of Inconel because of its poor thermal conductivity, high toughness, high hardness, and extremely high work hardening behaviour. Moreover, it contains highly abrasive carbide particles which tend to stick on the tool surface, resulting in inferior surface finish. Moreover, enormous heat is generated during machining which leads to reduction in tool life. Hence, machining and machinability aspects of Inconel have become a predominant research agenda today. Technological advances have led to an extensive usage of high strength, high hardness materials in manufacturing industries. In course of machining of “difficult-to-cut” materials, conventional manufacturing processes are increasingly being replaced by the advanced techniques such as electro-discharge machining (EDM), ultrasonic machining, electro-chemical machining and laser machining. Amongst these, EDM has found widespread application in micro-electro-mechanical systems; tool and die, automobile and aerospace industries. Therefore, promoting the quality of the EDMed product and thereby achieving satisfactory machining performance; a thorough understanding of the relationship between the EDM parameters and the machined surface integrity in consideration with the tool-work combination has become an important research focus. EDM is an electro-thermal machining process, where electrical energy is used to generate electrical spark and material removal mainly occurs due to thermal energy of the spark. It has become an excellent option to machine “difficult-to-cut” materials and high temperature resistant alloys; super alloy Inconel, in the present case. An experimental investigation on assessing machining performance during EDM of Inconel 625, 718, 601 and 825 has been delineated herein. Attempt has been made on evaluating optimal machining parameters setting to achieve satisfactory machining yield. Based on 5-factor-4-level L16 orthogonal array, experiments have been carried out by varying gap voltage, peak current, pulse-on time, duty factor and flushing pressure (each varied at four discrete levels) to examine the extent of machining performance in terms of material removal rate, electrode wear rate, surface roughness, and surface crack density of EDMed end products obtained by utilizing different parameters settings (for Inconel of different grades, respectively). An integrated optimization route combining satisfaction function approach, fuzzy inference system in conjugation with Taguchi’s philosophy has been proposed for simultaneous optimization of aforementioned multiple performance indices. The most favourable machining parameters setting have been obtained as: [gap voltage = 90 V, peak current = 5 A, pulse-on time = 200 µs, duty factor = 70%, flushing pressure = 0.6 bar] for Inconel 625; [gap voltage = 90 V, peak current = 5 A, pulse-on time = 200 µs, duty factor = 85%, flushing pressure = 0.4 bar] for Inconel 718; [gap voltage = 80 V, peak current = 7 A, pulse-on time = 500 µs, duty factor = 80%, flushing pressure = 0.3 bar] for Inconel 601; and [gap voltage = 80 V, peak current = 5 A, pulse-on time = 300 µs, duty factor = 85%, flushing pressure = 0.4 bar] for Inconel 825. In addition to that, analysis of SEM micro-graphs has been carried out to understand surface irregularities in terms of surface cracks, white layer for EDMed Inconel end products (of different grades). http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of the Brazilian Society of Mechanical Sciences and Engineering Springer Journals

Machining performance optimization for electro-discharge machining of Inconel 601, 625, 718 and 825: an integrated optimization route combining satisfaction function, fuzzy inference system and Taguchi approach

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Publisher
Springer Berlin Heidelberg
Copyright
Copyright © 2016 by The Brazilian Society of Mechanical Sciences and Engineering
Subject
Engineering; Mechanical Engineering
ISSN
1678-5878
eISSN
1806-3691
D.O.I.
10.1007/s40430-016-0659-7
Publisher site
See Article on Publisher Site

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