Multi-objective optimization of µ-EDM parameters for µ-hole drilling on Hastelloy C 276 super alloy using Response Surface Methodology and multi-objective genetic algorithm. (November 2022)

• Record Type: Journal Article
• Authors: Dutta, Souradeep; Kumar Sarma, Deba
• Is Part Of: CIRP journal of manufacturing science and technology. Volume 39(2022)
• Page Start: 115
• Page End: 133
• Publication Date: 2022-11
• Subjects: Micro-electrical discharge machining -- Material removal rate -- Tool wear rate -- Diametral overcut -- Response Surface Methodology -- Multi-objective genetic algorithm; Manufacturing processes -- Periodicals; 670.5
• DOI: 10.1016/j.cirpj.2022.07.011
• Languages: English
• ISSNs: 1755-5817

Abstract

Abstract: Hastelloy C 276 is one of the nickel-based super alloys which has an excellent resistance against corrosion at high temperature. It has a major application in nuclear and aerospace industry. Micro-electrical discharge machining (µ-EDM) is a highly accurate and precise non-conventional micro-machining process to fabricate this alloy. Thus, in this research paper an effort has been made to examine the impact of input process parameters like capacitance, gap voltage and pulse on time (ton ) on the response variables i.e., material removal rate (MRR), tool wear rate (TWR) and diametral overcut (DOC) during µ-EDM of Hastelloy C 276. Response Surface Methodology (RSM) is a collection of statistical and mathematical tools which determine the relationship between input and output characteristics. Box-Behnken design (BBD) is a special type of RSM based design that reduces the no of experiments without affecting the variation between the input and response parameters. RSM based BBD is used in the current study to develop the mathematical models for each response variable. RSM based desirability function (RSM-DF) which convert multiple responses into a scale free desirability, is used as an optimization tool in the present study. The current work used the multi-objective genetic algorithm (MOGA), a non-conventional searching based multi-response optimization algorithm, to optimize the machining parameters for maximum MRR along with minimum TWR and DOC. The lowest machining time is achieved by experiment no 10 and the least entry µ-hole diameter is drilled by experiment no 15. ANOVA analysis accomplished that capacitance has the highest significant contribution towards MRR, TWR and DOC. 3D response surface plot discloses that MRR, TWR and DOC is increased with capacitance until 5600 pF, 5600 pF and 8900 pF and then there is little reduction took place for all the three responses. The optimization result from RSM-DF is capacitance of 1001.560 pF, gap voltage of 137.6670 volt and ton of 41.532 µs for maximum MRR along with minimum TWR and DOC. MOGA approach reveals that maximum MRR of 0.005153 mm 3 /min along with minimum TWR of 0.002423 mm 3 /min and minimum DOC of 0.028691 mm is found at a capacitance of 1001.610 pF, gap voltage of 137.6671 volt and ton of 48.025 µs. Conformation experiments are conducted and the absolute percentage errors between the experimental and optimized values are found to be less than 5% for both approaches. Field emission scanning electron microscopy (FESEM) analysis reveals that MOGA settings drilled µ-hole with less DOC, more circularity and less surface cracks compared to the initial and RSM-DF parametric settings. A deposition of C and Cu took place in the side wall of the micro-hole from the dielectric fluid and tool material respectively.