Modeling and parametric optimization of electrical discharge machining on casted composite using central composite design

• Published in: International journal on interactive design and manufacturing Vol. 18; no. 5; pp. 2793 - 2803
• Main Authors: Gugulothu, Bhiksha, Bharadwaja, K., Vijayakumar, S., Rao, T. V. Janardhana, Sri, M. Naga Swapna, Anusha, P., Agrawal, Manoj Kumar
• Format: Journal Article
• Language: English
• Published: Paris Springer Paris 01.07.2024; Springer Nature B.V
• Subjects: Alloys; CAE) and Design; Composite materials; Computer-Aided Engineering (CAD; Design; Design optimization; Electric discharge machining; Electrodes; Electronics and Microelectronics; Engineering; Engineering Design; Fly ash; Hard materials; Hybrid composites; Industrial applications; Industrial Design; Instrumentation; Material removal rate (machining); Mechanical Engineering; Mechanical properties; Optimization techniques; Original Paper; Process variables; Regression models; Surface roughness; Variables; Variance analysis; MMC; EDM process; CCD technique; MRR; ANOVA
• ISSN: 1955-2513; 1955-2505
• DOI: 10.1007/s12008-023-01323-7

MMCs are broadly used in several industrial applications because of their excellent mechanical properties. Hard materials and composites cannot be machined by typical conventional methods. so nonconventional machining methods such as Electrical discharge machining are mostly used. This work focuses to optimize the process variables of EDM of Al5456/SiC/Flyash hybrid composites. The impact of three most significant variables including pulse-off time, current and pulse-on time are examined. Central Composite Design (CCD) based RSM is applied for experimentation. The development model for material removal rate (MRR) and surface roughness (SR) are investigated by using CCD technique. ANOVA is implemented to identify the most significant variables and their output response of MRR and SR. From the validation result, the maximum values of MRR and SR are identified as 0.783 mm 3 /min and 13.26 μm, whereas minimum values are 0.249 mm 3 /min and 8.24 μm. ANOVA results show that current and pulse OFF time are highly significant variables to increase MRR and SR. The development of a regression model and 3D/Contour are made to predict and evaluate the Material Removal Surface and Surface roughness.