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Surface Response Methodology Approach for Multi-Objective Optimization During Electrochemical Grinding of Al2O3/Al Interpenetrating Phase Composite

Surface Response Methodology Approach for Multi-Objective Optimization During Electrochemical Grinding of Al2O3/Al Interpenetrating Phase Composite

Goutam Kumar Bose, Pritam Pain
Copyright: © 2017 |Pages: 31
ISBN13: 9781522524403|ISBN10: 1522524401|EISBN13: 9781522524410
DOI: 10.4018/978-1-5225-2440-3.ch008
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MLA

Bose, Goutam Kumar, and Pritam Pain. "Surface Response Methodology Approach for Multi-Objective Optimization During Electrochemical Grinding of Al2O3/Al Interpenetrating Phase Composite." Handbook of Research on Manufacturing Process Modeling and Optimization Strategies, edited by Raja Das and Mohan Pradhan, IGI Global, 2017, pp. 162-192. https://doi.org/10.4018/978-1-5225-2440-3.ch008

APA

Bose, G. K. & Pain, P. (2017). Surface Response Methodology Approach for Multi-Objective Optimization During Electrochemical Grinding of Al2O3/Al Interpenetrating Phase Composite. In R. Das & M. Pradhan (Eds.), Handbook of Research on Manufacturing Process Modeling and Optimization Strategies (pp. 162-192). IGI Global. https://doi.org/10.4018/978-1-5225-2440-3.ch008

Chicago

Bose, Goutam Kumar, and Pritam Pain. "Surface Response Methodology Approach for Multi-Objective Optimization During Electrochemical Grinding of Al2O3/Al Interpenetrating Phase Composite." In Handbook of Research on Manufacturing Process Modeling and Optimization Strategies, edited by Raja Das and Mohan Pradhan, 162-192. Hershey, PA: IGI Global, 2017. https://doi.org/10.4018/978-1-5225-2440-3.ch008

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Abstract

Now a day the advances in the material science lead to the development of advanced engineering materials like super alloys. The current research work focus on the selection of significant machining parameters initially depending on single objective and then multi objective responses, while machining alumina-aluminum interpenetrating phase composites during electrochemical grinding. Control parameters such electrolyte concentration (C), voltage (V), depth of cut (D) and electrolyte flow rate (F) have been considered for experimentation. Initially single objective optimal parametric setting is generated from Taguchi Methodology and Regression analysis. Further it is optimize using Response Surface Methodology. The contradictory responses like higher material removal rate (MRR), lower surface roughness (Ra), lower overcut (OC) and lower cutting force (Fc) are ensured by using Overlaid contour plots and Desirability functions. These soft computing techniques corroborates well during the parametric optimization of electrochemical grinding process.

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