Multi-Objective Optimization and Predictive Modeling of Surface Roughness and Material Removal Rate in Turning Using Grey Relational and Regression Analysis-Reference-Cited by-同舟云学术

Multi-Objective Optimization and Predictive Modeling of Surface Roughness and Material Removal Rate in Turning Using Grey Relational and Regression Analysis

Published:2012 Issue: Volume:38 Page:1606-1627
ISSN:1877-7058
Container-title:Procedia Engineering
language:en
Short-container-title:Procedia Engineering

Author:

Sahoo Ashok Kumar,Baral Achyuta Nanda,Rout Arun Kumar,Routra B.C.

Publisher

Elsevier BV

Subject

Applied Mathematics

Reference24 articles.

1. Feng CX, Wang X. Development of Empirical Models for Surface Roughness Prediction in Finish Turning. The International Journal of Advanced Manufacturing Technology. 2002; 20: 348-356.

2. Chattopadhyay AB. Machining and Machine Tools, Wiley India, New Delhi; 2011.

3. Astakhov VP. Tribology of Metal Cutting, Elsevier: London; 2006.

4. Noordin MY, Venkatesh VC, Sharif S, Elting S, Abdullah A. Application of Response surface methodology in Describing the Performance of Coated carbide tools when Turning AISI 1045 steel. Journal of Materials Processing Technology. 2004; 145: 46-58.

5. Choudhury IA, El-Baradie MA. Tool-life Prediction model by Design of experiments for Turning High strength steel (290 BHN). Journal of Materials Processing Technology. 1998; 77: 319-326.

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