A Review on Optimization Method for Machining Parameters Using DOE

Optimizing Machining Parameters Using DOE

Authors

  • Dr. Prashant Sharma

Keywords:

optimization method, machining parameters, DOE, design of experiments, product design, process performance, factorial design, Taguchi method, response surface methodology, grey Taguchi, statistical design, metal machining, surface roughness, tool wear, metal removal rate

Abstract

The design of experiments is a powerful approach to improve product design or process performance. This procedure constitutes a systematic method for the planning of experiments, collection and analysis of data with near-optimum use of available resources. It is used to investigate the variables affecting the product design and process performance, systematically. On the basis of planning, the design of experiments includes several techniques, such as, factorial design, Taguchi method, response surface methodology, grey Taguchi etc. In the past, numerous researchers extensively used statistical design of experiments to investigate the effect of machining conditions on responses and to optimize the machining parameters for achieving the desire response i.e minimum surface roughness, minimum tool wear, maximum metal removal rate etc. in metal machining a brief discussion in this regard has been presented in this review paper.

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Published

2019-03-01

How to Cite

[1]
“A Review on Optimization Method for Machining Parameters Using DOE: Optimizing Machining Parameters Using DOE”, JASRAE, vol. 16, no. 3, pp. 186–192, Mar. 2019, Accessed: Jul. 08, 2024. [Online]. Available: https://ignited.in/jasrae/article/view/10846

How to Cite

[1]
“A Review on Optimization Method for Machining Parameters Using DOE: Optimizing Machining Parameters Using DOE”, JASRAE, vol. 16, no. 3, pp. 186–192, Mar. 2019, Accessed: Jul. 08, 2024. [Online]. Available: https://ignited.in/jasrae/article/view/10846