Quality characteristics optimization in CNC end milling of A36 K02600 using Taguchi’s approach coupled with artificial neural network and genetic algorithm
Author:
Publisher
Springer Science and Business Media LLC
Subject
Strategy and Management,Safety, Risk, Reliability and Quality
Link
http://link.springer.com/content/pdf/10.1007/s13198-019-00796-8.pdf
Reference36 articles.
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2. Arnaiz-González Á, Fernández-Valdivielso A, Bustillo A, de Lacalle LNL (2016) Using artificial neural networks for the prediction of dimensional error on inclined surfaces manufactured by ball-end milling. Int J Adv Manuf Technol 83(5–8):847–859
3. Arora R, Arora R (2018a) Multiobjective optimization and analytical comparison of single- and 2-stage (series/parallel) thermoelectric heat pumps. Int J Energy Res 42(4):1760–1778
4. Arora R, Arora R (2018b) Multicriteria optimization based comprehensive comparative analyses of single-and two-stage (series/parallel) thermoelectric generators including the influence of thomson effect. J Renew Sustain Energy 10(4):044701
5. Arora R, Kaushik SC, Kumar R (2015a) Multi-objective and multi-parameter optimization of two-stage thermoelectric generator in electrically series and parallel configurations through NSGA-II. Energy 91:242–254
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