Chinese Journal of Lasers, Volume. 47, Issue 1, 0102004(2020)
Multi-Objective Optimization of Coaxial Powder Feeding Laser Cladding Based on NSGA-II
[1] Fu L. Opportunities and challenges facing Chinese manufacturing under new model of intelligent manufacturing[J]. Machine Tool & Hydraulics, 44, 161-164, 89(2016).
[2] Zhang J, Wu W N, Zhao L Z. Research progress and development trend of laser cladding[J]. Hot Working Technology, 42, 131-134, 139(2013).
[4] Janicki D. Laser cladding of Inconel 625-based composite coatings reinforced by porous chromium carbide particles[J]. Optics & Laser Technology, 94, 6-14(2017).
[5] Paul C P, Mishra S K, Premsingh C H et al. Studies on laser rapid manufacturing of cross-thin-walled porous structures of Inconel 625[J]. The International Journal of Advanced Manufacturing Technology, 61, 757-770(2012).
[6] Chen W J, Chen H, Li C C et al. Microstructure and fatigue crack growth of EA4T steel in laser cladding remanufacturing[J]. Engineering Failure Analysis, 79, 120-129(2017).
[7] Lee C, Park H, Yoo J et al. Residual stress and crack initiation in laser clad composite layer with Co-based alloy and WC + NiCr[J]. Applied Surface Science, 345, 286-294(2015).
[10] Aubry P, Blanc C, Demirci I et al. Laser cladding and wear testing of nickel base hardfacing materials: influence of process parameters[J]. Journal of Laser Applications, 29, 022504(2017).
[11] Zhang Z, Kovacevic R. Multiresponse optimization of laser cladding steel+VC using grey relational analysis in the Taguchi method[J]. JOM, 68, 1762-1773(2016).
[12] Farahmand P, Kovacevic R. Parametric study and multi-criteria optimization in laser cladding by a high power direct diode laser[J]. Lasers in Manufacturing and Materials Processing, 1, 1-20(2014).
[13] Xu X C, Wen H J, Wang J Y et al. Optimization of laser cladding conditions in response surface method for repairing damaged alloy parts[J]. Chinese Journal of Vacuum Science and Technology, 38, 615-620(2018).
[14] Lei K Y, Qin X P, Liu H M et al. Prediction on characteristics of molten pool in wide-band laser cladding based on neural network[J]. Journal of Optoelectronics·Laser, 29, 1212-1220(2018).
[15] Caiazzo F, Caggiano A. Laser direct metal deposition of 2024 Al alloy: trace geometry prediction via machine learning[J]. Materials, 11, 444(2018).
[16] Tian J, Hou J B. FGM centrifugal casting parameters adaptive optimization with SVM[J]. Foundry Technology, 39, 1731-1734(2018).
[17] Sarker T K, Tang M L. A strength Pareto evolutionary algorithm for live migration of multiple interdependent virtual machines in data centers[M]. ∥Arik S, Huang T, Lai W, et al. Neural information processing. Lecture notes in computer science. Cham: Springer, 9490, 114-121(2015).
[18] Nag K, Pal T, Pal N R. ASMiGA: an archive-based steady-state micro genetic algorithm[J]. IEEE Transactions on Cybernetics, 45, 40-52(2015).
[19] Knowles J D, Corne D W. Approximating the nondominated front using the Pareto archived evolution strategy[J]. Evolutionary Computation, 8, 149-172(2000).
[21] Vardhan M V, Sankaraiah G, Yohan M. Optimization of process parameters in CNC milling for machining P20 steel using NSGA-II[J]. IOSR Journal of Mechanical and Civil Engineering, 14, 57-63(2017).
Get Citation
Copy Citation Text
Kai Zhao, Xudong Liang, Wei Wang, Ping Yang, Yunbo Hao, Zhongliang Zhu. Multi-Objective Optimization of Coaxial Powder Feeding Laser Cladding Based on NSGA-II[J]. Chinese Journal of Lasers, 2020, 47(1): 0102004
Category: laser manufacturing
Received: Jul. 29, 2019
Accepted: Sep. 26, 2019
Published Online: Jan. 9, 2020
The Author Email: Kai Zhao (zkdlut@163.com), Xudong Liang (zkdlut@163.com)