An Overview of Technological Parameter Optimization in the Case of Laser Cladding

Kaiming Wang; Wei Liu; Yuxiang Hong; H. M. Shakhawat Sohan; Yonggang Tong; Yongle Hu; Mingjun Zhang; Jian Zhang; Dingding Xiang; Hanguang Fu; Jiang Ju

doi:10.3390/coatings13030496

An Overview of Technological Parameter Optimization in the Case of Laser Cladding

Kaiming Wang, Wei Liu, Yuxiang Hong, H. M. Shakhawat Sohan, Yonggang Tong^*, Yongle Hu, Mingjun Zhang, Jian Zhang, Dingding Xiang, Hanguang Fu, Jiang Ju^*

^*Corresponding author for this work

Department of Materials Science and Engineering

Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

81 Citations (Scopus)

62 Downloads (CityUHK Scholars)

Abstract

This review examines the methods used to optimize the process parameters of laser cladding, including traditional optimization algorithms such as single-factor, regression analysis, response surface, and Taguchi, as well as intelligent system optimization algorithms such as neural network models, genetic algorithms, support vector machines, the new non-dominance ranking genetic algorithm II, and particle swarm algorithms. The advantages and disadvantages of various laser cladding process optimization methods are analyzed and summarized. Finally, the development trend of optimization methods in the field of laser cladding is summarized and predicted. It is believed that the result would serve as a foundation for future studies on the preparation of high-quality laser cladding coatings. © 2023 by the authors.

Original language	English
Article number	496
Journal	Coatings
Volume	13
Issue number	3
Online published	23 Feb 2023
DOIs	https://doi.org/10.3390/coatings13030496
Publication status	Published - Mar 2023

Research Keywords

laser cladding
process parameter
optimization methods
review
EMPIRICAL-STATISTICAL MODEL
ARTIFICIAL NEURAL-NETWORK
CO-BASED COATINGS
COAXIAL LASER
POWDER DEPOSITION
MULTIRESPONSE OPTIMIZATION
COMPOSITE COATINGS
WEAR-RESISTANCE
GEOMETRICAL CHARACTERISTICS
PROCESSING PARAMETERS

Publisher's Copyright Statement

This full text is made available under CC-BY 4.0. https://creativecommons.org/licenses/by/4.0/

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.3390/coatings13030496

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@article{495ddf15301b4840bc68373c52930782,

title = "An Overview of Technological Parameter Optimization in the Case of Laser Cladding",

abstract = "This review examines the methods used to optimize the process parameters of laser cladding, including traditional optimization algorithms such as single-factor, regression analysis, response surface, and Taguchi, as well as intelligent system optimization algorithms such as neural network models, genetic algorithms, support vector machines, the new non-dominance ranking genetic algorithm II, and particle swarm algorithms. The advantages and disadvantages of various laser cladding process optimization methods are analyzed and summarized. Finally, the development trend of optimization methods in the field of laser cladding is summarized and predicted. It is believed that the result would serve as a foundation for future studies on the preparation of high-quality laser cladding coatings. {\textcopyright} 2023 by the authors.",

keywords = "laser cladding, process parameter, optimization methods, review, EMPIRICAL-STATISTICAL MODEL, ARTIFICIAL NEURAL-NETWORK, CO-BASED COATINGS, COAXIAL LASER, POWDER DEPOSITION, MULTIRESPONSE OPTIMIZATION, COMPOSITE COATINGS, WEAR-RESISTANCE, GEOMETRICAL CHARACTERISTICS, PROCESSING PARAMETERS",

author = "Kaiming Wang and Wei Liu and Yuxiang Hong and Sohan, {H. M. Shakhawat} and Yonggang Tong and Yongle Hu and Mingjun Zhang and Jian Zhang and Dingding Xiang and Hanguang Fu and Jiang Ju",

year = "2023",

month = mar,

doi = "10.3390/coatings13030496",

language = "English",

volume = "13",

number = "3",

}

TY - JOUR

T1 - An Overview of Technological Parameter Optimization in the Case of Laser Cladding

AU - Wang, Kaiming

AU - Liu, Wei

AU - Hong, Yuxiang

AU - Sohan, H. M. Shakhawat

AU - Tong, Yonggang

AU - Hu, Yongle

AU - Zhang, Mingjun

AU - Zhang, Jian

AU - Xiang, Dingding

AU - Fu, Hanguang

AU - Ju, Jiang

PY - 2023/3

Y1 - 2023/3

N2 - This review examines the methods used to optimize the process parameters of laser cladding, including traditional optimization algorithms such as single-factor, regression analysis, response surface, and Taguchi, as well as intelligent system optimization algorithms such as neural network models, genetic algorithms, support vector machines, the new non-dominance ranking genetic algorithm II, and particle swarm algorithms. The advantages and disadvantages of various laser cladding process optimization methods are analyzed and summarized. Finally, the development trend of optimization methods in the field of laser cladding is summarized and predicted. It is believed that the result would serve as a foundation for future studies on the preparation of high-quality laser cladding coatings. © 2023 by the authors.

AB - This review examines the methods used to optimize the process parameters of laser cladding, including traditional optimization algorithms such as single-factor, regression analysis, response surface, and Taguchi, as well as intelligent system optimization algorithms such as neural network models, genetic algorithms, support vector machines, the new non-dominance ranking genetic algorithm II, and particle swarm algorithms. The advantages and disadvantages of various laser cladding process optimization methods are analyzed and summarized. Finally, the development trend of optimization methods in the field of laser cladding is summarized and predicted. It is believed that the result would serve as a foundation for future studies on the preparation of high-quality laser cladding coatings. © 2023 by the authors.

KW - laser cladding

KW - process parameter

KW - optimization methods

KW - review

KW - EMPIRICAL-STATISTICAL MODEL

KW - ARTIFICIAL NEURAL-NETWORK

KW - CO-BASED COATINGS

KW - COAXIAL LASER

KW - POWDER DEPOSITION

KW - MULTIRESPONSE OPTIMIZATION

KW - COMPOSITE COATINGS

KW - WEAR-RESISTANCE

KW - GEOMETRICAL CHARACTERISTICS

KW - PROCESSING PARAMETERS

UR - http://gateway.isiknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=LinksAMR&SrcApp=PARTNER_APP&DestLinkType=FullRecord&DestApp=WOS&KeyUT=000958320700001

U2 - 10.3390/coatings13030496

DO - 10.3390/coatings13030496

M3 - RGC 21 - Publication in refereed journal

SN - 2079-6412

VL - 13

JO - Coatings

JF - Coatings

IS - 3

M1 - 496

ER -

An Overview of Technological Parameter Optimization in the Case of Laser Cladding

Abstract

Research Keywords

Publisher's Copyright Statement

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