Optimizing Processing Parameters for Multi-Track Laser Cladding Utilizing Multi-Response Grey Relational Analysis
Source abstract
Abstract
Multi-track laser cladding is the primary technology used in industrial applications for surface reinforcement and remanufacturing of broken parts. In this study, the influence of processing parameters on multi-track laser cladding was investigated using a Taguchi orthogonal experimental design. A multi-response grey relational analysis (GRA) was employed to identify laser cladding processing parameters that simultaneously optimize the flatness ratio of the coating and the cladding efficiency. The optimal parameters setting found by GRA were validated experimentally. Results showed that the flatness ratio and cladding efficiency were closely correlated to the overlap rate and laser power, where the overlap rate shows the most significant impact on the flatness ratio and the laser power shows the most significant impact on cladding efficiency. Results from the validation experiment were within one percent (0.97% error) of the predicted value. This demonstrates the benefits of utilizing GRA in laser cladding process optimization. The methods presented in this paper can be used to identify ideal processing parameters for multi-response multi-track laser cladding processes or other industrial applications.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Additive Manufacturing Materials and Processes · High Entropy Alloys Studies · Welding Techniques and Residual Stresses
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Mechanical & Automotive Engineering, Fujian University of Technology, Fuzhou 350118, China
School of Engineering + Technology, Western Carolina University, Cullowhee, NC 28723, USA
Digital Fujian Industrial Manufacturing IoT Lab, Fuzhou 350118, China
Funding
National Natural Science Foundation of China
References (29)
Show source-provided references
1. Effect of laser remelting on microstructure and properties of wc reinforced fe-based amorphous composite coatings by laser cladding10.1016/j.optlastec.2018.01.024 ↗
2. Zhai, L., Ban, C., Zhang, J., and Yao, X. (2019). Characteristics of dilution and microstructure in laser cladding Ni-Cr-B-Si coating assisted by electromagnetic compound field. Mater. Lett.10.1016/j.matlet.2019.01.133 ↗
3. Effect of the scanning speed on microstructural evolution and wear behaviors of laser cladding nicrbsi composite coatings10.1016/j.optlastec.2015.03.015 ↗
4. Microstructure evolution during laser cladding Fe-Cr alloy coatings on ductile cast iron10.1016/j.optlastec.2018.07.004 ↗
5. Effects of the content of MoS2 on microstructural evolution and wear behaviors of the laser-clad coatings10.1016/j.surfcoat.2018.10.100 ↗
6. Microstructure, formation mechanism and property characterization of Ti + SiC laser cladded coatings on Ti6Al4V alloy10.1016/j.matchar.2018.11.032 ↗
7. Khamidullin, B., Tsivilskiy, I., Gorunov, A., and Gilmutdinov, A.K. (2019). Modeling of the effect of powder parameters on laser cladding using coaxial nozzle. Surf. Coat. Technol.10.1016/j.surfcoat.2018.12.002 ↗
8. An empirical-statistical model for laser cladding of Ti-6Al-4V powder on Ti-6Al-4V substrate10.1016/j.optlastec.2017.10.015 ↗
9. Geometry modeling of single track cladding deposited by high power diode laser with rectangular beam spot10.1016/j.optlaseng.2017.07.008 ↗
10. Parametric study and characterization of AlN-Ni-Ti6Al4V composite cladding on titanium alloy10.1016/j.surfcoat.2018.05.053 ↗
11. Laser cladding of Ni based powder on a Cu-Ni-Al glassmold: Influence of the process parameters on bonding quality and coating geometry10.1016/j.jallcom.2018.09.004 ↗
12. Predictive modeling and the effect of process parameters on the hardness and bead characteristics for laser-cladded stainless steel10.1007/s00170-017-0898-5 ↗
13. Optimization of parameters in laser powder deposition AlSi10Mg alloy using Taguchi method10.1016/j.optlastec.2018.10.030 ↗
14. Formation quality optimization of laser hot wire cladding for repairing martensite precipitation hardening stainless steel10.1016/j.optlastec.2014.07.017 ↗
15. Optimization of welding parameters of Ti 6Al 4V cruciform shape weld joint to improve weld strength based on taguchi method10.1016/j.matpr.2017.12.072 ↗
16. Optimization of tensile strength in TIG welding using the taguchi method and analysis of variance (ANOVA)10.1016/j.tsep.2018.08.005 ↗
17. Optimisation of multiple quality characteristics of hardfacing using grey-based taguchi method10.1016/j.matdes.2011.04.050 ↗
18. Analysis of hard machining of titanium alloy by taguchi method10.1016/j.matpr.2017.08.020 ↗
19. Application of signal to noise ratio and grey relational analysis to minimize forces and vibrations during precise ball end milling10.1016/j.precisioneng.2017.10.014 ↗
20. Investigation on the parameter optimization and performance of laser cladding a gradient composite coating by a mixed powder of Co50 and Ni/WC on 20CrMnTi low carbon alloy steel10.1016/j.optlastec.2017.09.010 ↗
21. Geometry characteristics modeling and process optimization in coaxial laser inside wire cladding10.1016/j.optlastec.2017.10.035 ↗
22. Study on deposition rate and laser energy efficiency of laser-induction hybrid cladding10.1016/j.optlastec.2015.08.019 ↗
23. Effects of the cladding parameters on the deposition efficiency in pulsed Nd: YAG laser cladding10.1016/j.jmatprotec.2007.09.024 ↗
24. Hussain, M.Z., Khan, S., and Sarmah, P. (2019). Optimization of powder metallurgy processing parameters of Al2O3/Cu composite through taguchi method with grey relational analysis. J. King Saud Univ. Eng. Sci., (In Press).
25. Experimental research and multi-response multi-parameter optimization of laser cladding Fe31310.1016/j.optlastec.2018.06.030 ↗
26. Multi-response optimization of process parameters in friction stir welded AM20 magnesium alloy by Taguchi grey relational analysis10.1016/j.jma.2014.12.002 ↗
27. Experimental investigation of machinability characteristics and multi-response optimization of end milling in aluminium composites using RSM based grey relational analysis10.1016/j.measurement.2017.04.014 ↗
28. Multi-response optimization design of tailor-welded blank (TWB) thin-walled structures using taguchi-based gray relational analysis10.1016/j.tws.2018.07.007 ↗
29. Grey relation performance correlations among economics, energy use and carbon dioxide emission in taiwan10.1016/j.enpol.2006.06.012 ↗