NiCrBSi coatings textured by Nd-YAG laser

Garrido, Alberto Higuera; González, R.; Cadenas, M.; Viesca, J.L.

doi:10.1504/ijsurfse.2011.041395

Cited by 6 publications

(1 citation statement)

References 31 publications

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“…Garrido et al [ 29 ] studied laser texturing of laser cladded Ni-based self-fluxing alloy coatings (>660 µm thick, of 800 to 880 HV0.3 microhardness), by applying central composite design. They changed three input variables (energy, laser spot diameter, and impulse duration) with the main aim to obtain statistical dependence of the diameter and the dimples’ depth on the previously mentioned input parameters.…”

Section: Statistical Modeling With Doe In Investigating Ni-based Smentioning

confidence: 99%

Modeling and Optimization in Investigating Thermally Sprayed Ni-Based Self-Fluxing Alloy Coatings: A Review

et al. 2020

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In investigating thermally sprayed Ni-based self-fluxing alloy coatings, widely applied under conditions of wear, corrosion, and high temperatures, designed experiments and statistical methods as a basis for modeling and optimization have become an important tool in making valid and comparable conclusions. Therefore, this paper gives an overview of investigating Ni-based self-fluxing alloy coatings deposited by thermal spraying by the use of designed experiments and statistical methods. The investigation includes the period of the last two decades and covers the treatments of flame spraying, high-velocity oxy/air fuel spraying, plasma spraying, plasma-transferred arc welding, and laser cladding. The main aim was to separate input variables, as well as measured responses, and to point out the importance of correct application of statistical design of experiment. After the review of the papers, it was concluded that investigators have used the process knowledge to analyze and interpret the results of the statistical analysis of experimental data, which is in fact the best way of using the design of experiment in every research. Nevertheless, more attention should be given to correct planning and conducting the experiments to derive the models suitable for the prediction of measured response and which could be an appropriate input for single- or multi-objective optimization.

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Section: Statistical Modeling With Doe In Investigating Ni-based Smentioning

confidence: 99%