Multi-variable optimisation of the quality characteristics of fiber-laser cladded Inconel-625 composite coatings

Olakanmi, Eyitayo Olatunde; Nyadongo, ST; Malikongwa, Kinsman; Lawal, Sunday Albert; Botes, Annelize; Pityana, Sisa

doi:10.1016/j.surfcoat.2018.09.063

Cited by 38 publications

(19 citation statements)

References 30 publications

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“…The R-Square value of this model is 0.9447. In addition, the Adjusted R-Square and Predicted R-Square values are both close to 1 and the difference between these two values is 0.0176, which is less than the needed value of 0.2 [ 18 ]. These results demonstrate that this model has a high level of fit and could be used to precisely predict the correlation between processing parameters and micro-hardness.…”

Section: Resultsmentioning

confidence: 99%

“…Multiple regression analysis was employed to build and analyze the model between the input parameters and the output. The polynomial regression function is shown in Equation (1) below [ 18 ], where y is the response value and β 0 is the intercept factor. The coefficients for the linear term, interaction term, and quadratic term are β j , β ij , β jj , respectively.…”

Section: Methodsmentioning

confidence: 99%

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Computational and Experimental Investigation of Micro-Hardness and Wear Resistance of Ni-Based Alloy and TiC Composite Coating Obtained by Laser Cladding

Lian

Zhang

et al. 2019

Materials

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The influence of processing parameters on the micro-hardness and wear resistance of a Ni-based alloy and titanium carbide (TiC) composite cladding layer was studied. Mathematical models were developed to predict the micro-hardness and wear resistance of the cladding layer by controlling the laser cladding processing parameters. Key processing parameters were the laser power, scanning speed, gas flow, and TiC powder ratio. The models were validated by analysis of variance and parameter optimization. Results show that the micro-hardness is positively correlated with laser power and TiC powder ratio, where the TiC powder ratio shows the most significant impact. The wear volume decreased with an increasing TiC powder ratio. The targets for the processing parameter optimization were set to 62 HRC for micro-hardness and a minimal volume wear. The difference between the model prediction value and experimental validation result for micro-hardness and wear volume were 1.87% and 6.33%, respectively. These models provide guidance to optimize the processing parameters to achieve a desired micro-hardness and maximize wear resistance in a composite cladding layer.

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Computational and Experimental Investigation of Micro-Hardness and Wear Resistance of Ni-Based Alloy and TiC Composite Coating Obtained by Laser Cladding

Lian

Zhang

et al. 2019

Materials

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“…RSM is a comprehensive optimization method for experiment design and modelling. Compared with orthogonal design, RSM is capable of establishing correlations between targets and influencing factors with high accuracy but lower experiment cost [19,20]. We used central composite design to produce an experimental matrix for four factors with five levels (Specifically, 24 axial points and 6 replicated centre points).…”

Section: Design Of Experimentsmentioning

confidence: 99%

An Integrated Method for Multi-Objective Optimization of Multi-Pass Fe50/TiC Laser Cladding on AISI 1045 Steel based on Grey Relational Analysis and Principal Component Analysis

et al. 2020

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As an essentially multi-input multi-output process, determination of optimal conditions for laser cladding normally requires multi-objective optimization. To understand multi-response coupling, the effects of processing parameters on the morphology quality of multi-pass laser claddings of Fe50/TiC on medium carbon steel AISI 1045 were investigated based on composite central design using response surface methodology. Multiple responses, including clad width, flatness, and non-fusion area, were transformed into a single objective through grey relational analysis, with weights objectively identified by principal component analysis. The correlation between grey relational grade (GRG) and process parameters was established by regression analysis. The results show that the GRG response model has excellent goodness of fit and predictive performance. A validation experiment was conducted at the process condition optimized for maximum GRG. The relative error of the predicted optimal GRG is 4.87% whereas those of interested individual objectives, i.e. clad width, flatness, and non-fusion area, are 5.73%, 2.97%, and 6.73%, respectively, which verifies the accuracy of the established model. The investigation of mechanical properties suggests the hardness of substrate can be improved from 20 HRC to 60 HRC and wear resistance to over 8.14 times better.Coatings 2020, 10, 151 2 of 22 independently when conducting optimization. The authors of [5][6][7] used regression analysis (RA) to develop empirical-statistical relationships between key parameters and geometrical characteristics of single-pass NiCrAlY, Ti-6Al-4V, and WC-12Co claddings (i.e., clad height, clad width, penetration depth, wetting angle, and dilution) as a combined parameter (P α V β F γ ). These empirical-statistical relationships were found to be in good agreement with measured values of single clad passes. Shi et al. [8] evaluated the effects of processing parameters (laser power, scanning velocity, and powder mass flow rate) on the geometric form of clad (clad height, width, and depth penetration into the substrate) using multiple regression analysis (MRA). With optimized process parameters, a 45-mm-high thin wall was formed with smooth side surfaces. By applying individual objectives, the laser cladding process can be easily optimized for each criterion. However, multiple optimizations of process conditions are hard to combine into a common goal.Many researchers have presented numerous methodologies to integrate multiple objectives for process optimization. Grey relational analysis (GRA), a process of quantifying the dynamic development of complex systems, has become an efficient method to reveal the correlation between influencing factors and multiple responses [9,10]. Mondal et al. [11] prepared Ni/Cr/Mo composite coatings on AISI 1040 steel with a L9 orthogonal array, using GRA (response target weight was one-third) to build the relationship between process parameters (laser power, scan speed, and powder feed rate) and clad quality characteristics (clad he...

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“…Due to its excellent weldability by both liquid Ni and Co and high hardness, tungsten carbide (WC) can be successfully used as reinforcement. Despite extensive research on the WC addition effect on Ni- and Co-based alloy behavior in laser additive manufacturing [ 11 , 12 , 13 , 14 , 15 ], there are no complex reports focused on material behavior during thermal processing with different conditions. The general simplified behavior of the Inconel 625–WC system during heating should proceed as follows:

which is then followed by cooling,

…”

Section: Introductionmentioning

confidence: 99%

Heating Conditions Influence on Solidification of Inconel 625–WC System for Additive Manufacturing

et al. 2020

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In this study, an Inconel 625–tungsten carbide (WC) composite system was investigated by means of microstructure changes affected by both heating rate and WC content. In order to investigate how the system behaves while exposed to fast thermal processing, controlled melting using a differential thermal analysis (DTA) apparatus was performed on the powders. Two WC powders with different average grain size were used to obtain six compositions of Inconel 625–WC powder mixtures (10, 20, and 30 wt.% WC). They were analyzed under 10 and 30 °C/min heating rate in order to obtain composite samples. Results from DTA together with SEM/energy-dispersive X-ray spectroscopy (EDS) microstructural observations allowed observing material changes during solidification. Because of the extensive microsegregation of alloying elements to liquid and their reactions with C, which derived from dissolved WC, the formation of secondary phases with improved microhardness was possible. The collected results provide a better understanding of material behavior during intensive thermal processing which can be useful when designing materials for the laser additive manufacturing technique.

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Multi-variable optimisation of the quality characteristics of fiber-laser cladded Inconel-625 composite coatings

Cited by 38 publications

References 30 publications

Computational and Experimental Investigation of Micro-Hardness and Wear Resistance of Ni-Based Alloy and TiC Composite Coating Obtained by Laser Cladding

Computational and Experimental Investigation of Micro-Hardness and Wear Resistance of Ni-Based Alloy and TiC Composite Coating Obtained by Laser Cladding

An Integrated Method for Multi-Objective Optimization of Multi-Pass Fe50/TiC Laser Cladding on AISI 1045 Steel based on Grey Relational Analysis and Principal Component Analysis

Heating Conditions Influence on Solidification of Inconel 625–WC System for Additive Manufacturing

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