Modeling and Optimization in Investigating Thermally Sprayed Ni-Based Self-Fluxing Alloy Coatings: A Review
Abstract
:1. Introduction
- Recognition of and statement of the problem (being a teamwork it includes people well acquainted with the investigated process, statisticians, operators, laboratory technicians, etc.).
- Selection of the response variable (what will be measured).
- Choice of input variables (factors), levels, and ranges (what will be varied).
- Choice of experimental design (as types of experimental designs are numerous, which one will be chosen depends on what the experiment is aimed at and which processing phase it is in).
- Performing the experiment (three important principles, described below, are to be taken into the consideration).
- Statistical analysis of the data (it is necessary to apply the knowledge of statistics).
- Conclusions and recommendations (“from statistics” turn again to the investigated problem and use the process knowledge to explain statistical conclusions).
- In Section 2, the investigations in which the designed experiments are applied for obtaining regression models, reviewed, and presented.
- Section 3 presents the research in which investigators did not apply (or did not specify) designed experiments for obtaining regression models or used some statistical methods.
- The investigations in which the DOE methodology and methods of artificial intelligence are combined, or only DOE methodology is used with the main aim of optimization, are also covered in Section 4.
- In Section 5, the discussion on the certain models, methodology, or optimization is presented.
- Finally, the conclusions are provided in Section 6.
2. Statistical Modeling with DOE in Investigating Ni-Based Self-Fluxing Alloy Coatings Deposition
2.1. PTAW and Laser Cladding
2.2. Flame Spraying
2.3. Plasma Spraying
2.4. HVOF Spraying
3. Statistical Modeling and Different Statistical Methods in Investigating Ni-Based Self-Fluxing Alloy Coatings Deposition
3.1. PTAW and Laser Cladding
3.2. Flame Spraying
3.3. Plasma Spraying
3.4. HVOF Spraying
4. Optimization in Investigating Ni-Based Self-Fluxing Alloy Coatings Deposition
4.1. PTAW and Laser Cladding
4.2. Flame Spraying
4.3. Plasma Spraying
4.4. HVOF Spraying
5. Discussion
- Normal probability plots of the residuals (or internally studentized residuals) to check for normal distribution (Figure 6).
- Plots of internally studentized residuals versus predicted values to check for constant error.
- Detailed discussion of externally studentized residuals to look for outliers, i.e., influential values (analysis of measure difference in fits and indicator of Cook’s distance should be included).
- Checking the coefficients of determination (high and equivalent values of R2 adjusted and R2 for prediction are desirable), as well as other ANOVA output (standard deviation, i.e., MSE—mean square error, predicted residual sum of squares, coefficient of variation, adequate precision, etc.).
6. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Deposition Technology | Input Variables | Responses | Method | References |
---|---|---|---|---|
PTAW | Coating hardness; Testing temperature; Sliding distance | Mass loss (dry sliding wear–pin on disc) | Full factorial design 33 | [21] |
Hardness of roller; Revolution speed of roller; Normal load | Wear rate (dry sliding wear–pin on roller) | CCD | [22,23] | |
Size of river sand particles in water; Temperature and concentration of slurry; Number of revolutions of samples | Wear rate (abrasive slurry) | [24,25] | ||
LC | Distance between microdimples obtained by laser texturing; Microdimples diameter | Coefficient of friction | Full factorial design 32 | [26] |
Laser power; Powder feed rate; Scanning speed | Clad height, width and penetration depth into substrate | Full factorial design 33 | [27] | |
Laser power; Scanning speed | Height and penetration of coating; Heat affected zone | Full factorial design 42 | [28] | |
Energy; Laser spot diameter; Impulse duration | Microdimples’ diameter and depth | CCD | [29] | |
Scanning speed; Powder feed rate; Overlapping and out-of-focus distance | Clad height, width and penetration depth into substrate; Content of WC in the coating | Taguchi and experimentation and modelization DOE | [30] | |
FS | Spraying distance; Type of coating | Volume loss (three-body abrasive wear) | Full factorial design 22 | [10] |
Time of fusing; Temperature of fusing | Porosity area; Corrosion resistance | Mixed-level full factorial design | [31] | |
Size of abrasive; Load; Temperature; Sliding speed | Mass loss (pin on disc two-body abrasive wear) | Fractional factorial design | [32] | |
PS | Load; Amount of WC particles in the coating; Size of abrasive particles; Environment (dry and wet testing) | Mass loss (three-body abrasive wear) | Full factorial design 24 | [33] |
Power; Spraying distance; Powders volume fraction | Porosity; Fraction of unmelted particles; Microhardness; Dynamic coefficient of friction and mass loss (dry sliding wear–ball on disc); Slurry erosion number; Polarization resistance | Mixed-level full factorial design | [34] | |
PS FS | Load; Testing temperature; Presence of WC in powder; Deposition technologies | Mass loss of coating and counter body (dry sliding wear–pin on plate) | Full factorial design | [35] |
PS HVOF | Amount of Fe2O3 in Ni matrix; Spraying distance; Gas pressure; Current–PS Amount of Fe2O3 in Ni matrix; Spraying distance; Flow rate of oxygen and propane–HVOF | Surface roughness; Coefficient of friction (dry sliding wear–ball on disc); Microhardness | Fractional design | [36] |
HVOF | Load; Temperature; Sliding distance | Mass loss (dry sliding wear–pin on disc) | Mixed-level full factorial design | [37] |
Laser power; Rotational scan speed–Laser remelting | Effectiveness index for laser remelting | Mixed-level full factorial design | [38] | |
Size of abrasive; Load; Temperature; Sliding distance | Mass loss (pin on disc two-body abrasive wear) | Fractional factorial design | [39] |
Deposition Technology | Input Variables | Responses | Method | Reference |
---|---|---|---|---|
PTAW | Content of sand; Slurry temperature; Velocity of slurry | Mass loss (erosion-corrosion) | Curve fitting | [40] |
PTAW LC | Average distance between WC particles; Average diameter of WC particles; Volume fraction of WC particles; Matrix hardness; Shape of WC particles | Wear rate (continuous impact abrasive wear) | Regression model | [41] |
LC | Volume removed (worn); Load; Sliding speed | Mass loss (dry sliding wear–block on ring); Average wear rate | Curve fitting | [42] |
Weight % of WC | Wear track cross section (dry sliding wear–ball on disc) | Curve fitting | [43] | |
Average distance between WC particles; Average diameter of WC particles; Volume fraction of WC particles; Matrix hardness | Wear rate (three-body abrasive wear) | Regression model | [44] | |
Weight % of WC | Hardness; Intensity (laser-induced breakdown spectroscopy) | Curve fitting | [45] | |
Pressure of carrier gas (air), Flow of carrier gas (air); Cladding distance, Laser spot speed | Powder feed rate; Clad height and width | Regression model | [46] | |
Exposure time in salt fog | Weibull modulus (Knoop hardness distribution) | Weibull distribution | [47] | |
- | - | Descriptive statistics | [48] | |
FS | Volume removed (worn) | Mass loss (dry sliding wear–block on ring) | Curve fitting | [49] |
Wear time | Wear volume (dry sliding wear–pin on disc) | Curve fitting | [50] | |
Debris particle (Al2O3) size; Initial (or final) surface roughness, lubricant viscosity, sliding speed, contact pressure | Surface roughness; Coefficient of friction | Curve fitting | [51] | |
PS | Load | Frictional force (dry sliding reciprocating wear) | Confidence interval; Curve fitting | [52] |
Capacitance arc radius (Nyquist plot); Frequency (Bode impedance and phase plots) | Solution, film and charge transfer resistance; Capacity element; Warburg impedance; Constant phase element | Curve fitting; Chi-square test | [53] | |
Linear parameters of pores | Spatial (3D) parameters of pores | Regression model; Correlation analysis | [54] | |
Hydrogen flow rate | Porosity | Weibull distribution | [55] | |
Power | Porosity | Weibull distribution | [56] | |
Power | Porosity; Modulus of elasticity; Microhardness; Residual stress | Weibull distribution | [57] | |
Powder feed rate | Porosity; Modulus of elasticity; Microhardness; Residual stress | Weibull distribution | [58] | |
Hydrogen flow rate; Power; Powder feed rate | Porosity; Modulus of elasticity; Microhardness | Weibull distribution | [59] | |
Contact pressure; Number of fatigue cycles | Failure probability | Weibull distribution | [60,61] | |
HVOF | Volume fraction of unmelted particles; sin2ψ (XRD measurement); Penetration depth | Surface roughness Rz; Interplanar spacing; Indentation load | Curve fitting | [62] |
HVOF FS | Volume fraction of hard particles | Abrasive wear resistance (three-body abrasive wear) | Curve fitting | [63] |
- | - | Descriptive statistics | [64] | |
HVOF FS PS | - | - | Statistical distribution | [65] |
Deposition Technology | Input Variables | Responses | Method | References |
---|---|---|---|---|
PTAW | Current; Oscillation amplitude; Travel speed; Preheat temperature; Powder feed rate | Weld height, depth and width; Dilution | Central composite design and genetic algorithm | [69] |
Type of coating material; Accelerating voltage; Powder feed rate; Preheat temperature; Current; Waving oscillation; Plasma gas rate; Rotation | Mass loss (dry sliding wear–pin on disc) | Taguchi and Taguchi regression method | [70] | |
Current; Welding speed; Oscillation speed | WC/W2C particles volume fraction in the coating; Hardness of the coating matrix; Equivalent diameter of WC/W2C particles | Grey relational Taguchi method | [71] | |
LC | Laser power; Scanning speed; Powder feed rate | Clad angle calculated by clad width and height | Full factorial design 33 and scatter search | [72] |
Laser power; Scanning speed; Powder feed rate | Porosity area | Method of steepest descent (RSM) | [73] | |
FS | Substrate surface roughness; Substrate preheat temperature; Oxygen-acetylene ratio; Spraying distance | Adhesive strength | Taguchi method | [74,75] |
Type of coating; Coating thickness; Type of substrate | Critical force (the appearance of the first crack) | Taguchi method | [8] | |
PS | Percentage of laser remelted surface; Angle of laser meshing for partial laser remelting after plasma spraying | Mass loss (lubricated sliding wear–block on ring) | Full factorial design 42 | [76] |
Powder feed rate; Power; Argon and hydrogen flow rate | Porosity | Box-Behnken design (RSM) | [77] | |
Powder feed rate; Power; Plasma gas flow rate; Spraying distance; Rotational speed of the specimen; Displacement rate of the plasma torch; Alloying additive | Coating microhardness, porosity and thickness; Cracks; Adhesive strength | Method of steepest descent (RSM) | [78] | |
PS HVOF | Type of deposition technology; Hardness of the counter body; Load of the sliding wear test | Mass loss (dry sliding wear–ball on disc); Coefficient of friction | Taguchi method | [64] |
HVOF | Spraying distance; Powder feed rate; Fuel/oxygen ratio | Corrosion current density; Corrosion potential; Porosity | Full factorial design 33 | [79] |
HVOF HVOLF | Speed; Impact angle; Concentration of slurry; Size of abrasive particles | Mass loss (slurry erosion) | Taguchi method | [80] |
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Simunovic, K.; Havrlisan, S.; Saric, T.; Vukelic, D. Modeling and Optimization in Investigating Thermally Sprayed Ni-Based Self-Fluxing Alloy Coatings: A Review. Materials 2020, 13, 4584. https://doi.org/10.3390/ma13204584
Simunovic K, Havrlisan S, Saric T, Vukelic D. Modeling and Optimization in Investigating Thermally Sprayed Ni-Based Self-Fluxing Alloy Coatings: A Review. Materials. 2020; 13(20):4584. https://doi.org/10.3390/ma13204584
Chicago/Turabian StyleSimunovic, Katica, Sara Havrlisan, Tomislav Saric, and Djordje Vukelic. 2020. "Modeling and Optimization in Investigating Thermally Sprayed Ni-Based Self-Fluxing Alloy Coatings: A Review" Materials 13, no. 20: 4584. https://doi.org/10.3390/ma13204584