2.1. Laser Powder Bed Fusion (PBF-LB/M)

SLM 125HL (SLM Solutions GmbH, Lubeck, Germany) was used for the AM samples. The device was equipped with a 400 W single Ytterbium-fiber-laser source (wavelength 1080 nm) and a maximum scanning velocity of 10 m/s. The maximum build volume is equal to 125 × 125 × 125 mm. The range of possible layer thicknesses was 20–75 µm. The substrate plate could be heated up to 200 °C, and the AM process was performed in an argon atmosphere (in which the amount of oxygen was lower than 0.3%).

The first stage of the study involved the development of process parameters based on the porosity analysis of the AM cubic samples. Regarding the limited availability of information on the process parameters for 21NiCrMo2 steel, the default settings for H13 tool steel were used as base parameters (laser power P_L = 225 W, scanning velocity v_s = 600 mm/s, hatch distance d_H = 0.120 mm). To properly prepare for the parameter development stage, 57 different parameter groups were considered. The exact values of process parameters were tested in the following ranges: laser power P_L ranging from 160 W to 240 W (not using the full laser power due to its tendency to generate cracks in the steel structure), scanning velocity v_s ranging from 600 to 1100 mm/s, and hatching distance d_H ranging from 0.070 mm to 0.120 mm. The layer thickness l_t was kept at the same level and was equal to 0.03 mm. The platform heating was set at a value of 190 °C. As a representative parameter (dependent on P_L, v_s, d_H, and t_L) energy density E_v can be described by means of the following Equation (1):

AM samples for the porosity analysis had the form of cubes with an edge length equal to 10 mm (one sample for each parameter group). The porosity measurements were performed utilizing the Keyence VHX 7000 optical microscope (Keyence, Osaka, Japan) in both representative planes: XY(P_ρXY)—parallel to the substrate plate surface, and YZ (P_ρYZ)—perpendicular to the substrate plate surface (Figure 2). The samples were cut using wire electrical discharge machining (WEDM) and mounted in resin for further microscopical investigation. All samples were ground using abrasive papers with a gradation from 320 to 2400 and polished using 1 µm diamond paste. As a representative porosity value, the average value was taken from P_ρXY and P_ρYZ (three different measurements for each plane).

(a) Flowchart of the adopted research methodology and (b) the orientation of samples orientaton in the substrate plate of SLM 125HL (Z—the direction of the layers’ deposition).

The maximum acceptable porosity value in the entire area of measurement in cross-sections was equal to 0.3%. Additionally, to improve the development of process parameters, Design of Experiment (DOE) analysis using Statistica software 13.1 (TIBICO Software Inc., Palo Alto, Santa Clara, CA, USA) was used. For the description of mathematical porosity values, the quadratic area regression model was used. This selection was made because of the possibility of combining features of multinomial regression and fraction factorial regression models. Hence, it allowed the consideration of three independent variables and their mutual interaction. Adegok et al. [29] suggested such an approach in their work. The general form of the quadratic regression is shown in Equation (2):

In Equation (2), y is a dependent variable (the estimated porosity value) and x₁, x₂, and x₃ are independent variables, which can be described as follows:

β_m and β_mn (for m = 1, 2, 3; n = 1, 2, 3) are regression coefficients, and ε is the modeling residual or error. The values of the regression coefficients were calculated with the use of the method of least squares. The calculations were divided into two parts. The first stage was dedicated to the creation of the model, based on the first porosity measurements (based on two experiments) of 27 different samples. The second stage was based on the development of further parameter combinations using the 3³ full factorial designs (three factors: laser power, exposure speed, and hatching distance were varied at three levels for each factor). Such an approach allowed us to supplement the statistical model with the obtained results.

Additionally, the R² and p values were calculated. The R² coefficient defines how the statistical model and its predictors describe the variability of a referred parameter. The p value is the cumulative probability of drawing a sample as extreme as or more extreme than the observed one, assuming that the null hypothesis is true. The p coefficient was estimated by constructing an analysis of variance (ANOVA) table, and this was related to statistical tests. Statistical significance was set at p < 0.05. The validation of the obtained PBF-LB/M process parameter groups with the statistical analysis results was possible via the experimental study of the microscopic observations and porosity measurements. As a result, five process parameter groups were chosen for further research (microstructure investigation, hardness testing, and tensile tests).