# A Prediction Model for Additive Manufacturing of Inconel 718 Superalloy
## 4 Results and Discussion  
### Experimental Results  
The process parameters have a direct impact on geometric accuracy. Therefore, the geometry of the fabricated IN718 samples was analyzed by a coordinate measuring machine (CMM) in this study. In order to simplify the measurement process, the sample height dimension was selected to investigate the effect of process parameters on dimensional accuracy. The average, standard deviation, and uncertainty of the measurements were calculated for the sample height. According to the results extracted for the sample height, the average value was between 5.971 and 6.018 mm. The standard deviation varied from 0.77% to 1.82% and the estimated standard measurement uncertainty was between 0.17% and 0.41%. In this case, the source of uncertainty can be associated with the coordinate measuring machine (CMM) system, including variation in a workpiece, variation in the fixture, workpiece form error, sampling strategy, thermal condition, dirt, coolant, dynamic effects, and the operator [63]. Figure 2 illustrates the influence of operational parameters (LP, SS, and HS) on the height of the fabricated samples. As shown, scanning speed plays a significant role in the dimension accuracy, particularly sample height. The results show that the sample heights decreased significantly to lower than 5.98 mm when the scanning speed was in the range of 900 to 1050 mm/s. This can be observed in both SS-LP and HS-SS diagrams. Conversely, it can be observed that the sample heights increased to over 6.03 mm when the hatch spacing was below 100 \(\upmu\)m. This also happened when laser power was below 260 W or scanning speed was over 1050 mm/s. Figure 1: Schematic of the neural network model. This variation in the height of the samples can be attributed to the level of energy density used during the fabrication process. A higher level of energy density will result in the formation of deeper pools, which facilitates epitaxial solidification [24, 64]. This, in turn, leads to the elongation of grains parallel to the building direction and the formation of columnar structures [24, 64]. This condition affects the dimensions of the parts, particularly the sample height. On the other hand, the formation of shallower melt pools results from a lower level of energy density, leading to lower height values for the as-fabricated samples [42]. As the relationship between scanning speed and energy density is inverse, a higher scanning speed (lower energy density) results in a lower sample height. The same thing is valid for the hatch spacing, as it follows a similar relationship with energy density. According to the results obtained for the hardness, the average value ranged from 260.28 to 308.58 HV. In this case, the standard deviation was between 1.36% and 16.14% and the standard measurement uncertainty varied from 0.30% to 3.61%. For the hardness measurements, the source of uncertainty can be categorized as test specimen (preparation, parallelism, and surface aspect), testing means (measurement for the diagonal of indentation), test environment (temperature and dirt), and the operator [65]. Figure 3 demonstrates that hatch spacing had a substantial impact on determining the surface hardness of the fabricated IN718 samples. As can be seen, the sample hardness decreased considerably from 270 to 260 HV when the hatch spacing increased from 110 to 125 \(\upmu\)m. This occurred when both laser power and scanning speed were considered  
Figure 2: The influence of processing parameters on the height of the SLM-fabricated IN718 samples. constant (960 mm/s and 285 W respectively). Additionally, Figure 3 reveals that the surface hardness can increase sharply to around 300 HV when the laser power is over 300 W and the scanning speed is below 850 mm/s, as shown in the LP-SS diagram.