## 2 Methodology
### Data Collection and Pre-Processing
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**AM Parameter** & **Acronym** & **Units** & **Description** \\ \hline Program Time & - & s & Time elapsed since the data logging was activated in the program \\ Current Layer & CL & 1–284 & The current layer within the program \\ Infill Flag & IF & 0/1 & If InfillFlag = 1, the toolpath is currently running infill motion and parameters \\ Contour Flag & CF & 0/1 & If ContourFlag = 1, the toolpath is currently running contour (outer wall) motion and parameters \\ Feedrate Velocity & FR & mm/min & The scan speed of the deposition \\ X position & - & mm & X location of the build \\ Y position & - & mm & Y location of the build \\ Z position & - & mm & Z location of the build \\ A position & - & degree & Tilt Axis Angle of the Trunton/Turn table \\ C position & - & degree & Rotation Axis Angle of the Trunton/Turntable \\ Laser Power & LP & Watts & The Laser Power output of the process \\ Melt Pool Size & MPS & mm & Diameter of the melt pool \\ Specific Laser Energy Density & SLED & J/mm\({}^{2}\) & Combined parameter containing Laser \\  & & & Power, Laser Spot Diameter, and Feedrate Velocity. \\ Enclosure Temperature & ET & C & Temperature inside in the machine enclosure \\  & & & The speed of the powder feeder disc \\ Powder [\#] Disc Speed & PDS & RPM & which directly affects the powder mass \\  & & & flow rate. The \#\(\gtrsim\) refers to the selected \\  & & & \\  & & & The shield gas flow rate coming out of \\ Shield Gas & SG & L/min & the nozzle. Shield gas is used to provide \\  & & & a localized inert melt pool and reduce \\  & & & debris from entering into the nozzle. \\  & & & The carrier gas flow rate delivering the \\ Powder [\#] Carrier Gas & PCG & L/min & powder to the deposition head. Carrier \\  & & & gas will affect the speed of the powder coming out of the deposition head \\  & & & and the \(\#\) refers to the selected powder \\  & & & feeder shape of the powder cone. \\ \hline \hline \end{tabular}
\end{table} 
Table 1: AM Parameters. loaded using the Python pandas package [82] and resulted in a data array of 31 predictors and one response (binary labels of 0 or 1). All 284 layers are utilized in the dataset with each layer containing multiple data points (4950 data points in total for each feature), resulting in a data array of size 31 \(\times\) 4950 for sample 1 and 2. Labels were created from the CT scan dataset and an adjustable threshold, discussed in Section 2.3. The CT scan dataset contains 33 columns of features and 453 data points for each feature, resulting in a data array of size 31 \(\times\) 453 for sample 1 and 2. A program was developed to visualize these parameters along with sensed features and data. Figures 4 and 5 isolate the eight synchronously collected parameters during the inter-layer build process of sample #2. In Figure 6, we display the porosity quantities and sizes at the inter-layer level during the build process of workpiece #2 from the CT scan dataset. We can see most of the larger porosities are located between layers 10 to 160. Figure 5: Synchronously collected process parameters: (**a**) PCG, (**b**) SG, (**c**) PDS, and (**d**) FR. Figure 6: (**a**) Inter-layer low-density identification (voxel scale 0.03228 mm) and (**b**) Volumetric measurement.