## 3 DL-Based Ontology
### Entities for Part Orientation  
Part orientation is a process planning task that aims to design a build orientation that best meets the build and quality requirements to build a part [4]. The main inputs of this task include a 3D model of a part to be built and specific build and quality requirements on the part. Its output is a 3D model in a build orientation. The 3D model is the results of the design activity and generally encoded in a specific format [22], such as the STL (standard \begin{table}
\begin{tabular}{l l l l} \hline \hline
**Object Relation** & **Domain** & **Range** & **Meaning** \\ \hline \(\mathit{hasEnergySource}\) & \(\mathit{AmProcess}\) & \(\mathit{LaserBeam}\) & An AM process that has energy source of \\ \(\mathit{hasBuildMaterial}\) & \(\mathit{AmProcess}\) & \(\mathit{PowderMaterial}\) & An AM process that has build material of \\ \(\mathit{hasBuildPlatform}\) & \(\mathit{AmProcess}\) & \(\mathit{PowderBed}\) & An AM process that has build platform of \\ \(\mathit{hasBuildMechanism}\) & \(\mathit{AmProcess}\) & \(\mathit{Melting}\) & An AM process that has build mechanism of \\ \(\mathit{hasAimOfDesigning}\) & \(\mathit{RealisationActivity}\) & \(\mathit{ProcessVariable}\) & A realisation activity that has aim of designing \\ \(\mathit{isManufacturedUsing}\) & \(\mathit{AmPart}\) & \(\mathit{Lbpf}\) & An AM part that is manufactured using \\ \(\mathit{isApplicableFor}\) & \(\mathit{PowderMaterial}\) & \(\mathit{Lbpf}\) & A powder material that is applicable for \\ \(\mathit{isBasedOn}\) & \(\mathit{AmMachine}\) & \(\mathit{Lbpf}\) & An AM machine that is based on \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Domain, range, and meaning of eight top-level object relations. tessellation language) format, 3 MF (3D manufacturing file) format, and AMF (additive manufacturing file) format. Existing methods for part orientation can be classified into search-based methods and rule-based methods [4]. Search-based methods take the part orientation problem as a multi-objective optimisation problem. They usually adopts specific search algorithms, such as the random search algorithm [57], genetic algorithm [58], particle swarm algorithm [59], and iterative tabu search algorithm [60], to search an orientation that can optimise multiple objectives at the same time from infinite possible orientations. In search-based methods, a build orientation is generally expressed via an angle pair \((\alpha,\beta)\), where the build orientation lines up along the +\(z\) axis after rotating the 3D model \(\alpha\) (\(0\leq\alpha\leq 360\)) degrees around the \(x\) axis and \(\beta\) (\(0\leq\beta\leq 360\)) degrees around the \(y\) axis. Search-based methods usually have relatively high accuracy and relatively low efficiency. They are generally applied to free-form surface models. Rule-based methods take the part orientation problem as a multi-objective decision-making problem. It first generates a certain number of alternative orientations from infinite possible orientations via performing shape feature recognition [61; 62] or triangular facet clustering [63; 64; 65] on the 3D model and carrying out rule-based reasoning according to the recognition or clustering results. Then, a multi-objective decision-making method is used to select an orientation from the alternative orientations that can satisfy multiple objectives at the same time. In rule-based methods, a build orientation is generally represented by a unit vector \((x,y,z)\). Rule-based methods are relatively efficient, since they do not spend time on many meaningless calculations. However, they are difficult to achieve desired accuracy on free-form surface models. They are more suitable for regular surface models. Based on the analysis above, it is recommended to use a rule-based method for part orientation when the input 3D model is a regular surface model and to use a search-based method on a free-form surface model.