# A Process Decision-Making Method for Planar Machining of Box-Type Components
## 6 Implementation and Examples
### Case Study  
To validate the feasibility of the proposed method for planar machining process decision-making of box-type components, a case study is conducted using a gearbox as an example. The meta-ontology model is created using the ontology editor software **Protege 5.5**, with the component diagram shown in Figure 9. The specific steps of the process are outlined below:  
1. A part model is constructed in the CAD system based on the design information, resulting in four machined faces (S1, S2, S3, and S4) for the box-type component. An assertion formula set (APS) is then constructed to represent the relationship between the part and its machined faces. \(A_{PS}\) = {_MachinedFlat (S1)_, _MachinedFlat (S2)_, _MachinedFlat (S3)_, _MachinedFlat (S4)_ }
2. Extraction of Part-Related Design Feature Information. From Figure 9, the relevant part design feature information can be obtained: the heat treatment applied to the part is aging treatment, the material is HT200, and the production type is mass production. Based on this, an assertion formula set (APD) is constructed to represent the relationships between the part and its associated design features. \(A_{PD}\) = { _Parts (CP)_, _hasPT (Lb)_, _isPMof (Gcr)_, _isHTbf (Na)_, _isITbf (f)_ }
3. Extraction of Machined Surface-Related Design Feature Information. From Figure 5, the relevant machined surface design feature information can be obtained. Taking  
Figure 8: Algorithm for decision-making on planar machining process of box-type components. surface S1 as an example: basic dimension: 80 mm; length: 142 mm; width: 52 mm; accuracy class: grade 8; surface roughness: 1.6 \(\upmu\)m; geometrical tolerance constraint: flatness. Other machined surfaces have similar characteristics. Based on this, an assertion formula set (AFD) is constructed to represent the relationships between the machined surface and its design features. \(\mathbf{A_{FD}}\) = {_Value_Of_Ra (S1, 1.6), Value_Of_Ra (S2, 6.3), Value_Of_Ra (S3, 0.8), Value_Of_Ra (S4, 6.3), Value_Of_SBD (S1, 80), Value_Of_SBD (S2, 80), Value_Of_SBD (S3, 58), Value_Of_SBD (S4, 38), Value_SL (S1, 142), Value_SL (S2, 30), Value_SL (S3, 45), Value_SL (S4, 30), Value_SW (S1, 69), Value_SW (S2, 30), Value_SW (S3, 45), Value_SW (S4, 30), hasFPT(S1,FN), hasFPT(S2,PA), hasFPT (S3,SQ), hasFPT (S4,SQ), Value_TG(S1, 7), Value_TG (S2, 8), Value_TG (S3, 11), Value_TG (S4, 11) )_
4. The machining process information, machining scheme for the machined surface, and process dimension parameters for box-type parts are determined based on key attributes such as material, heat treatment, production type, and the machined surface characteristics, including dimensions, accuracy class, and geometrical tolerances. Utilizing this information, an ontology-based planar machining process model for box-type parts is developed, as illustrated in Figure 10. By constructing SWRL inference rules and integrating the assertion formula sets APS, APD, and AFD, the machining process information, machining scheme for the machined surface, and process dimension parameters are inferred, as shown in Figure 11. The results are systematically organized and presented in Tables 6-8. The inferred results align with those obtained using traditional methods, such as consulting relevant international standards and manual calculations [32; 36]. \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline
**Production** & **Part** & **Heat** & **Casting** & **Machining** & **Tolerance** & **Grade of** \\
**Type** & **Material** & **Treatment** & **Method** & **Grade** & **Blank Dimensions** \\ \hline \multirow{3}{*}{\
\begin{tabular}{c} Large \\ Quantities \\ \end{tabular} } & \multirow{3}{*}{HT200} & \multirow{3}{*}{
\begin{tabular}{c} Aging \\ Treatment \\ \end{tabular} } & Machine & \multirow{3}{*}{\(10\)} & \multirow{3}{*}{\(G\)} \\  & & & Molding of \\  & & & Stand & & & \\ \cline{1-1}  & & & Casting & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Gearbox machining process information.