# Automated Assessment Tool for 3D Computer-Aided Design Models
## 2 State of the Art and Related Works
### Comparison Tools in the Literature  
The assessment of similarity in 3D mechanical parts has garnered considerable attention. In a study by [PERSON] et al. [2], previous research on shape similarity techniques was categorized into two groups. The first category focuses solely on geometric similarity, while \begin{table}
\begin{tabular}{c c c} \hline \hline
**Software** & **Comparison Tool** & **Limitations** \\ \hline \multirow{4}{*}{Autodesk AutoCAD (2023)} & “DWG Compare”, & Difficulty in detecting small changes between the different versions of DWG files. \\  & “Revision Cloud” & Limited ability to manage complex changes to assemblies \\  & “Product Compare” and & Limited ability to manage complex changes to assemblies \\ \multirow{2}{*}{Dassault Systems CATIA V5} & “Product Structure & and associations. \\  & Compare” & Detecting small features and part changes is challenging. \\  & & Limited ability to compare advanced geometric or complex parametric models. \\ \multirow{2}{*}{Siemens NX (2022)} & “Model Compare” & Difficulty in dealing with topology changes and structural modifications [14]. \\  & & Reduced accuracy in detecting minor geometric differences between models. \\ \multirow{2}{*}{PTC Creo 11} & “Compare Geometry” & Limited management of changes to the design based on constraints and parameters [15]. \\  & & Limitations in recognizing small geometric and dimensional differences. \\ \multirow{2}{*}{SolidWorks (2024)} & “Compare” & Difficulty in handling major changes in complex assemblies. \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Commercial CAD system comparison tools. the second compares predefined typical features. The former allows for any input data structure, as it compares parts based on geometric data alone. On the other hand, the latter requires more information and feature extraction, such as holes and fillets, but results in less computational load and more reasonable outcomes [16]. Various approaches have been proposed for 3D shape similarity assessment. Some utilize design features as the basis for a semantic design information model, representing 3D CAD models using feature-adjacent attribute graphs (FAAGs) [17]. Structural CAD models, presented as sets of features and characteristic structures, are compared using big-graphs [17]. Similar methods use feature dependency-directed acyclic graphs (FDAGs) [18]. Assembly models are also represented as relational graphs, and their similarity is measured based on compatibility matrices [19]. Signature-based methods, such as shape signature, offer a transferable and understandable model for 3D geometry comparison. Some authors [20] highlight the efficiency of methods generating shape signatures from CAD models. They classify methods into the following six categories based on the CAD information comprising the shape signature: feature-based, spatial function, shape histogram, section image, topological graph, and shape statistics. However, these methods have limitations, particularly the absence of a unique shape signature. Recognizing the importance of both geometrical and topological information for mechanical CAD models, others [21] proposed two shape signatures to describe geometry and topology separately. Another approach, shape distribution, computes a statistical distribution of distances on the object surface for similarity measurement [3]. Despite being geometry-based, this approach may struggle to differentiate parts that are similar in shape but distinct in design features [20]. [PERSON] and [PERSON] [22] introduced a method for comparing 3D CAD assemblies based on shape distribution, considering assembly relationships and part shape dissimilarities. Many works transform the original 3D model into other formats (STEP files, signatures, graphs) for comparison, potentially causing information loss. This transformation alters geometric features, making the identification of identical features challenging. In contrast, [PERSON] et al.