## 2 Related Work  
### Product Structure Modeling  
Product structure modeling involves quantitatively analyzing the relationship between the parts after splitting the product and displaying them in an intuitive and concise way. Researchers have proposed various methods and tools to achieve this, such as the design structure matrix (DSM) [10], node-link diagrams [11], Petri nets [12], and other analytical tools [13]. For more than a decade, the DSM has been a widely used modeling framework across many areas of research because of its conciseness in representation and ease of analysis [14]. In [PERSON]'s review, the DSM can be divided into four types according to different application objects: the component-based DSM, people-based DSM, activity-based DSM, and parameter-based DSM [15,16]. The use of the DSM to model products or system architectures can be traced back to the works of [PERSON] and [PERSON] in the early 1960s, but it was not until 1981 that [PERSON] formally proposed the concept of the DSM [17]. The product DSM is challenging to build because of the large amount of relevant professional knowledge required and the varied interpretations of a product's structural relationships. Product structure modeling usually needs to consider two factors. One is the decomposition granularity of the product, which determines the size of the product structure model. The second is the quantitative evaluation of the correlations among parts, which determines the complexity of the product structure model. For small products with a simple structure, the smallest particle size is often used to decompose them to the part level. For example, [PERSON] et al. completely decomposed a gear oil pump to the part level when establishing a DSM model of a gear oil pump; then, the community identification algorithm was used to realize the module division of the gear oil pump [18]. [PERSON] et al. realized the extraction of 3D model information through the secondary development of 3D modeling software, and established the DSM model based on the extracted product information [19]. For most mechatronic products, the complex product structure results in a huge number of parts. If product structure modeling is decomposed to the part level, the size of the established model will be huge, which is not conducive to the subsequent product module identification. Because of this, the relevant research literature began to focus on reducing the difficulty of modeling and improving the efficiency of modeling. [PERSON] et al. proposed a method for selecting product parts according to the market value and established a structural model of a coffee machine using this method [20]. [PERSON] et al. proposed a method of module division of complex products based on core parts, but the screening method of core parts in this paper is too cumbersome [6]. [PERSON] et al. proposed a pre-modular approach to the structural modeling of mechatronic products. This method divides a product into several small modules in advance, based on an analysis of the physical structure of the product; a structural model of the product is then built on the basis of these small modules [21]. [PERSON] et al. solved the problem of excessive parts by improving the granularity of product decomposition; they established a DSM model of a wind turbine using this method [8]. However, there is no specific principle that can be used to control the decomposition size of products in the literature, only relying on the design experience of engineers, so this method cannot be widely promoted. Some researchers proposed a method of building a product structure model based on product 3D model information extraction [22]. Such methods have great advantages in modeling efficiency and model data objectivity, but the limited product information that can be extracted cannot meet the modeling requirements of diversity. Based on the above analysis, we can divide the mainstream methods used for the structural modeling of mechatronic products into two types.