Technical Paper
Development of automated CAD database and Application on aluminum wheel
2024-04-09
2024-01-2724
As data science technologies are being widely applied on various industries, an importance of data itself increased. A typical manufacturer company has a vast data of products as 3D format but a common problem was that building a database from the 3D data costs much and it is hard to update the database after building by new products developed. In this paper, an automated database building method using CATIA and future probabilities are suggested. An aluminum wheel part was used as an example. An automated logic for extracting design shape features was used and data mining process deployed based on the extracted data. CNN and Auto-Encoder models were used for wheel weight regression and searching similarity in z-space. By using the method of this paper, establishing and analyzing database efficiently were possible with low cost.