The usage of CAD (Computer-Aided Design) tools is important in the later stages of product development. With CAD tools, the design team can create digital models of the product. Traditional CAD (single-user CAD) tools enable work from one PC and one user at a time on a single CAD model. This restriction makes collaboration more difficult. The development of cloud computing has enabled the creation of multi-user CAD tools. One of the leading multi-user CAD tools is Onshape, a PTC company product that allows more than one user to work on a CAD model simultaneously. Onshape also enables tracking of user activity using the Audit Trail module. For this master’s thesis, a dataset of CAD activity from a student association involved in rocket design is used. During the tracking period, 18,453,947 CAD activity were recorded from 491 users. At the beginning of this work, a survey of the existing literature related to the analysis of CAD activities was conducted, which greatly helped define the approach to data analysis. The analysis of CAD activity is divided into three parts. The first part involves grouping users and Onshape documents based on the number of recorded timestamps. Each created group is analyzed separately. In the second part, GMM (Gaussian Mixture Model) and K-Means clustering algorithms are used to generate clusters of documents and users. Clustering of data for CAD activity is performed using each algorithm, and the results are compared. Each approach to data grouping provides different insights into the structure of CAD activity. The use of different clustering algorithms results in the creation of some clusters that differ in their approach to CAD activity. The last part is the analysis of user collaboration. After analyzing the dynamics of the collaboration network, the existence of sub-teams was established, but only on a monthly basis.
