Comparing Collaborative Cad Modelling Patterns of High-Performing and Low-Performing Teams

Abstract

The development of cloud-based Computer-aided design (CAD) enabled real-time CAD collaboration between multiple designers. While this technology has great potential to change the way CAD work is done, it is still little explored. This paper presents a case with two high-performing and two low-performing three-member teams monitored with non-invasive methods (log data) during a six-week design project. The results show that high-performing teams focused more on the editing of assembly, while low-performing teams focused on creating and editing a part. Furthermore, high-performing teams tended to perform consecutive deleting actions and to transition to creating and editing classes of CAD actions after performing viewing actions. Two modelling approaches which lead to high-quality CAD models were identified. One approach is characterized by frequent use of transitions between editing and Organizing-Design (collaborative actions) classes, while the other between creating, editing and reversing classes. Presented results allow design teams to gain insight into sequential patterns which led to the generation of a high-quality CAD model and to better understand the CAD modelling process.

Analysis of collaborative CAD user actions in design sprint: insights from an educational setting

“…Furthermore, in terms of CAD actions concerning the action type within the design sprint format, the study found a series of insights that both corroborate and diverge from the existing literature on collaborative CAD usage. Predominantly, a tendency among three out of four observed teams to prioritize the Creating over Editing actions, aligning with Deng et al (2022) data, but diverges from Celjak et al (2023), who suggests that Editing is the most frequent CAD action. This implies that teams predominantly concentrated on generating new features or experimenting with their different aspects, possibly without revising them, taking a more iterative approach for enhanced design.…”

“…The study's objective was to explore CAD usage patterns in design sprint format among four internationally dislocated student teams. It focuses on collaborative CAD usage during online design sprint, comparing team-wise CAD usage through a structured review of relevant literature fosuced on conventional collaborative CAD usage during PBL (Celjak et al, 2023) or case study (Deng et al, 2022) and a two-day analysis.…”

“…In addition to Sadeghi et al's (2016) suggestion that capturing design process information could help to better understand the design process and its challenges to improve designer productivity, collaborative CAD can provide a suitable platform for a non-intrusive collection of data on user action. This data can then be used as a proxy when examining the overall design process, ensuring it does not impact or interfere with both the designer and the CAD modelling process (Celjak et al, 2023). Thus, Gopsill et al (2016) evaluated the potential of providing a non-intrusive approach for the monitoring, and assessment of designers and the engineering design process.…”

“…In contrast to Stone et al's study on a team-based level, in their examination of CAD user actions among collaboratively working pairs, as opposed to individual work, Phadnis et al (2021) found that the pairs demonstrated lower CAD performance and generated CAD models of lower quality. On the other hand, by studying and comparing teams in synchronous and collaborative CAD setups, Celjak et al (2023) compared CAD actions performed by low-performing and high-performing teams. They revealed that low-performing teams leaned towards actions involving creating a part or assembly, editing and deleting parts, and reversing CAD user actions.…”

“…Each data point within the collected dataset includes timestamps, document and tab details, the performing team member, and the CAD user action's name. To ensure accurate analysis, actions not within the study's focus were excluded from the dataset, such as those automatically logged by a CAD system and the multiple recorded actions for only one CAD action (e.g., when a user creates a sketch) (Celjak et al, 2023). The analysis of the acquired dataset was further conducted by using MUCAD-CLF developed by the ReadyLab (Deng et al, 2022).…”