Effective collaboration is crucial for success in complex engineering endeavors, and understanding the collaborative dynamics within virtual teams remains essential. This is because the engineering landscape continues to evolve, particularly with the increasing prevalence of hybrid teams and technology-mediated interactions, there is a pressing need to comprehend the intricacies of virtual collaboration. Furthermore, there is a lack of understanding of how collaborative behaviors may change concerning conversational dynamics and individual perceptions. Therefore, this study seeks to bridge this gap by investigating how actual collaborative dynamics and individual perceptions of collaborative efforts relate to collaborative behaviors in the context of engineering design. Data from experts in Non-Destructive Evaluation (NDE) and Design for Additive Manufacturing (DfAM) working on a multi-objective design in a virtual setting, were analyzed using Spearman's rank-order correlation analysis that revealed intriguing relationships between turn-taking, conversational dominance, and perceived contributions to design success. Further, Hidden Markov Models (HMMs) integrated with interaction Dynamics Notion (IDN) were constructed to delineate the nuanced interaction behaviors of 'unsynchronized' and 'synchronized' groups. Findings from this study highlight the importance of perception-driven synchronization within expert teams, particularly in virtual settings. Future research should focus on developing interventions to promote synchronization in virtual design collaboration, enhancing collaboration dynamics, and minimizing unproductive communication patterns.

Journal paper submitted to ASME Journal of Mechanical Design.

The pace of technological advancements has been rapidly increasing in recent years, with the advent of artificial intelligence, virtual/augmented reality, and other emerging technologies fundamentally changing the way human beings work. The adoption and integration of these advanced technologies necessitate teams with diverse disciplinary expertise, to help teams remain agile in an ever-evolving technological landscape. Significant disciplinary diversity amongst teams, however, can be detrimental to team communication and performance. Additionally, accelerated by the COVID-19 pandemic, the adoption and use of technologies that enable design teams to collaborate across significant geographical distances have become the norm in today's work environments, further complicating communication and performance issues. Little is known about the way in which technology-mediated communication affects the collaborative processes of design. As a first step toward filling this gap, the current work explores the fundamental ways experts from distinct disciplinary backgrounds collaborate in virtual design environments. Specifically, we explore the conversational dynamics between experts from two complementary yet distinct fields: non-destructive evaluation (NDE) and design for additive manufacturing (DFAM). Using Markov modeling, the study identified distinct communicative patterns that emerged during collaborative design efforts. Our findings suggest that traditional assumptions regarding communication patterns and design dynamics may not be applicable to expert design teams working in virtual environments. 

For more detailed information, please refer to this linked journal paper.

The versatility of Additive Manufacturing (AM) has enabled engineers and designers to realize previously impossible geometries. However, the increasing geometric complexities of these components pose a significant challenge for traditional inspection methods. If a part cannot be appropriately inspected costly redesign will be required, or worse fatal flaws and imperfections may not be identified prior to part use. Considering the constraints of inspection techniques early in the design process could help designers make better design decisions. This research aimed to identify and investigate the fundamental relationship between AM parts' geometric features, geometric complexity, and overall inspectability. Upon data collection and rigorous statistical analysis, results suggested that traditionally accepted indicators of geometric complexity, such as lattice structures, do not significantly predict part respectability.

For more detailed information, please refer to this linked conference paper.