Hostname: page-component-cd9895bd7-jkksz Total loading time: 0 Render date: 2024-12-26T04:26:04.388Z Has data issue: false hasContentIssue false

An Exploratory Study Comparing CAD Tools and Working Styles for Implementing Design Changes

Published online by Cambridge University Press:  26 July 2019

Vrushank Shripad Phadnis*
Affiliation:
Massachusetts Institute of Technology;
Kevin Alfonso Leonardo
Affiliation:
Massachusetts Institute of Technology;
David Robert Wallace
Affiliation:
Massachusetts Institute of Technology;
Alison Louise Olechowski
Affiliation:
University of Toronto
*
Contact: Phadnis, Vrushank Shripad, Massachusetts Institute of Technology, Mechanical Engineering, Canada, vphadnis@mit.edu

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

This paper presents the findings of a preliminary study comparing implementation of design changes using various computer-aided design (CAD) working styles. Our study compares individuals’ and pairs’ completion of a series of changes to a toy car CAD model. We discuss the results in terms of productivity and value added ratio, derived from time-based quantitative data. We also discuss qualitative findings acquired through post-study surveys. Overall, our findings suggest that pairs were less efficient than individual designers due to overheads like communication, history dependency and complex couplings within the CAD model tree. However, it is also noteworthy that within each pair the lead participant's performance was at par with individual participants. Lastly, we also discuss behaviors and patterns that emerge as unique to the synchronous collaborative environment, motivating future work.

Type
Article
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
© The Author(s) 2019

References

Andreadis, G., Fourtounis, G. and Bouzakis, K.D. (2015), “Collaborative design in the era of cloud computing”, Advances in Engineering Software, Elsevier Ltd, Vol. 81 No. C, pp. 6672.Google Scholar
Bucciarelli, L. and Kuhn, S. (1997), “Engineering education and engineering practise: Improving the fit”, Between Craft and Science: Technical Work in the United States.Google Scholar
Chulvi, V., Mulet, E., Felip, F. and García-García, C. (2017), “The effect of information and communication technologies on creativity in collaborative design”, Research in Engineering Design, Vol. 28 No. 1, pp. 723.Google Scholar
Eves, K., Salmon, J., Olsen, J. and Fagergren, F. (2018), “A comparative analysis of computer-aided design team performance with collaboration software”, Computer-Aided Design and Applications, Vol. 4360, pp. 112.Google Scholar
Häggman, A., Tsai, G., Elsen, C., Honda, T. and Yang, M.C. (2015), “Connections Between the Design Tool, Design Attributes, and User Preferences in Early Stage Design”, Journal of Mechanical Design, Vol. 137 No. 7, p. 071101.Google Scholar
Holyoak, V.L., Red, E. and Jensen, G. (2014), “Effective Collaboration through Multi user CAx by Implementing New Methods of Product Specification and Management”, Computer-Aided Design and Applications, Vol. 11 No. 5, pp. 560567.Google Scholar
Li, W.D., Lu, W.F., Fuh, J.Y.H. and Wong, Y.S. (2005), “Collaborative computer-aided design—research and development status”, Computer-Aided Design, Vol. 37 No. 9, pp. 931940.Google Scholar
Libardi, E.C., Dixon, J.R. and Simmons, M.K. (1988), “Computer environments for the design of mechanical assemblies: A research review”, Engineering with Computers, Vol. 3 No. 3, pp. 121136.Google Scholar
Martins, L.L., Gilson, L.L. and Maynard, M.T. (2004), “Virtual teams: What do we know and where do we go from here?”, Journal of Management, Vol. 30 No. 6, pp. 805835.Google Scholar
McComb, C., Cagan, J. and Kotovsky, K. (2016), “Optimizing design teams based on problem properties: Computational team simulations and an applied empirical test”, Submitted to Journal of Mechanical Design, Vol. 139 No. April, available at:https://doi.org/10.1115/1.4035793.Google Scholar
Ostergaard, K.J. and Summers, J.D. (2009), “Development of a systematic classification and taxonomy of collaborative design activities”, Journal of Engineering Design, Vol. 20 No. 1, pp. 5781.Google Scholar
Robertson, B.F. and Radcliffe, D.F. (2009), “Impact of CAD tools on creative problem solving in engineering design”, CAD Computer Aided Design, Elsevier Ltd, Vol. 41 No. 3, pp. 136146.Google Scholar
Stone, B., Salmon, J., Eves, K., Killian, M., Wright, L., Oldroyd, J., Gorrell, S., et al. (2017), “A multi-user computer-aided design competition: experimental findings and analysis of team-member dynamics”, Journal of Computing and Information Science in Engineering, Vol. 17 No. 3, p. 031003.Google Scholar
Stone, B., Salmon, J.L., Hepworth, A.I., Red, E., Killian, M., La, A., Pedersen, A., et al. (2017), “Methods for determining the optimal number of simultaneous contributors for multi-user CAD parts”, Computer-Aided Design and Applications, Vol. 14 No. 5, pp. 610621.Google Scholar
Woo, T. (2014), “The Ease of Agile Development in Cloud-Based CAD”, Vol. 9, available at: www.aberdeen.com.Google Scholar
Wu, D., Terpenny, J. and Schaefer, D. (2017), “Digital design and manufacturing on the cloud: A review of software and services”, Artificial Intelligence for Engineering Design, Analysis and Manufacturing: AIEDAM, Vol. 31 No. 1, pp. 104118.Google Scholar