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Engineering designers’ CAD performance when modelling from isometric and orthographic projections

Published online by Cambridge University Press:  16 May 2024

Fanika Lukačević ,
Niccolò Becattini  and
Stanko Škec
Fanika Lukačević*
Affiliation:
University of Zagreb Faculty of Mechanical Engineering and Naval Architecture, Croatia Politecnico di Milano, Italy
Niccolò Becattini
Affiliation:
Politecnico di Milano, Italy
Stanko Škec
Affiliation:
University of Zagreb Faculty of Mechanical Engineering and Naval Architecture, Croatia
*
fanika.lukacevic@fsb.hr

Abstract

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The presented study investigates differences in engineering designers' CAD performance when modelling from two types of projections in technical drawings – isometric and orthographic. The results revealed significant differences in the percentage of correctly replicated components' size and shape, indicating better CAD outcomes when generating CAD models from the orthographic projection. In addition, a comparison of duration, as well as the number and type of sketch entities, sketch relations, and CAD features, showed that CAD modelling processes were similar in both conditions.

Keywords

computer-aided design (CAD)performance indicatorsdesign representation
Type
Design Methods and Tools
Information
Proceedings of the Design Society , Volume 4: DESIGN 2024 , May 2024 , pp. 653 - 662
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), 2024.

References

Aranburu, A., Cotillas, J., Justel, D., Contero, M. and Camba, J.D. (2022), “How Does the Modeling Strategy Influence Design Optimization and the Automatic Generation of Parametric Geometry Variations?”, Computer-Aided Design, Elsevier, Vol. 151, p. 103364, https://dx.doi.org/10.1016/J.CAD.2022.103364.Google Scholar
Bhavnani, S.K., John, B.E. and Flemming, U. (1999), “The strategic use of CAD: An empirically inspired, theory-based course”, Conference on Human Factors in Computing Systems - Proceedings, No. May, pp. 183–190, https://dx.doi.org/10.1145/302979.303036.CrossRefGoogle Scholar
Cardone, A., Gupta, S.K. and Karnik, M. (2003), “A survey of shape similarity assessment algorithms for product design and manufacturing applications”, Journal of Computing and Information Science in Engineering, Vol. 3 No. 2, pp. 109–118, https://dx.doi.org/10.1115/1.1577356.CrossRefGoogle Scholar
Chester, I. (2007), “Teaching for CAD expertise”, International Journal of Technology and Design Education, Vol. 17 No. 1, pp. 23–35, https://dx.doi.org/10.1007/s10798-006-9015-z.CrossRefGoogle Scholar
Company, P., Contero, M., Otey, J. and Plumed, R. (2015), “Approach for developing coordinated rubrics to convey quality criteria in MCAD training”, CAD Computer Aided Design, Elsevier Ltd, Vol. 63, pp. 101–117, https://dx.doi.org/10.1016/j.cad.2014.10.001.Google Scholar
Company, P., Naya, F., Contero, M. and Camba, J.D. (2020), “On the role of geometric constraints to support design intent communication and model reusability”, Computer-Aided Design and Applications, Vol. 17 No. 1, pp. 61–76, https://dx.doi.org/10.14733/cadaps.2020.61-76.CrossRefGoogle Scholar
Diwakaran, R.P. and Johnson, M.D. (2012), “Analyzing the effect of alternative goals and model attributes on CAD model creation and alteration”, Computer-Aided Design, Elsevier, Vol. 44 No. 4, pp. 343–353, https://dx.doi.org/10.1016/J.CAD.2011.11.003.Google Scholar
Garland, A.P. and Grigg, S.J. (2019), “Evaluation of humans and software for grading in an engineering 3D CAD course”, ASEE Annual Conference and Exposition, Conference Proceedings, https://dx.doi.org/10.18260/1-2--32764.CrossRefGoogle Scholar
Gopsill, J., Snider, C., Shi, L. and Hicks, B. (2016), “Computer aided design user interaction as a sensor for monitoring engineers and the engineering design process”, Proceedings of International Design Conference, DESIGN, Vol. DS 84, pp. 1707–1718.Google Scholar
Hamade, R.F. and Artail, H.A. (2008), “A study of the influence of technical attributes of beginner CAD users on their performance”, CAD Computer Aided Design, Vol. 40 No. 2, pp. 262–272, https://dx.doi.org/10.1016/j.cad.2007.11.001.CrossRefGoogle Scholar
Kirstukas, S.J. (2016), “Development and evaluation of a computer program to assess student CAD models”, ASEE Annual Conference and Exposition, Conference Proceedings, Vol. 2016-June, https://dx.doi.org/10.18260/p.26781.CrossRefGoogle Scholar
Lieu, D.K. and Sorby, S. (2016), Visualization, Modeling, and Graphics for Engineering Design, Vol. 148, Cengage Learning.Google Scholar
Oti, A. and Crilly, N. (2021), “Immersive 3D sketching tools: Implications for visual thinking and communication”, Computers and Graphics, Elsevier Ltd, Vol. 94 No. 2021, pp. 111–123, https://dx.doi.org/10.1016/j.cag.2020.10.007.Google Scholar
Phadnis, V., Arshad, H., Wallace, D. and Olechowski, A. (2021), “Are two heads better than one for computer-aided design?”, Journal of Mechanical Design, Transactions of the ASME, Vol. 143 No. 7, https://dx.doi.org/10.1115/1.4050734.CrossRefGoogle Scholar
Renu, R. and Mocko, G. (2016), “Retrieval of solid models based on assembly similarity”, Computer-Aided Design & Applications, Vol. 13 No. 5, pp. 628–636, https://dx.doi.org/10.1080/16864360.2016.1150708.CrossRefGoogle Scholar
Rosso, P., Gopsill, J., Burgess, S. and Hicks, B. (2021), “Investigating and characterising variability in CAD modelling and its potential impact on editability: An exploratory study”, Computer-Aided Design and Applications, Vol. 18 No. 6, pp. 1306–1326, https://dx.doi.org/10.14733/cadaps.2021.1306-1326.CrossRefGoogle Scholar
Rynne, A. and Gaughran, W. (2008), “Cognitive modeling strategies for optimum design intent in parametric modeling (PM)”, Computers in Education Journal, Vol. 18 No. 3, pp. 55–68, https://dx.doi.org/10.18260/1-2--2651.Google Scholar
Shi, Y., Du, J. and Zhu, Q. (2020), “The impact of engineering information format on task performance: Gaze scanning pattern analysis”, Advanced Engineering Informatics, Elsevier, Vol. 46 No. July, p. 101167, https://dx.doi.org/10.1016/j.aei.2020.101167.Google Scholar
Steinhauer, H.M. (2012), “Correlation between a student's performance on the mental cutting test and their 3d parametric modeling ability”, Engineering Design Graphics Journal, Vol. 76 No. 3, pp. 44–48.Google Scholar
Sweany, J., Goodrum, P. and Miller, J. (2016), “Analysis of empirical data on the effects of the format of engineering deliverables on craft performance”, Automation in Construction, Elsevier B.V., Vol. 69, pp. 59–67, https://dx.doi.org/10.1016/j.autcon.2016.05.017.Google Scholar