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Frontiers of Engineering Management

Front. Eng
RESEARCH ARTICLE
Identifying subassemblies and understanding their functions during a design review in immersive and non-immersive virtual environments
Fanika LUKAČEVIĆ1, Stanko ŠKEC2(), Peter TÖRLIND3, Mario ŠTORGA4
1. Faculty of Mechanical Engineering and Naval Architecture, University of Zagreb, Ivana Lučića 5, 10 000 Zagreb, Croatia
2. Faculty of Mechanical Engineering and Naval Architecture, University of Zagreb, Ivana Lučića 5, 10 000 Zagreb, Croatia; DTU Management, Technical University of Denmark, Kongens Lyngby, Denmark
3. Department of Business Administration, Technology and Social Sciences, Luleå University of Technology, Luleå, Sweden
4. Faculty of Mechanical Engineering and Naval Architecture, University of Zagreb, Ivana Lučića 5, 10 000 Zagreb, Croatia; Department of Business Administration, Technology and Social Sciences, Luleå University of Technology, Luleå, Sweden
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Abstract

Design review (DR) is a product development (PD) activity used to inspect the technical characteristics of a design solution. Immersive virtual reality (IVR) technology enables the presentation of spatial information and interaction with 3D CAD models inside an immersive virtual environment (IVE). Such capabilities have shown the potential to mitigate the cognitive load needed for the visual perception of spatial information and, consequently, enhance design understanding and DR performance. Thus, an increasing number of studies have explored the effect of IVR technology on DR activities in different domains. However, determining when the implementation of IVR technology rather than a conventional user interface for DRs in mechanical engineering PD projects will be beneficial remains unclear. Hence, a conceptual DR experimental study was conducted to investigate the differences in the ability of engineering students to identify mechanisms and understand their functions when a design solution for a technical system is presented in an IVE by IVR technology and in a non-immersive virtual environment (nIVE) by a conventional user interface (monitor display, keyboard, and mouse). Data were collected by performing DR tasks and having participants complete a prior experience questionnaire, presence questionnaire, and mental rotations test. Findings of the study indicate that IVR does not support an enhanced ability of engineering students to identify mechanisms and understand their functions compared with a conventional user interface.
Keywords design review      virtual environment      virtual reality      mechanism      function     
Corresponding Author(s): Stanko ŠKEC   
Just Accepted Date: 05 March 2020   Online First Date: 02 April 2020   
 Cite this article:   
Fanika LUKAČEVIĆ,Stanko ŠKEC,Peter TÖRLIND, et al. Identifying subassemblies and understanding their functions during a design review in immersive and non-immersive virtual environments[J]. Front. Eng, 02 April 2020. [Epub ahead of print] doi: 10.1007/s42524-020-0099-z.
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http://journal.hep.com.cn/fem/EN/10.1007/s42524-020-0099-z
http://journal.hep.com.cn/fem/EN/Y/V/I/0
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Articles by authors
Fanika LUKAČEVIĆ
Stanko ŠKEC
Peter TÖRLIND
Mario ŠTORGA
Article Design domain Applicationa Participantsb Design solutionc
Satter and Butler (2015) engineering ED, SP EE, RS machine unit (IV)
Wolfartsberger (2019) engineering ED EE power unit (III)
Rigutti et al. (2018) architectural ED RS corridor (IV)
de Casenave and Lugo (2017) engineering ED RS cube assembly
Paes et al. (2017) architectural SP EE entrance hall (IV)
Berg and Vance (2017) engineering UIE EE vehicle (III)
Freeman et al. (2016) engineering DC S gearbox (II)
Maftei and Harty (2016) construction DC EE hospital room (IV)
Liu et al. (2014) construction DC EE energy retrofit (IV)
Satter and Butler (2012) engineering ED, SP S, EE ship (III)
Vora et al. (2001) engineering ED S aircraft (IV)
Dunston et al. (2010) architectural L O hospital room (IV)
Bassanino et al. (2010) construction L O bathroom (IV)
Mengoni et al. (2009) industrial DC EE shower (III)
Germani et al. (2009) engineering DC EE shower, washing machine (III)
Schnabel and Kvan (2003) architectural SP S cube assembly
Whyte et al. (2002) construction UIE EE building (IV)
Banerjee et al. (2002) engineering DC EE vehicle (III)
Tab.1  Overview of the literature that has researched how IVR technology supports DR activities
Fig.1  Driving mode model.
Fig.2  Folded mode model.
Fig.3  Experimental layout.
Fig.4  IVE with associated tools.
Fig.5  Experimental procedure.
DR experience (time) 0 1–3 4–6 7–9 ≥10
Number of participants 21 7 5 2 5
IVR experience (min) 0 <5 5–15 15–60 150–210 780
Number of participants 23 3 6 4 3 1
Tab.2  Prior experience
Fig.6  Participant identifying the mechanism for adjusting the steering bar height in the IVE.
Fig.7  Participant identifying the mechanism for adjusting the steering bar height in the nIVE.
Fig.8  Correctly identified adjustment mechanisms.
Fig.9  Linear regression of presence–adjustment mechanisms.
Fig.10  Linear regression of presence–confidence.
Educational background ME ID SEE PD
Ncam 3.0±0.5 3.4±0.7 2.0±0.0 3.6±0.8
Year of study 1 2 3 4 5
Ncam 2.0±0.0 2.8±0.4 3.5±0.7 3.4±0.8 3.3±0.8
Number of DRs 0 1–3 4–6 7–9 ≥10
Ncam 3.1±0.6 2.9±0.5 4.2±0.7 1.7±0.5 3.0±1.0
CAD skills None Limited Basic Intermediate Advanced
Ncam 2.0±0.5 3.0±0.8 3.2±0.5 3.5±0.8 3.8±0.8
Seat adjustments 0 1–5 6–10 11–30 ≥30
Ncam - 2.8±0.4 3.4±0.5 3.1±0.9 3.5±0.8
Steering bar adjustments 0 1–5 6–10 11–30 ≥30
Ncam 3.1±0.3 3.4±0.9 2.7±1.0 2.9±1.4 3.4±0.7
Tab.3  Relationship between the number of correctly identified adjustment mechanisms and prior experience aspects
Fig.11  Participant identifying a folding step in the IVE.
Fig.12  Participant identifying a folding step in the nIVE.
Fig.13  Correctly identified folding steps.
Fig.14  Linear regression of presence–folding steps.
Fig.15  Linear regression of presence–confidence.
Educational background ME ID SEE PD
Ncfs 4.0±1.3 4.3±1.0 3.5±0.5 4.1±1.1
Year of study 1 2 3 4 5
Ncfs 4.0±0.0 3.0±0.7 4.3±1.0 4.1±1.3 4.7±0.5
Number of DRs 0 1–3 4–6 7–9 ≥10
Ncfs 3.7±1.3 4.6±0.5 4.6±0.5 4.5±0.5 4.6±0.8
CAD skills None Limited Basic Intermediate Advanced
Ncfs 2.3±1.4 4.0±0.8 3.9±1.1 4.4±1.0 4.8±0.4
Number of vehicles folded 0 1–5 6–10 11–30 ≥30
Ncfs 3.3±2.4 3.7±1.3 4.2±1.1 4.4±0.5 3.6±1.3
Tab.4  Relationship between the number of correctly identified folding steps and prior experience aspects
Fig.16  Functional errors (left—Error 1, middle—Error 2, right—Error 3).
Fig.17  Participant detecting an error in the IVE.
Fig.18  Participant detecting an error in the nIVE.
1 M Aust, M de Clerk, R Blach, M Dangelmaier (2011). Towards a holistic workflow pattern for using VR for design decisions: Learning from other disciplines. In: ASME 2011 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers Digital Collection, 1463–1470
2 P Banerjee, G M Bochenek, J M Ragusa (2002). Analyzing the relationship of presence and immersive tendencies on the conceptual design review process. Journal of Computing and Information Science in Engineering, 2(1): 59–64
https://doi.org/10.1115/1.1486218
3 M Bassanino, K C Wu, J Yao, F Khosrowshahi, T Fernando, J Skjærbæk (2010). The impact of immersive virtual reality on visualisation for a design review in construction. In: Proceedings of the 14th International Conference on Information Visualisation. IEEE, 585–589
4 L P Berg, J M Vance (2017). An industry case study: Investigating early design decision making in virtual reality. Journal of Computing and Information Science in Engineering, 17(1): 011001
https://doi.org/10.1115/1.4034267
5 S K Chandrasegaran, K Ramani, R D Sriram, I Horváth, A Bernard, R F Harik, W Gao (2013). The evolution, challenges, and future of knowledge representation in product design systems. Computer-Aided Design, 45(2): 204–228
https://doi.org/10.1016/j.cad.2012.08.006
6 Q Chen, R Weidner, S Vossel, P H Weiss, G R Fink (2012). Neural mechanisms of attentional reorienting in three-dimensional space. Journal of Neuroscience, 32(39): 13352–13362
https://doi.org/10.1523/JNEUROSCI.1772-12.2012 pmid: 23015426
7 C C P Chu, T H Dani, R Gadh (1998). Evaluation of virtual reality interface for product shape designs. IIE Transactions, 30(7): 629–643
https://doi.org/10.1080/07408179808966507
8 J Q Coburn, I Freeman, J L Salmon (2017). A review of the capabilities of current low-cost virtual reality technology and its potential to enhance the design process. Journal of Computing and Information Science in Engineering, 17(3): 031013
https://doi.org/10.1115/1.4036921
9 C Cruz-Neira, D J Sandin, T A DeFanti (1993). Surround-screen projection-based virtual reality: The design and implementation of the CAVE. In: Proceedings of the 20th Annual Conference on Computer Graphics and Interactive Techniques, 135–142
10 L de Casenave, J E Lugo (2017). Design review using virtual reality enabled CAD. In: Proceedings of the ASME 2017 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. Cleveland: American Society of Mechanical Engineers Digital Collection, 1–11
11 G E Dieter, L C Schmidt (2012). Engineering Design. 5th ed. New York: The McGraw-Hill Higher Education
12 P S Dunston, L L Arns, J D McGlothlin (2010). Virtual reality mock-ups for healthcare facility design and a model for technology hub collaboration. Journal of Building Performance Simulation, 3(3): 185–195
https://doi.org/10.1080/19401490903580742
13 C Eckert, A Ruckpaul, T Alink, A Albers (2012). Variations in functional decomposition for an existing product: Experimental results. Artificial Intelligence for Engineering Design, Analysis and Manufacturing, 26(2): 107–128
https://doi.org/10.1017/S0890060412000029
14 D Faas, Q Bao, D D Frey, M C Yang (2014). The influence of immersion and presence in early stage engineering designing and building. Artificial Intelligence for Engineering Design, Analysis and Manufacturing, 28(2): 139–151
https://doi.org/10.1017/S0890060414000055
15 I J Freeman, J L Salmon, J Q Coburn (2016). CAD integration in virtual reality design reviews for improved engineering model interaction. In: ASME International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers Digital Collection
16 P George, A Kemeny, F Colombet, F Merienne, J R Chardonnet, I M Thouvenin (2014). Evaluation of smartphone-based interaction techniques in a CAVE in the context of immersive digital project review. In: The Engineering Reality of Virtual Reality. International Society for Optics and Photonics, 9012: 901203
17 M Germani, M Mengoni, M Peruzzini (2009). Metric-based approach for VR technology evaluation in styling product design. In: Proceedings of the ASME 2009 International Design Engineering Technical Conferences & Computers and Information in Engineering Conference. American Society of Mechanical Engineers Digital Collection, 1325–1339
18 R Hannah, S Joshi, J D Summers (2012). A user study of interpretability of engineering design representations. Journal of Engineering Design, 23(6): 443–468
https://doi.org/10.1080/09544828.2011.615302
19 T Hartmann, W Wirth, H Schramm, C Klimmt, P A Vorderer, A Gysbers, S Böcking, N Ravaja, J Laari, T Saari, F R Gouveia, A Sacau (2015). The Spatial Presence Experience Scale (SPES): A short self-report measure for diverse media settings. Journal of Media Psychology, 28(1): 1–15
https://doi.org/10.1027/1864-1105/a000137
20 C Hendrix, W Barfield (1996). Presence within virtual environments as a function of visual display parameters. Presence: Teleoperators & Virtual Environments, 5(3): 274–289
https://doi.org/10.1162/pres.1996.5.3.274
21 A Heydarian, J P Carneiro, D Gerber, B Becerik-Gerber, T Hayes, W Wood (2015). Immersive virtual environments versus physical built environments: A benchmarking study for building design and user-built environment explorations. Automation in Construction, 54: 116–126
https://doi.org/10.1016/j.autcon.2015.03.020
22 V Hubka, W E Eder (1988). Theory of Technical Systems: A Total Concept Theory for Engineering Design. Berlin: Springer-Verlag
23 G S Hubona, G W Shirah, D G Fout (1997). The effects of motion and stereopsis on three-dimensional visualization. International Journal of Human-Computer Studies, 47(5): 609–627
https://doi.org/10.1006/ijhc.1997.0154 pmid: 11541533
24 Igroup (2019). Igroup Presence Questionnaire (IPQ)
25 L N Kalisperis, K Muramoto, B Balakrishnan, D Nikolic, N Zikic (2002). Evaluating relative impact of virtual reality system variables on architectural design comprehension and presence: A variable-centered approach using fractional factorial experiment. In: Proceedings of the 24th Education and Research in Computer Aided Architectural Design in Europe (eCAADe). Volos, Greece, 66–73
26 J Lessiter, J Freeman, E Keogh, J Davidoff (2001). A cross-media presence questionnaire: The ITC-sense of presence inventory. Presence: Teleoperators & Virtual Environments, 10(3): 282–297
https://doi.org/10.1162/105474601300343612
27 Y F Liu, J Lather, J Messner (2014). Virtual reality to support the integrated design process: A retrofit case study. In: International Conference on Computing in Civil and Building Engineering, 801–808
28 M Lombard, T Ditton (1997). At the heart of it all: The concept of presence. Journal of Computer-Mediated Communication, 3(2): JCMC321
https://doi.org/10.1111/j.1083-6101.1997.tb00072.x
29 M Lombard, T B Ditton, L Weinstein (2009). Measuring presence: The temple presence inventory. In: Proceedings of the 12th Annual International Workshop on Presence. Los Angeles, 1–15
30 L Maftei, C Harty (2016). Challenging design perceptions in immersive virtual reality environments? In: Proceedings of the 32nd Annual ARCOM Conference, 113–122
31 A F Mckenna, W Chen, T W Simpson (2008). Exploring the impact of virtual and physical dissection activities on students’ understanding of engineering design principles. In: Proceedings of the ASME 2008 International Design Engineering Technical Conferences & Computers and Information in Engineering Conference. American Society of Mechanical Engineers Digital Collection, 359–368
32 M Mengoni, M Peruzzini, M Germani (2009). The impact of virtual environments on human collaboration in product design. In: Proceedings of the 17th International Conference on Engineering Design—vol. 9, Human Behavior in Design. Palo Alto, CA, 57–68
33 N S Newcombe, T F Shipley (2015). Thinking about spatial thinking: New typology, new assessments. In: Gero J S, ed. Studying Visual and Spatial Reasoning for Design Creativity. Dordrecht: Springer, 179–192
34 K J Ostergaard, W Wetmore, J D Summers (2003). A methodology for the study of the effects of communication method on design review effectiveness. In: Proceedings of ASME 2003 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers Digital Collection, 383–390
35 D Paes, E Arantes, J Irizarry (2017). Immersive environment for improving the understanding of architectural 3D models: Comparing user spatial perception between immersive and traditional virtual reality systems. Automation in Construction, 84: 292–303
https://doi.org/10.1016/j.autcon.2017.09.016
36 G Pahl, W Beitz, J Feldhusen, K H Grote (2007). Engineering Design: A Systematic Approach (3rd ed). London: Springer-Verlag
37 M Peters, B Laeng, K Latham, M Jackson, R Zaiyouna, C Richardson (1995). A redrawn Vandenberg and Kuse mental rotations test: Different versions and factors that affect performance. Brain and Cognition, 28(1): 39–58
https://doi.org/10.1006/brcg.1995.1032 pmid: 7546667
38 S Rigutti, M Stragà, M Jez, G Baldassi, A Carnaghi, P Miceu, C Fantoni (2018). Don’t worry, be active: How to facilitate the detection of errors in immersive virtual environments. PeerJ, 6: e5844
https://doi.org/10.7717/peerj.5844 pmid: 30397547
39 M A Robinson (2016). Quantitative research principles and methods for human-focused research in engineering design. In: Cash P, Stanković T, Štorga M, eds. Experimental Design Research: Exploring Complex Design Activity. Cham, Switzerland: Springer, 41–64
40 K Satter, A Butler (2015). Competitive usability analysis of immersive virtual environments in engineering design review. Journal of Computing and Information Science in Engineering, 15(3): 031001
https://doi.org/10.1115/1.4029750
41 K M Satter, A C Butler (2012). Finding the value of immersive, virtual environments using competitive usability analysis. Journal of Computing and Information Science in Engineering, 12(2): 024504
https://doi.org/10.1115/1.4005722
42 M A Schnabel, T Kvan (2003). Spatial understanding in immersive virtual environments. International Journal of Architectural Computing, 1(4): 435–448
https://doi.org/10.1260/147807703773633455
43 T Schubert, F Friedmann, H Regenbrecht (2001). The experience of presence: Factor analytic insights. Presence: Teleoperators & Virtual Environments, 10(3): 266–281
https://doi.org/10.1162/105474601300343603
44 M Slater, V Linakis, M Usoh, R Kooper (1995). Immersion, presence, and performance in virtual environments: An experiment with tri-dimensional chess. In: Proceedings of ACM Symposium on Virtual Reality Software and Technology (VRST). New York: ACM Press, 163–172
45 M L Spence, P E Dux, D H Arnold (2016). Computations underlying confidence in visual perception. Journal of Experimental Psychology: Human Perception and Performance, 42(5): 671–682
https://doi.org/10.1037/xhp0000179 pmid: 26594876
46 L Stankov, S Kleitman, S A Jackson (2014). Measures of the trait of confidence. In: Boyle G J, Saklofske D H, Matthews G, eds. Measures of Personality and Social Psychological Constructs. Academic Press, 158–189
47 K M Stanney, R R Mourant, R S Kennedy (1998). Human factors issues in virtual environments: A review of the literature. Presence: Teleoperators & Virtual Environments, 7(4): 327–351
https://doi.org/10.1162/105474698565767
48 J Steuer (1992). Defining virtual reality: Dimensions determining telepresence. Journal of Communication, 42(4): 73–93
https://doi.org/10.1111/j.1460-2466.1992.tb00812.x
49 I E Sutherland (1968). A head-mounted three dimensional display. In: Proceedings of the Fall Joint Computer Conference, part I, 757–764
50 S Thimmaiah, K Phelan, J D Summers (2017). An experimental study on the influence that failure number, specialization, and controls have on confidence in predicting system failures. Journal of Mechanical Design, 139(1): 011102
https://doi.org/10.1115/1.4034789
51 J Vora, S Nair, A K Gramopadhye, B J Melloy, E Medlin, A T Duchowski, B G Kanki (2001). Using virtual reality technology to improve aircraft inspection performance: Presence and performance measurement studies. In: Proceedings of the Human Factors and Ergonomics Society Annual Meeting. Los Angeles, CA: SAGE Publications, 45(27): 1867–1871
https://doi.org/10.1177/154193120104502703
52 J Wann, M Mon-Williams (1996). What does virtual reality NEED? Human factors issues in the design of three-dimensional computer environments. International Journal of Human-Computer Studies, 44(6): 829–847
53 K Watanuki (2010). Development of virtual reality-based universal design review system. Journal of Mechanical Science and Technology, 24(1): 257–262
https://doi.org/10.1007/s12206-009-1156-z
54 J Whyte, D Bouchlaghem, T Thorpe (2002). IT implementation in the construction organization. Engineering, Construction and Architectural Management, 9(5–6): 371–377
https://doi.org/10.1108/eb021231
55 B G Witmer, M J Singer (1998). Measuring presence in virtual environments: A presence questionnaire. Presence: Teleoperators & Virtual Environments, 7(3): 225–240
https://doi.org/10.1162/105474698565686
56 J Wolfartsberger (2019). Analyzing the potential of virtual reality for engineering design review. Automation in Construction, 104: 27–37
https://doi.org/10.1016/j.autcon.2019.03.018
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