John K. Ostrander, Lauren Ryan, Snehal Dhengre, Christopher McComb, T. Simpson, N. Meisel
{"title":"A Comparative Study of Virtual Reality and Computer-Aided Design to Evaluate Parts for Additive Manufacturing","authors":"John K. Ostrander, Lauren Ryan, Snehal Dhengre, Christopher McComb, T. Simpson, N. Meisel","doi":"10.1115/detc2019-97480","DOIUrl":null,"url":null,"abstract":"\n Virtual Reality (VR) has been shown to be an effective assistive tool in the engineering design process, aiding designers in ergonomics studies, data visualization, and manufacturing simulation. Yet there is little research exploring the advantages of VR to assist in the design for the additive manufacturing (DfAM) process. VR may present advantages over traditional computer-aided design (CAD) tools, and these advantages may be more evident as designs become more complex. The following study investigates two types of environments: 1) Immersive Virtual Reality (VR) and 2) Non-Immersive Virtual Reality (CAD) and the advantages that each environment gives to designers to assess parts for additive manufacturing. The two environments are compared to assess potential differences in DfAM decision-making. Participants familiar with DfAM are tasked with evaluating five designs of varying complexity using the Design for Additive Manufacturing Worksheet. Participant scores, evaluation times, and self-reported metrics are recorded and analyzed. Our findings indicate that as part complexity increases, DfAM scores and evaluation times increasingly differ between VR and CAD groups. We found that the VR group evaluates more complex parts at a faster rate, but with a lower accuracy when compared to the CAD group. In evaluating self-reported metrics, both groups were relatively similar; however, the CAD group reported improved confidence in identifying stress concentrations in DfAM parts. Our findings in this research identify VR as a design evaluation tool that enhances evaluation speed which speaks to its efficiency and usability; however, VR in its current form may not present the resolution necessary to identify smaller details when compared to CAD, the more accurate evaluation tool.","PeriodicalId":365601,"journal":{"name":"Volume 2A: 45th Design Automation Conference","volume":"34 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Volume 2A: 45th Design Automation Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1115/detc2019-97480","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
Virtual Reality (VR) has been shown to be an effective assistive tool in the engineering design process, aiding designers in ergonomics studies, data visualization, and manufacturing simulation. Yet there is little research exploring the advantages of VR to assist in the design for the additive manufacturing (DfAM) process. VR may present advantages over traditional computer-aided design (CAD) tools, and these advantages may be more evident as designs become more complex. The following study investigates two types of environments: 1) Immersive Virtual Reality (VR) and 2) Non-Immersive Virtual Reality (CAD) and the advantages that each environment gives to designers to assess parts for additive manufacturing. The two environments are compared to assess potential differences in DfAM decision-making. Participants familiar with DfAM are tasked with evaluating five designs of varying complexity using the Design for Additive Manufacturing Worksheet. Participant scores, evaluation times, and self-reported metrics are recorded and analyzed. Our findings indicate that as part complexity increases, DfAM scores and evaluation times increasingly differ between VR and CAD groups. We found that the VR group evaluates more complex parts at a faster rate, but with a lower accuracy when compared to the CAD group. In evaluating self-reported metrics, both groups were relatively similar; however, the CAD group reported improved confidence in identifying stress concentrations in DfAM parts. Our findings in this research identify VR as a design evaluation tool that enhances evaluation speed which speaks to its efficiency and usability; however, VR in its current form may not present the resolution necessary to identify smaller details when compared to CAD, the more accurate evaluation tool.