Industry use of virtual reality in product design and manufacturing: a survey

Berg, Leif P.; Vance, Judy M.

doi:10.1007/s10055-016-0293-9

Cited by 631 publications

(317 citation statements)

References 28 publications

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“…Within the engineering field, nowadays VR is being effectively used in engineering education [2][3][4][5] since the use of VR presents several advantages, namely: (i) VR allows simulating in real time the use of otherwise unavailable expensive laboratory equipment [6][7][8][9]; (ii) the use of VR avoids potential damages to a real machine caused by students' misuse during practical classes [9]; (iii) VR solves the difficulty of developing practical classes in a real laboratory environment when the groups are overcrowded [10]; (iv) VR improves the prevention of occupational hazards [11][12][13][14][15]; and (v) VR allows the students to interact with complete manufacturing processes, which would be practically impossible otherwise [16][17][18]. This paper deals with didactic virtual resources designed by means of VR systems.…”

Section: Introductionmentioning

confidence: 99%

On the Design of Virtual Reality Learning Environments in Engineering

Vergara

Rubio

Lorenzo

2017

MTI

128

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Currently, the use of virtual reality (VR) is being widely applied in different fields, especially in computer science, engineering, and medicine. Concretely, the engineering applications based on VR cover approximately one half of the total number of VR resources (considering the research works published up to last year, 2016). In this paper, the capabilities of different computational software for designing VR applications in engineering education are discussed. As a result, a general flowchart is proposed as a guide for designing VR resources in any application. It is worth highlighting that, rather than this study being based on the applications used in the engineering field, the obtained results can be easily extrapolated to other knowledge areas without any loss of generality. This way, this paper can serve as a guide for creating a VR application.

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Section: Introductionmentioning

confidence: 99%

On the Design of Virtual Reality Learning Environments in Engineering

Vergara

Rubio

Lorenzo

2017

MTI

128

View full text Add to dashboard Cite

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“…VR software is currently dominated by applications for entertainment and gaming purposes. Existing business or research data visualisation applications tend to be focussed on exploiting the VR environment for representation of spatial data such as engineering drawings, structures and mapping (Berg and Vance, 2016;Boulos et al 2017;Sastry and Boyd, 1998;Seth et al 2011). Within health and medical sciences VR is used for predominantly therapeutic or rehabilitation applications (e.g.…”

Section: Datashield Applications For Data Visualisationmentioning

confidence: 99%

DataSHIELD – New Directions and Dimensions

Wilson

Butters

Avraam

et al. 2017

Data Science Journal

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In disciplines such as biomedicine and social sciences, sharing and combining sensitive individual-level data is often prohibited by ethical-legal or governance constraints and other barriers such as the control of intellectual property or the huge sample sizes. DataSHIELD (Data Aggregation Through Anonymous Summary-statistics from Harmonised Individual-levEL Databases) is a distributed approach that allows the analysis of sensitive individual-level data from one study, and the co-analysis of such data from several studies simultaneously without physically pooling them or disclosing any data.Following initial proof of principle, a stable DataSHIELD platform has now been implemented in a number of epidemiological consortia. This paper reports three new applications of DataSHIELD including application to post-publication sensitive data analysis, text data analysis and privacy protected data visualisation. Expansion of DataSHIELD analytic functionality and application to additional data types demonstrate the broad applications of the software beyond biomedical sciences.

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“…Decision making, job scheduling and human-in-the-loop approaches are expected to constitute a kind of hybrid control systems with a dynamic structure and distributed intelligence capable of meeting industrial needs and rapid market changes [13]. Augmented reality (AR), virtual reality (VR), camera and vision identification services are expected to [14] mimic the human information processing system in order to take advantage of and interpret the ambient industrial environment. Prognostics and prediction processes, anomalies detection and fault diagnosis are expected not only to enable the collection of data, but also to support advanced analytics to extract useful insights with high returns on investments in the manufacturing industry [15].…”

Section: Introductionmentioning

confidence: 99%

Data Management in Industry 4.0: State of the Art and Open Challenges

2019

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Information and communication technologies are permeating all aspects of industrial and manufacturing systems, expediting the generation of large volumes of industrial data. This article surveys the recent literature on data management as it applies to networked industrial environments and identifies several open research challenges for the future. As a first step, we extract important data properties (volume, variety, traffic, criticality) and identify the corresponding data enabling technologies of diverse fundamental industrial use cases, based on practical applications. Secondly, we provide a detailed outline of recent industrial architectural designs with respect to their data management philosophy (data presence, data coordination, data computation) and the extent of their distributiveness. Then, we conduct a holistic survey of the recent literature from which we derive a taxonomy of the latest advances on industrial data enabling technologies and data centric services, spanning all the way from the field level deep in the physical deployments, up to the cloud and applications level. Finally, motivated by the rich conclusions of this critical analysis, we identify interesting open challenges for future research. The concepts presented in this article thematically cover the largest part of the industrial automation pyramid layers. Our approach is multidisciplinary, as the selected publications were drawn from two fields; the communications, networking and computation field as well as the industrial, manufacturing and automation field. The article can help the readers to deeply understand how data management is currently applied in networked industrial environments, and select interesting open research opportunities to pursue.

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Industry use of virtual reality in product design and manufacturing: a survey

Cited by 631 publications

References 28 publications

On the Design of Virtual Reality Learning Environments in Engineering

On the Design of Virtual Reality Learning Environments in Engineering

DataSHIELD – New Directions and Dimensions

Data Management in Industry 4.0: State of the Art and Open Challenges

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