Streamlining XR Technology Into Industrial Training and Maintenance Processes

Simões, Bruno; Creus, Carles; Carretero, María del Puy; Ochaíta, Álvaro Guinea

doi:10.1145/3424616.3424711

Cited by 7 publications

(4 citation statements)

References 35 publications

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“…These results are consistent with researchdesigned 2D-VR training environments (Smith et al, 2018;Madden et al, 2020) and interactive VR training environments, e.g., (Buttussi and Chittaro, 2017;Smith et al, 2018;Rupp et al, 2019). Additionally, this study found no significant difference between the two conditions regarding SSQ, consistent with previous research by Joshi et al (2021), but a difference between VR and monitor was found for SUS, as also reported by Simões et al (2020) and Othman et al (2022).…”

Section: Discussionsupporting

confidence: 92%

Behavior and self-efficacy modulate learning in virtual reality simulations for training: a structural equation modeling approach

Mousavi,

Powell,

Louwerse

et al. 2023

Front. Virtual Real.

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Introduction: There is a rising interest in using virtual reality (VR) applications in learning, yet different studies have reported different findings for their impact and effectiveness. The current paper addresses this heterogeneity in the results. Moreover, contrary to most studies, we use a VR application actually used in industry thereby addressing ecological validity of the findings.Methods and Results of Study1: In two studies, we explored the effects of an industrial VR safety training application on learning. In our first study, we examined both interactive VR and passive monitor viewing. Using univariate, comparative, and correlational analytical approaches, the study demonstrated a significant increase in self-efficacy and knowledge scores in interactive VR but showed no significant differences when compared to passive monitor viewing. Unlike passive monitor viewing, however, the VR condition showed a positive relation between learning gains and self-efficacy.Methods and Results of Study2: In our subsequent study, a Structural Equation Model (SEM) demonstrated that self-efficacy and users’ simulation performance predicted the learning gains in VR. We furthermore found that the VR hardware experience indirectly predicted learning gains through self-efficacy and user simulation performance factors.Conclusion/Discussion of both studies: Conclusively, the findings of these studies suggest the central role of self-efficacy to explain learning gains generalizes from academic VR tasks to those in use in industry training. In addition, these results point to VR behavioral markers that are indicative of learning.

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Section: Discussionsupporting

confidence: 92%

Behavior and self-efficacy modulate learning in virtual reality simulations for training: a structural equation modeling approach

Mousavi,

Powell,

Louwerse

et al. 2023

Front. Virtual Real.

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“…In particular, dedicated approaches propose a methodical approach for implementing an XR solution based on the identified deployment purpose for these steps. These can range from generic approaches deploying information systems for business transformation [92], approaches describing the required activities and the ecosystem for deploying XR technologies [93], to approaches describing the technological process of developing and configuring XR solutions from the initial requirements over the proof-ofconcept to the value-adding XR solution [94]. In the larger context of the state of research, the presented paper takes a supporting role in the initiation phase of a deployment with the above-mentioned methodologies.…”

Section: The Role Of the Taxonomy In The Execution Of An Xr Solutionmentioning

confidence: 99%

XR Technology Deployment in Value Creation

Krodel¹,

Schott²,

Ovtcharova

2023

Applied Sciences

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With increasing computing power and data transmission performance of information technologies, the application scenarios for Extended Reality (XR) technologies in industries are growing. Despite the ongoing scientific investigation of industrial XR applications for over 25 years, these technologies are still considered emerging. Within this paper, we present an industry- and business-process agnostic approach for classifying the deployment purposes of XR technologies in value creation. We identified two major research streams regarding the role of XR technologies in value creation: (1) the research initiatives focusing on business-process-specific use case analysis and (2) industry-oriented research reviews. This results in limited identification of suitable application scenarios for new use cases and restricted transferability of the existing use case to future deployments. First, we provide a qualitative analysis of the current research streams. Then, in the second step, by abstracting the XR technology from the existing business processes and the industry-specific context, the generic purposes for XR technologies in value creation are identified and defined. The summary of these deployment purposes results in a taxonomy that enables the identification and transfer of potential use cases of XR technologies in value creation.

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“…The CAD models are also exported to external files. Figure 12 shows the interface that is devised for the toolkit that was introduced in [19,20] to enable the virtual prototype. The interface is built with Qt™ library and it comprises several panels: (i) the 3D visualization panel, which allows for the visualization of the pump geometry (gears, ports, and chambers) and the animation showing the rotation of the pump through a pumping cycle, (ii) a hierarchy panel that shows the hierarchy tree of the geometric model and allows the user to select and highlight geometric entities, (iii) a settings panel in which the user inputs the fluid properties, operating conditions, and initial pressure conditions that are necessary to perform the fast pre-CFD simulation (see Figure 2), (iv) a simulated data panel that displays the results from the fast simulation model, and (v) a measured data panel that displays the results of the variables that are imported to the virtual prototype tool, whether measured in the test bench or simulated by the CFD software.…”

Section: Software Toolmentioning

confidence: 99%

A Virtual Prototype for Fast Design and Visualization of Gerotor Pumps

et al. 2021

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In the context of generation of lubrication flows, gear pumps are widely used, with gerotor-type pumps being specially popular, given their low cost, high compactness, and reliability. The design process of gerotor pumps requires the simulation of the fluid dynamics phenomena that characterize the fluid displacement by the pump. Designers and researchers mainly rely on these methods: (i) computational fluid dynamics (CFD) and (ii) lumped parameter models. CFD methods are accurate in predicting the behavior of the pump, at the expense of large computing resources and time. On the other hand, Lumped Parameter models are fast and they do not require CFD software, at the expense of diminished accuracy. Usually, Lumped Parameter fluid simulation is mounted on specialized black-box visual programming platforms. The resulting pressures and flow rates are then fed to the design software. In response to the current status, this manuscript reports a virtual prototype to be used in the context of a Digital Twin tool. Our approach: (1) integrates pump design, fast approximate simulation, and result visualization processes, (2) does not require an external numerical solver platforms for the approximate model, (3) allows for the fast simulation of gerotor performance using sensor data to feed the simulation model, and (4) compares simulated data vs. imported gerotor operational data. Our results show good agreement between our prediction and CFD-based simulations of the actual pump. Future work is required in predicting rotor micro-movements and cavitation effects, as well as further integration of the physical pump with the software tool.

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Streamlining XR Technology Into Industrial Training and Maintenance Processes

Cited by 7 publications

References 35 publications

Behavior and self-efficacy modulate learning in virtual reality simulations for training: a structural equation modeling approach

Behavior and self-efficacy modulate learning in virtual reality simulations for training: a structural equation modeling approach

XR Technology Deployment in Value Creation

A Virtual Prototype for Fast Design and Visualization of Gerotor Pumps

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