A Training Simulation System for Substation Equipments Maintenance

Chang, Zhengwei; Fang, Yu; Zhang, Yun

doi:10.1109/mvhi.2010.31

Cited by 18 publications

(7 citation statements)

References 2 publications

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“…Buriol, Rozendo, de Geus, Scheer, and Felsky (2009) described a VR application for live line maintenance of power distribution networks. Chang, Fang, Zhang, and Hu (2010) presented a training simulation system for substation equipment maintenance.…”

Section: Introductionmentioning

confidence: 99%

Evaluating virtual reality and augmented reality training for industrial maintenance and assembly tasks

Gavish

Gutiérrez

Webel

et al. 2013

Interactive Learning Environments

526

240

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The current study evaluated the use of virtual reality (VR) and augmented reality (AR) platforms, developed within the scope of the SKILLS Integrated Project, for industrial maintenance and assembly (IMA) tasks training. VR and AR systems are now widely regarded as promising training platforms for complex and highly demanding IMA tasks. However, there is a need to empirically evaluate their efficiency and effectiveness compared to traditional training methods. Forty expert technicians were randomly assigned to four training groups in an electronic actuator assembly task: VR (training with the VR platform twice), Control-VR (watching a filmed demonstration twice), AR (training with the AR platform once), and Control-AR (training with the real actuator and the aid of a filmed demonstration once). A post-training test evaluated performance in the real task. Results demonstrate that, in general, the VR and AR training groups required longer training time compared to the Control-VR and Control-AR groups, respectively. There were fewer unsolved errors in the AR group compared to the Control-AR group, and no significant differences in final performance between the VR and Control-VR groups, probably due to a ceiling effect created by the use of two training trials in the selected task for participants who were expert technicians. The results suggest that use of the AR platform for training IMA tasks should be encouraged and use of the VR platform for that purpose should be further evaluated

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Section: Introductionmentioning

confidence: 99%

Evaluating virtual reality and augmented reality training for industrial maintenance and assembly tasks

Gavish

Gutiérrez

Webel

et al. 2013

Interactive Learning Environments

526

240

View full text Add to dashboard Cite

show abstract

“…There are many examples of systems that explore the above characteristics in the literature [Bingda et al 2000;Chang et al 2010;Buriol et al 2011;Rosendo et al 2011]. However, the most interesting is that the complexity or the increased cognitive overload generated by VR is almost often seen as something that has allegedly good effects on the learning experience.…”

Section: Related Workmentioning

confidence: 99%

Interacting with danger in an immersive environment

Jorge

Sarmiento

Maciel

et al. 2013

Proceedings of the 19th ACM Symposium on Virtual Reality Software and Technology

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Figure 1: Snapshots of the administrative scenario of the AES-risk simulator. Images (a) and (b) show two views of the courtyard, while images (c) and (d) show the offices and the kitchen. Red arrows on the floor indicate a path that should be followed by users. On image (c), an office chair (highlighted in red) was selected by the user because it is in the middle of a corridor. The user understood that the chair represents a risky situation. AbstractAny human-computer interface imposes a certain level of cognitive load to the user task. Analogously, the task itself also imposes different levels of cognitive load. It is common sense in 3D user interfaces research that a higher number of degrees of freedom increases the interface cognitive load. If the cognitive load is significant, it might compromise the user performance and undermine the evaluation of user skills in a virtual environment. In this paper, we propose an assessment of two immersive VR interfaces with varying degrees of freedom in two VR tasks: risk perception and basic object selection. We examine the effectiveness of both interfaces in these two different tasks. Results show that the number of degrees of freedom does not significantly affect a basic selection task, but it affects risk perception task in an unexpected way.

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“…Offspring are then created by applying conventional crossover and mutation operators selecting parents from different sub-populations. Other relevant non-Pareto approaches are summarized in [2].…”

Section: B Multi Objective Evolutionary Algorithmsmentioning

confidence: 99%

An ontological multi-criteria optimization system for Workforce Management

Cimitile

Gaeta

Loia

2012

2012 IEEE Congress on Evolutionary Computation

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Workforce Management (WFM) is becoming a core decisional approach for optimizing different enterprise processes such as operational activities needed to maintain a high production rate. However, in order to solve complex optimization problems it is necessary to analyze and deal with a plethora of distributed and semantically different information defining the collection of criteria from which enterprise activities depend. For this reason, this paper introduces a novel WFM system that, by using an ontological representation of knowledge related to the different aspects of an enterprise activity, exploits a multicriteria decision making approach for selecting the most suitable strategies to face WFM issues.U.S. Government work not protected by U.S. copyright WCCI 2012 IEEE World Congress on Computational Intelligence June, 10-15, 2012 -Brisbane, Australia FUZZ IEEE

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A Training Simulation System for Substation Equipments Maintenance

Cited by 18 publications

References 2 publications

Evaluating virtual reality and augmented reality training for industrial maintenance and assembly tasks

Evaluating virtual reality and augmented reality training for industrial maintenance and assembly tasks

Interacting with danger in an immersive environment

An ontological multi-criteria optimization system for Workforce Management

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