A mixed reality for virtual assembly

Zaldivar-Colado, Ulises; Garbaya, Samir; Tamayo-Serrano, Paul; Zaldivar-Colado, Xiomara; Blazevic, Pierre

doi:10.1109/roman.2017.8172385

Cited by 12 publications

(5 citation statements)

References 19 publications

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“…Conversely, Aschenbrenner et al [13] found using tablet-based AR applications to repair a switch cabinet did not improve results in terms of time taken or cognitive effort involved. The work of Zaldívar-Colado et al supports this [7], as they too found Mixed Reality may have a detrimental effect on assembly performance.…”

Section: Introductionmentioning

confidence: 85%

“…Consumer environment 508 unique records were identified from the search criteria: title or abstract contains ("Augmented Reality" OR "Mixed Reality") AND ("Maintenance" OR "Repair") published since 2013. Once records which were irrelevant, or presented no usable data on user performance were filtered out, 6 remained [6,7,[15][16][17][18]. All 6 presented data on the time to complete the specified operation for both an AR instruction and paper instruction.…”

Section: Effect Size Meta-analysismentioning

confidence: 99%

“…Prominent figures in AR research, such as Funk, Erkoyuncu and Sanna have all presented studies claiming the benefits of AR guided assembly including faster task completion and fewer errors [4][5][6]. On the other hand, research such as that carried out by Zaldívar-Colado et al suggests Augmented or Mixed Reality can, in fact, slow down assembly [7], suggesting that AR is not unanimously beneficial to the assembly process. Instead, performance depends very much on the particular design aspects of an AR system.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Augmented Instructions: Analysis of Performance and Efficiency of Assembly Tasks

Smith

Semple

Evans

et al. 2020

Lecture Notes in Computer Science

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Augmented Reality (AR) technology makes it possible to present information in the user's line of sight, right at the point of use. This brings the capability to visualise complex information for industrial maintenance applications in an effective manner, which typically rely on paper instructions and tacit knowledge developed over time. Existing research in AR instruction manuals has already shown its potential to reduce the time taken to complete assembly tasks, as well as improving accuracy [1][2][3]. In this study, the outcomes of several aspects of AR instructions are explored and their effects on the chosen Key Performance Indicators (KPIs) of task completion time, error rate, cognitive effort and usability are assessed. A standardised AR assembly task is also described for performance comparison, and a novel AR experimental tool is presented, which takes advantage of the flexibility of internet connected peripherals, to explore various different aspects of AR app design to isolate their effects. Results of the experiments are given here, providing insight into the most effective way of delivering information and promoting interaction between user and computer, in terms of user performance and acceptance.

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Section: Introductionmentioning

confidence: 85%

Section: Effect Size Meta-analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Augmented Instructions: Analysis of Performance and Efficiency of Assembly Tasks

Smith

Semple

Evans

et al. 2020

Lecture Notes in Computer Science

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“…One of the earliest machinery maintenance and repair (laser-printer) mixed reality (MR) applications was developed by Steve Feiner’s team at Columbia University in 1993 [ 414 ]. Mixed reality (MR) has also been used to develop an application for improving performance in the execution of assembly tasks [ 415 ]. Applications of AR/MR for employee training and work on production lines [ 416 ], quality monitoring and inspection, maintenance, assembly, and safety have been reported [ 417 , 418 ].…”

Section: Key Building Blocks Technology Enablers and Innovation Accel...mentioning

confidence: 99%

A Primer on the Factories of the Future

Anumbe

Saidy

Harik

2022

Sensors

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In a dynamic and rapidly changing world, customers’ often conflicting demands have continued to evolve, outstripping the ability of the traditional factory to address modern-day production challenges. To fix these challenges, several manufacturing paradigms have been proposed. Some of these have monikers such as the smart factory, intelligent factory, digital factory, and cloud-based factory. Due to a lack of consensus on general nomenclature, the term Factory of the Future (or Future Factory) has been used in this paper as a collective euphemism for these paradigms. The Factory of the Future constitutes a creative convergence of multiple technologies, techniques, and capabilities that represent a significant change in current production capabilities, models, and practices. Using the semi-narrative research methodology in concert with the snowballing approach, the authors reviewed the open literature to understand the organizing principles behind the most common smart manufacturing paradigms with a view to developing a creative reference that articulates their shared characteristics and features under a collective lingua franca, viz., Factory of the Future. Serving as a review article and a reference monograph, the paper details the meanings, characteristics, technological framework, and applications of the modern factory and its various connotations. Amongst other objectives, it characterizes the next-generation factory and provides an overview of reference architectures/models that guide their structured development and deployment. Three advanced communication technologies capable of advancing the goals of the Factory of the Future and rapidly scaling advancements in the field are discussed. It was established that next-generation factories would be data rich environments. The realization of their ultimate value would depend on the ability of stakeholders to develop the appropriate infrastructure to extract, store, and process data to support decision making and process optimization.

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“…AR technologies see more widespread use in supporting users on visualization of information in both 2D and 3D. Some applications are also not restricted to standalone AR implementations such as a virtual assembly tasks by Zaldívar-Colado et al [14] which used AR in conjunction with virtual reality (mixed reality).…”

Section: Introductionmentioning

confidence: 99%

A Review on Augmented Reality Tracking Methods for Maintenance of Robots

et al. 2020

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Augmented reality (AR) in maintenance is a broad subject with many nuances when it comes to their implementation. The applications of these systems range from maintenance of large-scale assets such as buildings to smaller scale assets such as robots. Applications of AR in maintenance typically serves as a visual guide to assist users in diagnosis or steps needed to be performed for maintenance. In this paper, the tracking methods utilized in AR-based maintenance for robots are qualitatively evaluated. The reviewed works in this paper are between the years of 2015 to 2020 to ensure that the AR tracking methods are relatively state of the art. It is found that applications of AR-based maintenance for robots are uncommon in the scope defined in this research especially in the industrial environment as most reviewed works are conducted in a laboratory setting. In addition to that, it is found that marker-based tracking methods are commonly utilized in these applications.

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A mixed reality for virtual assembly

Cited by 12 publications

References 19 publications

Augmented Instructions: Analysis of Performance and Efficiency of Assembly Tasks

Augmented Instructions: Analysis of Performance and Efficiency of Assembly Tasks

A Primer on the Factories of the Future

A Review on Augmented Reality Tracking Methods for Maintenance of Robots

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