The importance of information and communication design for manual skills instruction with augmented reality

Fox, Stephen

doi:10.1108/17410381011014369

Cited by 22 publications

(16 citation statements)

References 63 publications

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“…Other position papers provided guidelines for AR implementation, either in general terms (Chimienti et al, 2010) or for the deployment of AR in the specific areas, e.g., assembly and remote maintenance (Haist, 2008). Fox (2010), instead, described the requirements to properly design ICT tools for the implementation of AR.…”

Section: Conceptual Papersmentioning

confidence: 99%

Augmented reality technology in the manufacturing industry: A review of the last decade

2019

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The aim of this article is to analyze and review the scientific literature relating to the application of Augmented Reality (AR) technology in industry. AR technology is becoming increasingly diffuse, due to the ease of application development and the widespread use of hardware devices (mainly smartphones and tablets) able to support its adoption. Today, a growing number of applications based on AR solutions are being developed for industrial purposes. Although these applications are often little more than experimental prototypes, AR technology is proving highly flexible and is showing great potential in numerous areas (e.g., maintenance, training/learning, assembly or product design) and in industrial sectors (e.g., the automotive, aircraft or manufacturing industries). It is expected that AR systems will become even more widespread in the near future.The purpose of this review is to classify the literature on AR published from 2006 to early 2017, to identify the main areas and sectors where AR is currently deployed, describe the technological solutions adopted, as well as the main benefits achievable with this kind of technology.ARTICLE HISTORY

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Section: Conceptual Papersmentioning

confidence: 99%

Augmented reality technology in the manufacturing industry: A review of the last decade

2019

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“…If there are five ways to carry out a work process but one of those ways is followed four times in five, then the entropy is 1.12. Thus, entropy and Information Gain can provide a practical bridge between practitioner expertise and computer-aided analyses of the fit of autonomous production systems to work with challenging characteristics [59][60][61].…”

Section: Implications For Practicementioning

confidence: 99%

Reliable Autonomous Production Systems: Combining Industrial Engineering Methods and Situation Awareness Modelling in Critical Realist Design of Autonomous Production Systems

Fox

2018

Systems

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Autonomous production needs to be reliable. Outputs from reliable production systems consistently conform to performance requirements. By contrast, outputs from unreliable production systems often do not conform to performance requirements. Unreliable production can lead to accidents, rework, scrap, loss of good will, etc. In this communication paper, comparative analyses are provided of work characteristics in the manufacturing and construction industries, which affect opportunities for reliable high-level autonomous production systems. Analyses indicate that there are strong opportunities and weak opportunities for reliable high-level autonomous production systems in these industries. In the strongest opportunities, there is repeated work certainty; the composition of work involves few materials/parts that have little variation; and work is carried out in settings that require no additional engineering to facilitate reliable autonomous production. In the weakest opportunities, work settings require extensive additional engineering; the composition of work involves many materials/parts that have lots of variation; the work to be done is not certain until completion and then it is never repeated. It is explained that when seeking to improve weak opportunities for reliable high-level autonomous production systems, industrial engineering methods and situation awareness modelling can be combined within a critical realist framework in order to address challenges in work setting, composition and uncertainty.

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“…Moreover, if a component is redesigned so that it can be fitted in only one way (i.e., entropy 0.00), there is an Information Gain of 2.58. Similarly, uncertainty arising from manufacturing instructions can be reduced through information and communication design that reduces sources of ambiguity [ 15 ].…”

Section: Introductionmentioning

confidence: 99%

Cognitive Factories: Modeling Situated Entropy in Physical Work Carried Out by Humans and Robots

Fox

Kotelba

Niskanen

2018

Entropy

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Entropy in factories is situated. For example, there can be numerous different ways of picking, orientating, and placing physical components during assembly work. Physical components can be redesigned to increase the Information Gain they provide and so reduce situated entropy in assembly work. Also, situated entropy is affected by the extent of knowledge of those doing the work. For example, work can be done by knowledgeable experts or by beginners who lack knowledge about physical components, etc. The number of different ways that work can be done and the knowledge of the worker combine to affect cognitive load. Thus, situated entropy in factories relates to situated cognition within which knowledge is bound to physical contexts and knowing is inseparable from doing. In this paper, six contributions are provided for modelling situated entropy in factories. First, theoretical frameworks are brought together to provide a conceptual framework for modelling. Second, the conceptual framework is related to physical production using practical examples. Third, Information Theory mathematics is applied to the examples and a preliminary methodology in presented for modelling in practice. Fourth, physical artefacts in factory production are reframed as carriers of Information Gain and situated entropy, which may or may not combine as Net Information Gain. Fifth, situated entropy is related to different types of cognitive factories that involve different levels of uncertainty in production operations. Sixth, the need to measure Net Information Gain in the introduction of new technologies for embodied and extended cognition is discussed in relation to a taxonomy for distributed cognition situated in factory production. Overall, modelling of situated entropy is introduced as an opportunity for improving the planning and control of factories that deploy human cognition and cognitive technologies including assembly robotics.

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The importance of information and communication design for manual skills instruction with augmented reality

Cited by 22 publications

References 63 publications

Augmented reality technology in the manufacturing industry: A review of the last decade

Augmented reality technology in the manufacturing industry: A review of the last decade

Reliable Autonomous Production Systems: Combining Industrial Engineering Methods and Situation Awareness Modelling in Critical Realist Design of Autonomous Production Systems

Cognitive Factories: Modeling Situated Entropy in Physical Work Carried Out by Humans and Robots

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