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Towards Qualitative and Quantitative Dependability Analyses for AR-Equipped Socio-Technical Systems
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0002-6952-1053
2021 (English)In: 2021 5th International Conference on System Reliability and Safety, ICSRS 2021, Institute of Electrical and Electronics Engineers Inc. , 2021, p. 161-170Conference paper, Published paper (Refereed)
Abstract [en]

Augmented Reality technologies are becoming essential components in various socio-technical systems. New kinds of risks, however, may emerge if the concertation between AR, other technical components and socio-components is not properly designed. To do that, it is necessary to extend techniques for risk assessment to capture such new risks. This may require the extension of modelling languages and analysis techniques. In the literature, modeling languages have been already extended by including specific language constructs for socio aspects in relation to the AR-impact. No satisfying contribution is available regarding analysis techniques. Hence, to contribute to filling the gap, in this paper, we propose an extension of previously existing analysis techniques. Specifically, we build on top of the synergy of qualitative and quantitative dependability analysis techniques and we extend it with the capability of benefiting from AR-related modelled aspects. In addition, we apply our proposed extension to an illustrative example. Finally, we provide discussion and sketch future work. 

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers Inc. , 2021. p. 161-170
Keywords [en]
AR-equipped Systems, Augmented Reality, Risk Analysis, Socio-technical Systems
National Category
Human Computer Interaction
Identifiers
URN: urn:nbn:se:mdh:diva-57539DOI: 10.1109/ICSRS53853.2021.9660642ISI: 000850133700026Scopus ID: 2-s2.0-85124987130ISBN: 9781665400497 (print)OAI: oai:DiVA.org:mdh-57539DiVA, id: diva2:1641604
Conference
International Conference on System Reliability and Safety, ICSRS 2021, Palermo, Italy, 24-26 November, 2021
Available from: 2022-03-02 Created: 2022-03-02 Last updated: 2023-03-10Bibliographically approved
In thesis
1. Organizational Changes-aware Safety-centered Risk Assessment in Augmented Reality-equipped Socio-technical Systems
Open this publication in new window or tab >>Organizational Changes-aware Safety-centered Risk Assessment in Augmented Reality-equipped Socio-technical Systems
2023 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

In the last two to three decades, organizations have extremely changed. Post normal accident theory argues about implication of new organizational changes such as digitalization which may lead to new kinds of accidents called post normal accidents. In addition, there are technological changes such as usage of augmented reality (AR) as human-machine interface within various types of safety-critical systems. The organizational changes in addition to technological changes and their effects on human may introduce new system risks and should be considered in the risk assessment activities in compliance with related safety standards. Systems including technical entities and socio entities (i.e. humans and organizations) are called socio-technical systems. We consider socio-technical systems containing augmented reality which we call AR-equipped socio-technical systems. In order to adequately assess risk in such systems, it is essential to consider new dependability threats caused by augmented reality and new organizational changes. In the literature, various modeling and analysis techniques exist which are beneficial to be used for risk assessment. Furthermore, in the context of safety-critical systems, it is crucial to consider safety standards and assess the risk in compliance with the related safety standards. 

This thesis aims at strengthening risk assessment in AR-equipped socio-technical systems in compliance with safety standards considering post normal accidents by providing a safety-centered risk assessment framework (we call it safety-centered due to the support it provides for safety standards). Our work provides modeling capabilities for modeling dependability threats caused by organizational changes leading to post normal accidents in AR-equipped socio-technical systems. The capabilities are provided through metamodel extensions. The extensions are used for extending analysis techniques to address the requirements of AR-equipped socio-technical systems analysis considering safety standard and post normal accidents. To achieve this, we capture dependability threats leading to post normal accidents via new modeling elements, which we add to SafeConcert, a conceptual metamodel for modeling socio-technical systems, and its AR-related extensions. The extended metamodel is then used to strengthen a risk analysis technique used for socio-technical systems analysis. We propose a dependability analysis process in order to analyze the behavior of AR-equipped socio-technical systems. Based on the modeling and analysis extensions, we propose a safety-centered framework for risk assessment of AR-equipped socio-technical systems and we apply it in two different domains. First, we conduct a case study in the automotive domain in cooperation with our industrial partner and we show how the required activities in the related safety standards are supported by different steps of our framework. Then, we use a digitalized socio-technical factory system in robotic domain containing both organizational and technological changes as a case in a new domain in order to evaluate applicability and effectiveness of our framework for capturing new kinds of accidents due to dependability threats caused by organizational changes and AR. Furthermore, we conduct a systematic literature review to position our contributions and to compare our work with other related works (we had preliminary literature reviews in the initial steps, nevertheless in this step we conduct a systematic literature review for positioning and comparing our work).

Place, publisher, year, edition, pages
Västerås: Mälardalens universitet, 2023
Series
Mälardalen University Press Dissertations, ISSN 1651-4238 ; 371
National Category
Engineering and Technology Other Engineering and Technologies
Research subject
Computer Science
Identifiers
urn:nbn:se:mdh:diva-61172 (URN)978-91-7485-577-7 (ISBN)
Public defence
2023-03-15, Delta och online via Zoom/Teams, Mälardalens högskola, Västerås, 13:30 (English)
Opponent
Supervisors
Available from: 2022-12-09 Created: 2022-12-08 Last updated: 2023-03-10Bibliographically approved

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Sheikh Bahaei, SoheilaGallina, Barbara

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