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A case study for risk assessment in 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
Xylon Elect Co, Zagreb, Croatia.
2021 (English)In: Journal of systems architecture, ISSN 1383-7621, E-ISSN 1873-6165, Vol. 119, article id 102250Article in journal (Refereed) Published
Abstract [en]

Augmented Reality (AR) technologies are used as human-machine interface within various types of safety critical systems. Several studies have shown that AR improves human performance. However, the introduction of AR might introduce risks due to new types of dependability threats. In order to avoid unreasonable risk, it is required to detect new types of dependability threats (faults, errors, failures). In our previous work, we have designed extensions for the SafeConcert metamodel (a metamodel for modeling socio-technical systems) to capture AR-related dependability threats (focusing on faults and failures). Despite the availability of various modeling techniques, there has been no detailed investigation of providing an integrated framework for risk assessment in AR-equipped socio-technical systems. Hence, in this paper, we provide an integrated framework based on our previously proposed extensions. In addition, in cooperation with our industrial partners, active in the automotive domain, we design and execute a case study. We aim at verifying the modeling and analysis capabilities of our framework and finding out if the proposed extensions are helpful in capturing system risks caused by new AR-related dependability threats. Our conducted qualitative analysis is based on the Concerto-FLA analysis technique, which is included in the CHESS toolset and targets socio-technical systems.

Place, publisher, year, edition, pages
2021. Vol. 119, article id 102250
National Category
Computer Systems
Identifiers
URN: urn:nbn:se:mdh:diva-56204DOI: 10.1016/j.sysarc.2021.102250ISI: 000701678200005Scopus ID: 2-s2.0-85112660178OAI: oai:DiVA.org:mdh-56204DiVA, id: diva2:1603249
Available from: 2021-10-14 Created: 2021-10-14 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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