Representing Causal Structures in HAZOP Studies

Publikation: Beitrag in Buch/Konferenzbericht/Sammelband/GutachtenBeitrag in KonferenzbandBeigetragenBegutachtung

Beitragende

Abstract

Hazard & Operability (HAZOP) studies are a common expert-driven brainstorming methodology to analyze the safety of systems. In this paper, we propose an approach to integrate the content of HAZOP studies of (apparatus and process) by extracting and disclosing the causal structures implied in the HAZOPs. Thus, a methodology for data compression and integration of several HAZOP studies is supposed, resulting in a comprehensible summary of the underlying causal relationships withing the current system set-up. The resulting diagrams constitute a summary of the essential HAZOP studies by disclosing and visualizing the internal causal structures and are hence designed to facilitate interpretations and deductions performed by human operators and support machine-readability. The application of the methodology is implemented in the import of HAZOP-tables to Resource Description Framework (RDF). Using this formalized structure, the export to their original format as table is supported as well, so that the transformation can be conducted without the loss of information in both directions.

Details

OriginalspracheDeutsch
Titel2021 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA )
Herausgeber (Verlag)Wiley-IEEE Press
Seiten1-4
Seitenumfang4
ISBN (Print)978-1-7281-2990-7
PublikationsstatusVeröffentlicht - 10 Sept. 2021
Peer-Review-StatusJa

Konferenz

Titel2021 26th IEEE International Conference on Emerging Technologies and Factory Automation
KurztitelETFA 2021
Veranstaltungsnummer26
Dauer7 - 10 September 2021
Webseite
Ortonline
StadtVasteras
LandSchweden

Externe IDs

Scopus 85122926409
ORCID /0000-0003-3954-7786/work/142243137
ORCID /0000-0001-5165-4459/work/142248225

Schlagworte

Schlagwörter

  • Conferences, Data visualization, Data compression, Resource description framework, Hazards, Manufacturing automation