Representing Causal Structures in HAZOP Studies

Research output: Contribution to book/conference proceedings/anthology/reportConference contributionContributedpeer-review

Contributors

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

Original languageGerman
Title of host publication2021 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA )
PublisherWiley-IEEE Press
Pages1-4
Number of pages4
ISBN (print)978-1-7281-2990-7
Publication statusPublished - 10 Sept 2021
Peer-reviewedYes

Conference

Title2021 26th IEEE International Conference on Emerging Technologies and Factory Automation
Abbreviated titleETFA 2021
Conference number26
Duration7 - 10 September 2021
Website
Locationonline
CityVasteras
CountrySweden

External IDs

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

Keywords

Keywords

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