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Automation for HAZOP study: A state-of-the-art review and future research directions

Author(s):

Medium: journal article
Language(s): English
Published in: Journal of Information Technology in Construction, , v. 29
Page(s): 750-777
DOI: 10.36680/j.itcon.2024.033
Abstract:

Hazard and Operability Study is a structured and systematic metodology to identify and mitigate potential hazards and operational issues associated with a system, process, or facility. This methodology—dubbed as HAZOP—has been initially applied in the chemical industry and subsequently extended to other process industries. Despite its effectiveness, conventional HAZOP study is time consuming, labor-intensive, expensive,and heavily reliant on human judgement. To address these challenges, intelligent systems and different levels of automation have been developed, including knowledge-based approaches that use domain-specific rules, and expertise and data-driven models that identify potential hazards from historical data patterns. The existing AI HAZOP tools lack both full automation for generating HAZOP reports and a comprehensive knowledge base for detecting hazards and operational malfunctions. This paper provides a detailed literature review on the application of automated HAZOP methodologies across different industries. It summarizes the advancements and contributions made over the past decade, highlighting sophisticated technologies such as powerful knowledge representation formalisms and reasoning techniques. The benefits and shortcomings of existing technologies are discussed and future work directions are proposed.

Structurae cannot make the full text of this publication available at this time. The full text can be accessed through the publisher via the DOI: 10.36680/j.itcon.2024.033.
  • About this
    data sheet
  • Reference-ID
    10806377
  • Published on:
    10/11/2024
  • Last updated on:
    10/11/2024
 
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