Mohammad Bakhshandeh , Jayantha P. Liyanage , Bjarne Andre Asheim , Lu Li
{"title":"Process deviations, early sensemaking, and enabling operators: Thinking beyond the traditional alarm-based practice to enhance industrial resilience","authors":"Mohammad Bakhshandeh , Jayantha P. Liyanage , Bjarne Andre Asheim , Lu Li","doi":"10.1016/j.jsasus.2024.09.002","DOIUrl":null,"url":null,"abstract":"<div><div>In the dynamic landscape of modern industrial systems, there is an emerging important need for new thinking and practice to facilitate risk-informed decision-making, especially in high-risk industrial sectors. Such novel solutions should enable operators to proactively counteract and prevent unwanted events and incidents. Efforts to harness and convert relevant data to meaningful information with unique meanings, in fact represents new opportunities to create relevant knowledge of the actual context. This research examines this through early sensemaking of process deviations, facilitating a seamless integration of information towards context-sensitive decision-making processes. Two industrial approaches are discussed: a conventional alarm-based practice, as well as an enhanced approach. The research underscores the application of such techniques through two industrial cases, aiming at fostering enhanced resilience, reliability, and safety within high-risk industrial settings.</div></div>","PeriodicalId":100831,"journal":{"name":"Journal of Safety and Sustainability","volume":"1 3","pages":"Pages 161-172"},"PeriodicalIF":0.0000,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Safety and Sustainability","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2949926724000301","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In the dynamic landscape of modern industrial systems, there is an emerging important need for new thinking and practice to facilitate risk-informed decision-making, especially in high-risk industrial sectors. Such novel solutions should enable operators to proactively counteract and prevent unwanted events and incidents. Efforts to harness and convert relevant data to meaningful information with unique meanings, in fact represents new opportunities to create relevant knowledge of the actual context. This research examines this through early sensemaking of process deviations, facilitating a seamless integration of information towards context-sensitive decision-making processes. Two industrial approaches are discussed: a conventional alarm-based practice, as well as an enhanced approach. The research underscores the application of such techniques through two industrial cases, aiming at fostering enhanced resilience, reliability, and safety within high-risk industrial settings.