Safety and Risk Management in Process Industries

A special issue of Safety (ISSN 2313-576X).

Deadline for manuscript submissions: 30 December 2024 | Viewed by 4659

Special Issue Editors


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Guest Editor
Hephaestus Laboratory, Department of Chemistry, Faculty of Science, Democritus University of Thrace, 65404 Kavala, Greece
Interests: occupational safety; chemical safety; fire safety; labor law; hazard assessment; solvents; chemical release; posted workers; undeclared work; diplomacy; international security; computational chemistry; terrorism; molecular simulation; molecular dynamics; molecular modeling; physical chemistry; monte simulation; computational science; hydrogen bonding; statistical mechanics; material modeling; theoretical chemistry; statistical thermodynamics
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Guest Editor
Systems Reliability and Industrial Safety Laboratory, Institute for Nuclear and Radiological Sciences, Energy, Technology and Safety, National Center for Scientific Research “DEMOKRITOS”, 15310 Athens, Greece
Interests: human reliability; quantitative risk assessment; hazard identification; risk management; accident analysis; process safety; oil and gas industry; offshore installations
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Safety and risk management within process industries are of paramount importance in terms of safeguarding human lives, preserving the environment, and protecting valuable assets, all the while ensuring the uninterrupted and efficient operation of these industries. This Special Issue endeavors to deepen our understanding of the myriad challenges and opportunities within the realm of process safety. It provides a platform for researchers, practitioners, and policymakers to share invaluable insights and groundbreaking innovations. Through the collaboration of multidisciplinary perspectives, we strive to advance the state of knowledge in this critical field, ultimately contributing to the secure, sustainable, and prosperous future of process industries.

This Special Issue titled “Safety and Risk Management in Process Industries” serves as a comprehensive platform for the exchange of knowledge, research findings, and innovative approaches related to safety and risk management in various process industries. Process industries encompass a wide range of sectors, including chemical, petrochemical, pharmaceutical, manufacturing, and energy production, where the handling of hazardous materials and complex operations presents inherent safety challenges.

This Special Issue warmly welcomes original research articles, reviews, case studies, and critical analyses that delve into and address the following issues:

  • Safety Culture and Human Factors: exploring the pivotal role of safety culture, human factors, and workforce engagement in elevating safety performance within process industries;
  • Hazard Identification and Risk Assessment: introducing novel methodologies and tools for the identification of hazards, performance of risk assessments, and strategic mitigation of risks, all of which are tailored to the unique contexts of process industry settings;
  • Process Safety Management: scrutinizing the effective implementation of process safety management systems, adherence to industry standards, and adoption of best practices aimed at accident and incident prevention;
  • Emergency Preparedness and Response: evaluating emergency planning, response strategies, and the utilization of incident investigation techniques that aim to minimize the impact of accidents when they inevitably occur.
  • Technological Advancements: putting a spotlight on cutting-edge technologies, such as artificial intelligence, the Internet of Things (IoT), and data analytics for real-time risk monitoring and dynamic risk management;
  • Environmental Impact and Sustainability: investigating the intersection of process safety with environmental sustainability, with a focus on emissions reduction and effective waste management;
  • Regulatory Compliance: analyzing the latest developments in regulatory frameworks and their implications for safety and risk management in the ever-evolving landscape of process industries.
  • Safety Education and Training: discussing innovative approaches to safety education, training programs, and the dissemination of knowledge and best practices among industry professionals.

Dr. Chalaris Michail
Dr. Myrto Konstantinidou
Guest Editors

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • process safety
  • risk management
  • safety culture
  • hazard identification
  • emergency preparedness
  • sustainability
  • regulatory compliance
  • safety education
  • human factors
  • process industries
  • incident investigation

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Published Papers (2 papers)

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Research

20 pages, 3520 KiB  
Article
A Model of Adaptive Error Management Practices Addressing the Higher-Order Factors of the Dirty Dozen Error Classification—Implications for Organizational Resilience in Sociotechnical Systems
by Nicki Marquardt, Ricarda Gades-Büttrich, Tammy Brandenberg and Verena Schürmann
Safety 2024, 10(3), 64; https://doi.org/10.3390/safety10030064 - 17 Jul 2024
Viewed by 1577
Abstract
Within the dynamic, complex, and often safety-critical operations of many process industries, the integration of technology and human elements has given rise to sociotechnical systems (STSs), where the interaction between people and technology plays a pivotal role. To thrive in this complex environment, [...] Read more.
Within the dynamic, complex, and often safety-critical operations of many process industries, the integration of technology and human elements has given rise to sociotechnical systems (STSs), where the interaction between people and technology plays a pivotal role. To thrive in this complex environment, organizations must adopt adaptive error management strategies and cultivate organizational resilience. This approach involves managing the unexpected and designing systems to embrace disorder by organizational learning from errors in STSs. The main objective of this article was to present empirical data of error-causing elements in STSs based on the Dirty Dozen concept, their underlying structure, and implications for error causation screening and adaptive error management systems. A sample of 544 workers employed in seven process industries, such as automotive, chemicals, defense, metal, and timber, participated in this study. The results revealed a three-factor model of human error causation in STSs. Based on these results, an adaptive error management system (AEMS), which includes evidence-based interventions to manage causes of human errors and mitigate their risky consequences, was presented. Finally, implications for organizational resilience and safety culture in STSs were discussed. Full article
(This article belongs to the Special Issue Safety and Risk Management in Process Industries)
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20 pages, 2367 KiB  
Article
The BowTie as a Digital Twin: How a BowTie Looks Different from a Data Perspective
by Paul Singh, Coen van Gulijk and Neil Sunderland
Safety 2024, 10(2), 34; https://doi.org/10.3390/safety10020034 - 31 Mar 2024
Viewed by 1814
Abstract
This work follows from a research project for safety management system re-engineering that turned a safety BowTie into a digital twin. A digital twin is a model embedded in software that mirrors a specific aspect of a real system; the aspect in this [...] Read more.
This work follows from a research project for safety management system re-engineering that turned a safety BowTie into a digital twin. A digital twin is a model embedded in software that mirrors a specific aspect of a real system; the aspect in this case is the risk space associated with a process. The well-known BowTie is the model that turns out to be singularly well suited as a digital twin from the risk perspective as it maps out the risk space together with real-life controls. However, for a BowTie to be a high-fidelity digital twin of a real system, the rules and processes for designing and operating a BowTie are changed. Full article
(This article belongs to the Special Issue Safety and Risk Management in Process Industries)
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