A Framework for Assessing Emerging Technology Risks in Industrial Asset

The management of risks in the context of Industry 4.0 is currently lacking accurate and efficient systematic approaches and tools, leading to a potential underestimation or unrealistic perception of risks in various domains where effective risk management is crucial. Traditional methods, while valuable, have limitations and may not adequately capture all the factors that influence system safety. To address the challenges posed by conventional industry issues, emerging risks, and the complexities of socio-technical systems, there is a need for comprehensive Asset Management and Decision Support approaches. These approaches should encompass both conventional and emerging risk safety management, providing innovative and efficient solutions to support practitioners in navigating these complex environments. Based on the rationale provided, this paper is dedicated to the identification and analysis of risk management components, particularly pertaining to emerging safety risks in the context of Industry 4.0. It also examines the challenges posed by extreme, rare, and disruptive events that have the potential to severely impact organizational performance. The research focuses on relatively new methods grounded in system theories, specifically the Functional Resonance Analysis Method (FRAM) and the System-Theoretic Accident Model and Processes (STAMP). These approaches are considered the most suitable for investigating and addressing the research objectives. To validate the efficiency and practicality of the adopted methods, further research initiatives will be focused on conducting case studies. These case studies will aim to gather more accurate data and insights related to the application of FRAM and STAMP in real-world scenarios.