Abstract
AbstractAccurate systematic approaches and tools for managing risks in the context of industry 4.0 and its corollary industry 5.0 are lacking or less efficient, propagating unrealistic awareness of risk in various domains where risk management is needed. Traditional methods have their own limits and might not identify all aspects that influence system safety. When conventional industry challenges are combined with emerging risks along with new systemic and organizational risks as well as cognitive and motivational biases in human logic, there arises the necessity of building thorough Asset Management (AM) and Decision Support approaches. This should account both for conventional and emerging risk safety management. Therefore, innovative, and efficient approaches that can investigate issues from a broad systemic perspective to support AM practitioners to deal with those threats associated with the complexity of socio-technical systems are of interest. On these grounds, this paper focuses on identifying and analysing components of risk management approaches especially for new emerging safety risks within industry 4.0, as well as the rising of extreme, rare, and disruptive events that might generate fatal disturbance of the performance of organizations. We have opted for the relatively new methods that have been developed based on system theories, viz. The Functional Resonance Analysis Method (FRAM), the System-Theoretic Accident Model and Processes (STAMP) and the global risk-informed decision-making approach (RIDM) in AM as the best suited approach for this research. Further research would validate their efficiency and practicality. Therefore, future research initiatives will be devoted to conduct case-studies in order to obtain more accurate data.KeywordsAsset management strategyEnterprise Risk Management (ERM)Emerging risksExtreme-rare-and-disruptive-eventsResilienceIndustry 4.0/5.0Risk-Informed Decision-Making Approach (RIDM)Functional Resonance Analysis Method (FRAM)System-Theoretic Accident Model and Processes (STAMP)
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