Uncertainty modeling in risk assessment of digitalized process systems

Risk assessment is inevitable in different industrial and social systems, which potential risks have to be continuously monitored and controlled to improve system safety and resilience performance. Risk analysis yields invaluable data and a detailed understanding of the systems to support decision-making. However, risk analysis deals with inherent uncertainties that mainly arise from system complexity, parameters randomness, the applied risk model and techniques’ assumptions and incapability, the unpredictability of human behavior, and insufficient data. The digitalized process systems are monitored and maintained with better efficiency and control among all existing process safety domains. Thus, it causes overconfidence in instrumentation and data utilization, affecting process safety adversely. The present chapter provides a big picture to characterize and treat uncertainty in digitalized process systems. The chapter starts with an introduction highlighting the necessity of uncertainty modeling in the risk assessment of digitalized process systems. Then, it continues with the definition of uncertainty, how to model and treat uncertainty with a primary focus in digitalized process systems. Finally, the current challenges and future directions are discussed.