What is it about?
Contrary to the common wisdom, risks don’t depend on hypothetical external events, only on the system itself. Event guessing is abusively called analysis but useless to help design physical systems or launch organizational moves. Events provide inputs to which systems respond according to their structure. A risk-informed dynamic model for a system’s structure capably responds to arbitrary inputs. All inputs carry energy. A new method for risk analysis uses energy attributes of dynamic models. Physical or policy systems trade energy with the surroundings through expected transactions and unexpected disturbances. The method measures risk as a function of the energy traded when moving a system from an acceptable to a faulty state. Robust systems dissipate excess energy, whereas vulnerable systems lose functionality. Instead of guessing countless hypothetical events, the method systematically and comprehensively analyzes weaknesses in the system model. Fuses and cushions are generic classes of risk protection. Placing them into system models at identified weak points helps improve design. An extension to the method includes definitions of measures for consequence and uncertainty as functions of acceptable and faulty states.
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Why is it important?
The dominant risk analysis method relies on guessing events. External events are the usual culprit of design or decision errors. Engineers don’t guess events; they create them to test their systems. In turn, managers decide policies irrespective of guessed events. Hence, guessing events is useless. In contrast, a formal risk method shows how system models may exhibit the intended functionality when responding to arbitrary events.
Perspectives
I believe that attempting to guess the probability of one among possibly countless events is the modern equivalent to tossing chicken bones or reading tea leaves. When properly worded, reading works. Although thrilled to have nailed down a formal risk theory, I understand it will take a long time before it is widely accepted.
Dr. Pedro Mendes
Read the Original
This page is a summary of: Model‐based risk analysis for system design, Systems Engineering, June 2023, Wiley,
DOI: 10.1002/sys.21704.
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