|
Estimated Degree of Risk Detection — When considering a system accident, life-cycle detection is important. The system is to be monitored to ensure that there are no situations or circumstances where initiators could occur to start the adverse accident process. Initiators are circumstances that trigger a latent condition(s) (hazard) within the system. They are decision errors, or other errors, made during system inception through the life cycle of the system. Latent hazards are, for example, code errors, specification errors and errors in calculations, errors in assumptions, failures, malfunctions and anomalies that adversely affect the system.
It is important to monitor the health of complex systems from a system safety view [Ref. 3]. In some cases, when these systems are automated, built-in testing (BIT) is designed into the system. Initial built-in testing (IBIT) may be designed to operate when an automated system is first powered up. Continuous background testing (CBIT) may be on during system operation. When the system is configured during shutdown, an additional BIT may operate to monitor and test the reconfiguration of the system for power shutdown. The automatic health monitoring of a complex system is needed when malfunction, failure and anomalies can present hazards. BIT capabilities drive alerts, warnings or cautions when the system is not functioning according to designed parameters. When BIT is not adequately designed, or should BIT fail when needed, accidents can happen.
For high-reliability physical hardware designs, such as building or bridge structures, ships or aircraft, visual inspection and non-destructive testing may be conducted to monitor and determine the health of such systems. However, there are instances when it is not totally possible to determine potential hazardous conditions. Depending on the material selection of metals, composites, chemicals or aggregates, it may not be apparent if there has been excessive wear, degradation or damage. Consequently, maintenance of hardware structures is a subject of continuous study in the fields of materials science, fracture mechanics, physical science, chemical, civil, nuclear, aerospace and mechanical engineering.
When thinking in terms of system safety, it is applicable to include the monitoring of deviations within a system and the fact that these deviations can be hazards. Trained collectors acquire data, and this data is plotted over time. Statistically, it is possible to identify deviations with trends in a complex system. Once the trends are identified, corrections could be made to offset the system imbalance before harm occurs. Not only are unsafe acts and unsafe conditions to be corrected, but so should any system deviation that could affect safety. By applying statistical control, it then becomes possible to decrease the risks associated with very complex system accidents.
During trade-off studies, it is important that the analyst addresses the concept of detection and, based upon the initial premise defined within particular options, judgment can be applied to estimating the degree of risk detection.
Estimated Degree of Knowledge Concerning Risk — Complex systems are usually variants of particular past designs, generally considered system evolution. Most major systems have evolved over time; for example, commercial aircraft, nuclear power, commercial tankers, oil platforms, automobiles and locomotives. In the application of system safety, there are instances where there is cutting-edge design or state-of-the-art design to evaluate, especially when research and development pushes the development of new designs, processes and products. In a sense, science is pushing the envelope in the evolutionary development of systems. When systems are at the cutting edge, the knowledge concerning risk can be very limited, and knowledge acquired may be based on experimentation, simulation and limited testing. There may be more unknowns than knowns. An estimate should be made of the degree of knowledge concerning risk.
Estimated Degree of Knowledge of Science to Mitigate Risks — The concepts discussed above also relate to the mitigation of risks. The design may be at the cutting edge; therefore, so may be the mitigations. If mitigations do not work when needed, system risks will not be eliminated or controlled. Experimentation, simulation and testing should be scrutinized and evaluated closely. Such efforts must be made as closely as possible to what is perceived as expected reality. Consequently, an analyst should estimate the degree of knowledge of science to mitigate system risks. This is an estimate of confidence of mitigation, given current knowledge.
Estimated Degree of Knowledge of Science Associated with the System — Specifically, the amount of scientific effort or work in order to successfully develop or modify the system is estimated. Assumptions can be made indicating that there may be appropriate knowledge about the system; however, additional scientific work is actually needed. New system development must be an iterative evolutionary process, and as knowledge is acquired, the scientific work needed will also change. At the inception of new systems, the analyst estimates or forecasts this iterative evolutionary process.
Estimated Degree of Knowledge of Loss History Associated with Risks — Since many complex systems are variants of particular past designs, it may be possible to equate past loss history in order to estimate future risks. Past knowledge of similar systems may help in the development of a like system. However, depending on the circumstances, past history may or may not reflect future reality. Slight changes, variances or deviations within similar systems may cause greater changes, variances and deviations within future reality. Bayesian analyses consider prior, current and estimated future random variable distributions in an attempt to forecast the future. Depending on the system under review, the analyst may be able to estimate the degree to which loss history can be used to identify, eliminate or control system risks.
« previous page | next page »
|
