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Tutorial on Architecting Resilient Systems: Accident
Avoidance and Survival and Recovery from Disruptions
Monday, June 16, 2008 from 0800 to 1700 Utrecht, the Netherlands Scott Jackson, University of Southern California This tutorial is part of the International Council on Systems Engineering (INCOSE) International Symposium in Utrecht. Registration for the symposium can be found on http://www.incose.org/symp2008/. Persons wishing to attend the tutorial but not the entire symposium may use the one-day registration option. Abstract of the tutorial: This tutorial provides a framework for the architecting of systems, both human and product systems, that avoid major accidents and survive and recover from disruptions. This tutorial will explain the process for architecting a system that will avoid accidents and will be most likely to survive and recover from a disruption. In resilience the emphasis is on anticipation of the accident and taking steps to prevent them. It is also comprehensive with respect to the kinds of systems of interest. It discusses, for example, human systems, such as hospitals and emergency infrastructures. It also discusses large and complex hardware and software systems, such as space systems and commercial aircraft. Survival and recovery from disruptions are central to the study of system resilience. In order to define a system capable of avoiding an accident or surviving and recovering from a disruption, it is necessary to define the disruptions that may occur. These disruptions fall into two major categories: disruptions of input and systemic disruptions. The architecting of resilient systems is dependent on creating resilient attributes of the system of which adaptability is one of the most important. The creation of adaptability relies on advanced systems approaches utilizing the principles and heuristics of adaptability. This tutorial also discusses many of the cultural barriers to avoiding accidents and recovering from them. It presents a survey of promising methods to deal with them. Another subject of interest is whether the propensity to accidents can be inferred from statistical analysis of defects and near misses. This tutorial summarizes some promising research on the subject that suggests that it is possible to do this. |
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