Resilience Engineering In industrial applications, accidents in large, complex systems such as oil wells, oil refineries, chemical processing plants, electri-
cal power systems, transportation, and medical services can have
major impacts on the company and the surrounding community.
Sometimes the problems do not arise in the organization but out- side it, such as when fierce storms, earthquakes, or tidal waves demolish large parts of the existing infrastructure. In either case, the question is how to design and manage these systems so that they can restore services with a minimum of disruption and dam- age. An important approach is resilience engineering, with the goal of designing systems, procedures, management, and the training of people so they are able to respond to problems as they arise. It strives to ensure that the design of all these things—the equipment, procedures, and communication both among workers and also ex- ternally to management and the public—are continually being as- sessed, tested, and improved.
Thus, major computer providers can deliberately cause errors in their systems to test how well the company can respond. This is done by deliberately shutting down critical facilities to ensure that the backup systems and redundancies actually work. Although it might seem dangerous to do this while the systems are online, serving real customers, the only way to test these large, complex systems is by do- ing so. Small tests and simulations do not carry the complexity, stress levels, and unexpected events that characterize real system failures.
As Erik Hollnagel, David Woods, and Nancy Leveson, the au- thors of an early influential series of books on the topic, have skill- fully summarized:
Resilience engineering is a paradigm for safety management that fo- cuses on how to help people cope with complexity under pressure to achieve success. It strongly contrasts with what is typical today—a paradigm of tabulating error as if it were a thing, followed by interven- tions to reduce this count. A resilient organisation treats safety as a core value, not a commodity that can be counted. Indeed, safety shows itself only by the events that do not happen! Rather than view past success as a reason to ramp down investments, such organisations continue to invest in anticipating the changing potential for failure because they appreciate that their knowledge of the gaps is imperfect and that their environment constantly changes. One measure of resilience is therefore the ability to create foresight—to anticipate the changing shape of risk,
before failure and harm occurs. (Reprinted by permission of the publishers. Hollnagel, Woods, & Leveson, 2006, p. 6.)
The Paradox of Automation Machines are getting smarter. More and more tasks are becoming fully automated. As this happens, there is a tendency to believe
that many of the difficulties involved with human control will go
away. Across the world, automobile accidents kill and injure tens
of millions of people every year. When we finally have widespread
adoption of self-driving cars, the accident and casualty rate will
probably be dramatically reduced, just as automation in factories
and aviation have increased efficiency while lowering both error
and the rate of injury.
When automation works, it is wonderful, but when it fails, the
resulting impact is usually unexpected and, as a result, danger-
ous. Today, automation and networked electrical generation sys-
tems have dramatically reduced the amount of time that electrical
power is not available to homes and businesses. But when the elec-
trical power grid goes down, it can affect huge sections of a coun-
try and take many days to recover. With self-driving cars, I predict
that we will have fewer accidents and injuries, but that when there
is an accident, it will be huge.
Automation keeps getting more and more capable. Automatic
systems can take over tasks that used to be done by people,
whether it is maintaining the proper temperature, automatically
keeping an automobile within its assigned lane at the correct
distance from the car in front, enabling airplanes to fly by them-
selves from takeoff to landing, or allowing ships to navigate by
themselves. When the automation works, the tasks are usually
done as well as or better than by people. Moreover, it saves peo-
ple from the dull, dreary routine tasks, allowing more useful,
productive use of time, reducing fatigue and error. But when
the task gets too complex, automation tends to give up. This, of
course, is precisely when it is needed the most. The paradox is
that automation can take over the dull, dreary tasks, but fail with
the complex ones.
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