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Battling Risks in High-Tech Systems
In his wondrous Against the Gods, historian Peter L. Bernstein poses the question of what distinguishes the thousands of years of history from what we believe signifies modern times. His answer: the mastery of risk - the notion that ‘the future is more than a whim of the gods and that men and women are not passive before nature’. Without the tools of quantitative risk assessment, he claims, “engineers could never have designed the great bridges that span our widest rivers, homes would still be heated by fireplaces or parlour stoves, electric power utilities would not exist, polio would still be maiming children, no airplanes would fly, and space travel would be just a dream”. Bernstein’s conclusion leaves no doubt: quantitative risk assessment is at the roots of technological progress, turning once perilous endeavours into rational and well-considered processes of risk-taking.
It should be no surprise that one can find a copy of Bernstein’s book in the office of Mariëlle Stoelinga . As Professor of Risk Management for High-Tech Systems, Mariëlle builds on the many mathematicians, logicians, and innovators before her to keep the risks associated with complex systems within ‘acceptable boundaries’. Mariëlle is well-aware of these risks. Bridges may collapse, airplanes may crash and space shuttles may never return home. Modern technologies introduce new risks: drones may spy in your backyard, or interfere with regular air traffic; coaches in hyperloops may get stuck underground, or their inside pressure may drop. At the same time, Mariëlle would agree with Bernstein that it is exactly these kinds of technologies that have dragged us into modern times. As Mariëlle puts it herself: “no risk, no fun”.
Rather, we should ensure that the risks associated with technological systems stay as low as possible, while we do our best to maximize the benefits. Quantitative risk assessment is at the core of her mission. By introducing data from the past, modelling and analysing it, predictions about the future can be made. As such, technological progress can be steered into beneficial and hopefully risk-free directions. In this regard, Mariëlle uses computer science to her advantage, making risk models precise and transparent – not based on feelings, but on facts and figures. Using fault trees, model-based testing, and architectural reliability modelling, Mariëlle develops techniques to “analyse, predict and improve the reliability of technological systems”. In the PrimaVera-project, Mariëlle focuses particularly on ‘just-in-time predictive maintenance’. Using big data and smart sensors, she explains, we can better predict upcoming malfunctions in complex systems and do maintenance exactly when it is required. For example, Mariëlle collaborates with the Dutch Railways to keep train travels free from unexpected delays. By collecting appropriate data, she analyses to which extent heavy freight trains, accelerating and decelerating trains, and temperature differences contribute to unexpected defects in the railway system. “The better we understand these factors, the more effective maintenance is”.
At both the University of Twente and the Radboud University, Netherlands, Mariëlle continues her journey into risk management - on the PrimaVera-project, but also on the CAESAR-project. This ERC-granted project aims to develop a “framework for the joint analysis of safety and security”. Throughout, Mariëlle’s mission remains the same: to combat risk as much as possible. ‘As much as possible’, indeed, because Mariëlle is aware that, as sophisticated as our mathematical models and algorithms may be, the future is inherently unpredictable. In this regard, Bernstein and Mariëlle share a common claim: “[the] goal of wresting society from the mercy of the laws of chance continue to elude us”. Mariëlle’s main source of inspiration, however, can be found closer to home. Already at a young age, her father taught her the basics of electronics; while her mother was one of the first scientific programmers in the Netherlands at the forerunner of what is now called the Eindhoven University of Technology.
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- 5 miljoen voor Predictive maintenance met big data algoritmen. (2019, June 12). Link Magazine. Retrieved from: https://www.linkmagazine.nl/5-miljoen-voor-predictive-maintenance-met-big-data-algoritmen/ (Accessed 12-01-2022).
Bernstein, P.L. (1996). Against the Gods: The Remarkable Story of Risk. New York City, New York: John Wiley & Sons, Inc.
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Nesvarova, M. (2019, December 10). ERC Consolidator Grant for Mariëlle Stoelinga. Retrieved from: https://www.utoday.nl/news/67696/erc-consolidator-grant-for-marielle-stoelinga (Accessed 12-01-2022).
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Stoelinga, M. (2018). A certain risk: Quantitative risk management for high-tech systems. University of Twente. Retrieved from: https://www.utwente.nl/en/academic-ceremonies/inaugural-lectures/booklets-inaugural-lectures/2018/oratieboekje-marielle-stoelinga.pdf (Accessed 12-01-2022).
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