Data-Driven Intelligent Predictive Maintenance of Industrial Assets

  • Olga FinkEmail author
Part of the Women in Engineering and Science book series (WES)


Condition monitoring and predictive maintenance enable to focus on the operating and degradation conditions of a specific asset and designing maintenance policies that are optimal for the single asset and not for an entire fleet or a population of similar assets. While this was already possible for critical systems such as power plants for decades, decreased costs of condition monitoring solutions enabled a tight health monitoring also for less critical devices, enabling thereby an improved availability of the assets and decreased life cycle costs. With the increased accessibility to large amounts of condition monitoring data, the challenges of the developed predictive maintenance applications have also increased. The book chapter provides an introduction to predictive maintenance and the current state of knowledge in the field, particularly focusing on the data-driven approaches. It points out challenges and finally presents approaches that overcome some of the existing challenges.


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© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Chair of Intelligent Maintenance SystemsETH ZürichZurichSwitzerland

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