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Abstract:
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Modern technological developments, such as smart chips, sensors, and wireless networks, have changed many data collection processes. Modern engineering systems, such as jet engines, wind turbines, or even automobiles, are well equipped with sensors that generate a massive amount of data, which can be used to make reliability predictions and do prognostics. The arrival of big data in reliability brings challenges and opportunities in reliability analysis, which needs tremendous research effort to address those challenges. In another aspect, machine learning and deep learning methods are popular in many applications. The reliability and safety of artificial intelligence systems, such as the safety of autonomous cars, need to be demonstrated so that people can use them with confidence. The reliability of AI systems is a complex problem, which involves hardware, software, the environment, and human-machine interactions, providing numerous opportunities for doing cutting-edge research.
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