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Component reliability plays a pivotal role in industrial systems, which are evolving with larger complexity and higher dimensionality of data. It is insufficient to ensure reliability and prevent failure based only on empiri- cal and parametric assumptions. Driven by huge amount of historical data, data- and statistics-based approaches aided by artificial intelligence (AI) are emerging as promising solutions. Especially, with the introduction to deep learning technology, the powerful ability of hierarchy representation is re- markably enhanced with deep cascaded layers. Furthermore, the demand for AI technology is high, and the applicability of the model in securing reliability, failure prediction and prevention in the industrial system is still nontrivial. Yet, there hardly exists such a systematic review of the AI-based approaches. In this survey, we provide a comprehensive overview of the AI- aided approaches to failure analysis …