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In automation and manufacturing industry, products are becoming more and more integrated and complex. These high technological products must operate reliably and safely in daily use as they are used in safety-critical applications (e.g. automotive domain). Post-production Failure Analysis is a process to build a progressive diagnosis and understanding of failure factors, leading to in-depth root cause analysis. In spite of a highly technological environment, the industrial process of Failure Analysis is often carried out manually, driven by single tasks coming from production, reliability testing and field returns, and relies heavily on human expert knowledge. Automation offers important opportunities here to improve the efficiency of failure analysis. Artificial Intelligence and Machine Learning algorithms are increasingly playing a leading role in suggesting solutions in fields related and not limited to anomaly detection, condition monitoring, failure analysis and root cause analysis in many domains. Therefore, this special session aims at discussing recent advances and developments in this field. In addition, recent advances coming from Industry 4.0 to support failure analysis on high technology manufactured devices are highly relevant for further automation of the failure analysis and are welcomed in this special session.