In recent years many industrial and infrastructure asset owners are shifting towards data-driven solutions for condition monitoring and intelligent maintenance planning of their equipment. Old paradigms such as “fix it when it fails” or alternatively preventive maintenance are being replaced by condition-based and predictive maintenance algorithms. What are the practical implications for asset owners and manufacturers if they would like to deploy such advanced algorithms? What are the benefits? What are the challenges and how can they be tackled? How can industry profit from recent advances of applied research, in particular in the field of machine learning and deep learning?In the meetings of the “Smart Maintenance” expert group we gather experts from industry and from applied research in order to address these questions. We organize webinars showing case studies of innovative smart maintenance applications in industry, focusing not only on success stories but also on challenges, open problems and practical solutions for successful deployment. We encourage our members to participate actively in the discussions and provide us with input out of their own experience and interest domains. With this we provide a complete view of smart maintenance, covering all relevant aspects: from business case definition through data management, data analytics up to implementation and feedback by an engineering team in a commercial environment.