Data-Driven Maintenance: Combining Predictive Maintenance and Mixed Reality-supported Remote Assistance

Abstract Predictive Maintenance and Mixed Reality are two enabling technologies, which enable effective ways to support future maintenance work in factories. Predictive maintenance techniques are designed to help determine the condition of machines and machinery parts in order to estimate when maintenance should be performed. Mixed reality describes ways to merge digital (or virtual) information with real environments, where both worlds can interact in real-time. Both technologies show potential to support workers in industrial settings to accomplish their tasks more effectively. Especially the field of remote assistance (or remote support) where workers are visually guided through maintenance tasks via smartphones or smartglasses and mixed reality-supported information, are described to be disruptive. In this paper, we describe our concepts and ideas to integrate both technologies into future learning factories. Following this idea, predictive maintenance algorithms trigger a specific maintenance task and inform a technician. If the technician needs further support at the component in need of a maintenance check, she can trigger a remote support call with an expert. Both can make use of anchored annotations to discuss and solve the problem. We present our current research, as well as a design proposal to combine both technologies in future learning factories.