Intelligent predictive maintenance control using augmented reality

Modern manufacturing industry is currently facing significant challenges with regard to the concept of Industry 4.0. The promise of increased productivity and flexibility in manufacturing processes can not be achieved without implementation of systems and advance methods based on smart technologies. Implementation of Industrial Internet of Things (IIoT), Condition Monitoring, Big Data, Cloud computing, virtual and augmented reality in maintenance processes will significantly increase the effectivy and quality of manufacturing processes as well as eliminate the human factor. Under this perspective, cyber- physical systems can be accessible from remote location; process paramters can be visualized at real time and prediction of unexpected production stop due to machine breakdown will be significantly reduced. The paper deals with the development of effective approach to real-time process control using parameters visualization of manufacturing process with the use of augmented reality smart glasses. Collected data from condition monitoring sensors from electric monorail system are evaluated in real time and visualized in the field of maintainer view. Critical values from field of sensors are highlighted and enable to predict manufacturing breakdowns. On real example from automotive industry will be demonstrated the signification and effectivity for maintenance of electric monorail system and potential for application in different types of modern industrial processes with the focus on rule-based intelligent predictive maintenance control.