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The supply of customer-specific products is leading to the increasing technical complexity of machines and plants in the manufacturing process. In order to ensure the availability of the machines and plants, maintenance is considered as an essential key. The application of cyber-physical systems enables the complexity to be mastered by improving the availability of information, implementing predictive maintenance strategies and the provision of all relevant information in real-time. The present research project deals with the development of a cost-effective and retrofittable smart maintenance system for the application of ultraviolet (UV) lamps. UV lamps are used in a variety of applications such as curing of materials and water disinfection, where UV lamps are still used instead of UV LED due to their higher effectiveness. The smart maintenance system enables continuous condition monitoring of the UV lamp through the integration of sensors. The data obtained are compared with data from existing lifetime models of UV lamps to provide information about the remaining useful lifetime of the UV lamp. This ensures needs-based maintenance measures and more efficient use of UV lamps. Furthermore, it is important to have accurate information on the remaining useful lifetime of a UV lamp, as the unplanned breakdown of a UV lamp can have far-reaching consequences. The key element is the functional model of the envisioned cyber-physical system, describing the dependencies between the sensors and actuator, the condition monitoring system as well as the IoT platform. Based on the requirements developed and the functional model, the necessary hardware and software are selected. Finally, the system is developed and retrofitted to a simulated curing process of a 3D printer to validate its functional capability. The developed system leads to improved information availability of the condition of UV lamps, predictive maintenance measures and context-related provision of information.
Production systems are becoming increasingly complex, which means that the main task of industrial maintenance, ensuring the technical availability of a production system, is also becoming increasingly difficult. The previous focus of maintenance efforts on individual machines must give way to a holistic view encompassing the whole production system. Against this background, the technical availability of a production system must be redefined. The aim of this publication is to present different definition approaches of production systems’ availability and to demonstrate the effects of random machine failures on the key figures considering the complexity of the production system using a discrete event simulation.