IoT Architecture and Solutions for Predictive Maintenance of Mobile Machinery
Jani Hietala, Kalle Raunio, Tero Jokinen, Petri Kaarmila · IECON 2022 – 48th Annual Conference of the IEEE Industrial Electronics Society · 2022
Continuous development of advanced web and IoT technologies facilitate new solutions for scalable data management systems. Data can be transferred over the internet efficiently in standardized formats. We propose a system architecture applicable to both mobile machinery and other industries. We introduce standards and technologies for collecting and analysing data in addition to exchanging the data in cloud applications and with partner systems. Data is exchanged in a standardized MIMOSA CCOM format over efficient MQTT communication protocol for near real-time updates of operation. Eclipse Arrowhead framework is used to securely manage the edge and cloud services. VTT O&M Analytics provide predictive maintenance services for mobile machinery based on the collected data. We describe in detail a system designed for collecting and analysing data from the combination seed drill. Our architecture facilitates monitoring and predictive maintenance, thus improving crop yields and OEE.