Sensors, connected devices, and the Internet of Things (IoT) are changing our capabilities to gain insights into the inner workings of industrial machines in manufacturing. Nowadays, machines in factories are often equipped with a large number of sensors constantly collecting data points on a high variety of measurements. The data recorded can be used to improve monitoring and maintenance as well as optimise multiple aspects of these machines.
One particular example of complex industrial machines that we have recently worked on are steam boilers. Steam boilers create steam by applying heat energy to water and are essentially used where (hot) steam is needed, such as in manufacturing, the food industry, agriculture, and many more.
The long-term goal of this project was to optimise efficiency of the steam plant and build a system that implemented predictive maintenance and alarming. As a first step we aimed at analysing the data at hand in order to identify patterns and anomalies that could point to inefficiencies and failures of the steam plant.