Machine learning is one of the biggest challenges in Industry 4.0. Systems that can go beyond executing simple instructions and are capable of learning, processing and evaluating is the key to accessing the full potential of digitization and the smart factory.
The main benefits of machine learning are primarily an increase in production efficiency and the ability to perform unprecedented predictive maintenance. As a result, companies can produce high-quality products at minimal cost.
What makes all this possible? Above all, data. Let’s see how.
The role of Big Data in machine learning
Experience is the basis of all forms of learning. In computers world, experience is data: the insight on a process, anomaly, etc. The more data you have, the greater the learning.
It is clear, then, that Big Data is crucial in the machine learning process. Today the volumes of information circulating in the production plants are immense. Which presents unprecedented and virtually limitless machine learning potential. In fact, through the analysis of all these production data, the machines can identify models independently, perform specific tasks without being programmed to do so and make operational decisions with minimal human input.
However, data (experience) alone is not enough: we also need intelligence to process it. In this case, repetitiveness-based calculation algorithms are essential so that machines can learn from previous processing to make reliable and replicable decisions to produce the desired results.
Machine learning and predictive maintenance
One of the most useful and effective applications of machine learning is predictive maintenance. The ability to rely on machines capable of processing data and learning automatically means being able to anticipate anomalies and malfunctions, so as to act in real time before they actually occur.
Such a level of predictive maintenance allows to cut both downtimes and production costs. Hence the opportunity for the industry to be more productive, efficient and competitive.
ESA and machine learning
ESA promotes machine learning on different levels. Starting from the flexibility in data acquisition, with products that have always been multi-protocol and therefore able to communicate with most of the automation devices on the market.
Finally, we simplify data transfer to the Cloud thanks to Everyware and compatibility with the OPC-UA and MQTT standards, as well as data analysis and visualization via dashboards.