Machine learning enables a computer to process large quantities of data, automatically recognize patterns and “learn” correlations. As it does this, the computer not only learns the data from memory, it generalizes the information in order to evaluate previously unknown data.
Examples of machine learning can be found everywhere – in the Google translation feature, product recommendations from Amazon, or in the recognition of pedestrians in autonomous driving.
Industrial processes, such as tool manufacturing or monitoring of production systems, can be optimized through machine learning. Quality parameters can be monitored during the manufacture of tools.
Classification on the basis of these parameters enables the early detection of faulty processes and production errors.
This type of machine learning arranges sensor-based data to a finite number of classes or groups and thereby identifies outliers. This reduces the number of defective products and thus production costs.
Optimizing maintenance is the focus when it comes to monitoring production systems. Standard maintenance plans work according to fixed time schedules that don’t take into account the current status of the systems. This can lead to unnecessary or overdue maintenance activities, among other things. With the help of regression, functional correlations between equipment wear and key production indicators, such as system parameters, process parameters and other sensor values, can be learned. This enables conclusions to be drawn about the progression of tool wear, which makes predictive maintenancepossible – that is, it helps to determine the optimal time for maintenance. This leads to lower maintenance costs and reduction of downtime.
The data analysis specialists from the USU business segment Katana have extensive experience in applying machine learning methods in the industrial sector. Take advantage of our knowledge and our solutions for optimizing your production processes to reduce your costs and improve your quality.
Some people call this artificial intelligence, but the reality is this technology will enhance us. So instead of artificial intelligence, I think we'll augment our intelligence.
Katana, the data analytics segment of the USU Group, has extensive experience in the application of machine learning methods in the industrial sector. Take advantage of our knowledge and our solutions for building your data-driven business models to reduce your costs and improve your quality and value added.