Plant manufacturers can expand their business model and generate additional income by guaranteeing machine availability over a certain period of time.
Many machine manufacturers are asking themselves what they can do in the age of digitalization and Industry 4.0 to stay ahead of the competition. What customer requirements already exist or will arise in the future? How can you make your business fit for the future?
Predictive maintenance with adaptive algorithms
Condition monitoring, the monitoring of machine status using machine data, is largely state of the art. Machine data is much more useful if it is used for predictive maintenance. This usually requires additional sensor-based measured values. In this way, however, risks due to previously unforeseeable, unplanned system downtimes can be greatly reduced, almost eliminated.
Predictive maintenance uses intelligent algorithms that provide a forecast of when individual system components are likely to fail based on the combined analysis of many different operating parameters. This enables the plant operator to plan downtimes in such a way that they have as little impact as possible on the planned operating sequence. The algorithms used for this are often adaptive, i.e. they improve their forecasting quality with the number of monitored systems. A globally accessible cloud is the ideal place to run such adaptive systems, especially if systems at different locations are to be monitored centrally.
An efficient analysis can only be carried out if all operating parameters are brought together, collected and evaluated centrally. For example, this can involve a relatively large amount of work for machine parks that have grown over the years. But even with new systems, many system operators want the option of connecting to cloud services of all kinds. Operators may also want to network a large number of globally distributed systems and monitor them from a central control center.
As a rule, plant operators no longer want to plan their monitoring application in detail themselves and assemble the individual components such as sensors, data acquisition devices, measurement data management and software for visualization and analysis on their own. Instead, they look for a complete solution in which they receive all components, including installation and commissioning, from a single source. This way, they can rely on the functioning of all parts of the system and only need one point of contact when it comes to servicing and maintaining this system.
Image: Shubby Studio@Adobe Stock, Delphin Technology AG