When is the optimum time to maintain a production plant? Reliable data can now be used as a basis for predictive maintenance. Predictive maintenance is the buzzword. The application is based on advanced analytics, a big data technology that can be used to derive future scenarios.

Until now, machines and systems were subject to a fixed maintenance cycle that was determined at some point. However, the actual use of a machine is not normally based on fixed times and intervals, but on individual criteria such as: What is the machine used for? How old is it? A maintenance cycle at the same intervals does not do justice to this fact. With predictive maintenance, the maintenance of a machine can be controlled according to its actual maintenance requirements. To this end, data is collected and analyzed during operation. Based on these data records, the system continuously learns and makes it possible to interpret live data using a model. This allows individual maintenance schedules to be defined for machines and components. This makes production smarter and reduces the risk of breakdowns.

One area of application for advanced analytics is the production of filling and packaging solutions. Certain process parameters of machines and systems are monitored in order to detect quality deviations in advance. The Zenon software platform from Copa-Data can be used to control this process, allowing the collected data to be visually processed and analyzed. This allows valuable information to be obtained: The wear and tear of a bottle coating station can be detected at an early stage and maintenance appointments can be planned in advance accordingly. Another possible application is the classification of events according to severity. Is it just a warning - or can a critical fault be assumed?

Advanced analytics is also used in resource management and production planning. The data collected from a production plant can be used to create a picture of resource consumption - not just for the past, but extrapolated to the end of the accounting period.

Another area of application is process optimization. In order to improve the production result of a machine, it is first necessary to identify how individual parameters affect the production process. This process can be greatly accelerated with the help of advanced analytics, as the technology makes it possible to determine correlations between individual values and data points. as