“Large production plants are predestined for predictive maintenance”

In a nutshell, predictive maintenance is preventing breakdowns and preserving the value of investment goods of all kinds by means of proactive as opposed to reactive maintenance. All available operating data is collected and processed in parallel with regular, value-creating operation in order to weigh up the cost of downtimes for inspection and repairs against the potential risk of breakdowns. It involves everything from the operational readiness of all sensors and subsystems to spare parts procurement to the documentation of all maintenance processes and the correct qualification of personnel. In the digital world of Industry 4.0, predictive maintenance does all this by processing the relevant data in real time for proactive, needs-based maintenance in order to reduce outages.

No, because digitalization is making processes more complex and complicated – everything in the value-creation chain is now interconnected in this world of “connected services”. Today, a product no longer exists in isolation, but rather within a fully fledged ecosystem of services, spare parts supply, maintenance and repair, operation, sales and distribution. If we want to make room for predictive maintenance, we must consider all these factors and offer a comprehensive solution. 

Algorithmics, data analytics and artificial intelligence can all help here. The evaluation is done partly by people trained to process large volumes of data. But the majority of the analysis is done automatically on digital and cloud-based service platforms.

Predictive maintenance is useful wherever valuable investment goods with high breakdown costs are used. These could be production plants, special machines, ships, wind turbines or even airplanes. They must function reliably round the clock, and any breakdown costs a fortune – in the worst case scenario human lives. Any maintenance work is laborious and must be planned far in advance in order to prevent these cost-intensive breakdowns. Plants of this kind are predestined for predictive maintenance. Where empirical values and data from individual machines were previously primarily used, globally available sensor and analysis data can now be combined so that industrial goods can be maintained predictively over the long term in a cost-effective manner.

No, not even close. Although many plants have a wide range of sensors, most are concentrated in control rooms and are still evaluated locally, sometimes even using analog means. The data is already being collected, but it is not yet digitized and it cannot yet be viewed collectively. Even though some industry sectors have supposedly already made the transition to Industry 4.0, that does not mean that all possibilities have been fully explored. There is still a great deal of untapped potential.

We offer IT consultation and services as well as IT solutions for automatically analyzing data in order to help clients with the digital transformation of maintenance. In doing so, we work on various levels. First of all, we record operational data, available documents and sensor information. This may be for aircraft, wind turbines, cruise ships and, of course, industrial operations and investment goods of all kinds. The next stage involves aggregating all of this data on digital service platforms and deriving relevant information from it. Then, using this information, we can identify which maintenance measures can be adopted preemptively and implement and document concrete maintenance measures directly from the platform.

Here, I can name two examples. Our Windpulse platform is a predictive maintenance product for OEMs, operation managers, operators and service providers that enables reliable operation of wind turbines and makes it possible to predict and control maintenance events. The solution is designed such that we can also use it with any other investment good. The second example comes from the aviation industry. In this case, we offer a wide variety of solutions in the realm of “Maintenance, Repair and Overhaul” to help ensure smooth operation of aircraft and aircraft fleets of numerous airlines.