Artificial Intelligence, Machine Learning & Predictive Maintenance
Source: hannovermesse

Predictive maintenance is a major focus theme at the upcoming HANNOVER MESSE 2020. Many of the show’s exhibitors are providers of AI-powered software solutions that predict faults and prevent costly unplanned shutdowns in connected manufacturing plants and systems.

“Every minute of every hour that a production line or facility is shut down owing to technical problems is a major cost burden. That’s where AI-based predictive maintenance comes into play,” explained Hubertus von Monschaw, Deutsche Messe’s Global Director Digital Ecosystems for HANNOVER MESSE.

“If the machines in question are able to talk to one another and exchange data with one another, then potential problems can be detected relatively quickly by running background AI-based software that is able to identify anomalies and other normally unforeseeable faults. The key is that the problems and anomalies are detected as early on as possible so as to avoid outages.”

But that’s not all. Predictive maintenance is also a very useful way of interconnecting digital value chains. Once the predictive maintenance system knows the exact point in the future at which a particular machine will need to be shut down for maintenance, it can, for instance, automatically initiate the associated logistics processes. This ensures that all the relevant work and parts ordering processes are properly coordinated.

A good example of this is Datawatch, which Altair Engineering will be showcasing in Hall 17. Datawatch can be integrated into existing infrastructure and addresses predictive maintenance in three steps: data preparation, generation of data models, and real-time prediction. The platform brings together users with diverse skills and backgrounds from diverse disciplines.

Another example is Data Lighthouse, a Hamburg-based software development company that will be presenting an array of innovations in Hall 16. Data Lighthouse will show how industrial firms can leverage its cloud-based Data Grid solution to monitor their production plants in real time and predict their behavior. The solution uses digital twinning and mobile end devices to enable users to continuously monitor the condition of their production facilities.

Artificial Intelligence, Machine Learning & Predictive Maintenance
Source: hannovermesse

And last but not least, Saarbrücken-based consulting and software firm Scheer GmbH will be presenting a lineup of AI-based solutions in Hall 17. Among them will be Predictive Intelligence, a software application powered by self-learning algorithms. The application enables users to reduce production rejects, predictively plan maintenance runs and reduce plant energy consumption.

In a very real sense, predictive maintenance goes hand-in-hand with machine learning because in order to be able to reliably detect potential faults, a predictive maintenance system needs to have prior knowledge of all possible fault situations. By “teaching” the maintenance system about all the various possible fault situations, AI-based machine learning software enables it to detect specific faults in real-time and initiate remedial action. HANNOVER MESSE 2020 will therefore have a very strong focus on machine learning.