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Start-up brings real-time AI to machines on the shopfloor

03 January, 2020

A German start-up that Festo bought last year claims to be implementing AI (artificial intelligence) directly on machines on factory floors and interpreting data there in real time. Resolto Informatik says it already has applications at work in manufacturing environments.

Until now, most industrial applications of AI have been restricted by problems of latency (reaction times) and by the vast amount of data required when connecting to the cloud. Resolto’s Scraitec software interprets data in the field, close to shopfloor machines. It says that this makes it possible to save energy, shorten cycle times and reduce machine failures and production errors.

The software knows the healthy condition of a plant and spots any anomalies, providing real-time analyses of sensor data. It is said to deliver diagnoses quickly and accurately, and to suggest recommended actions.

“The platform continuously learns from actual operation, integrating the knowledge of the engineers and the customer’s technical experts – we call it the ‘human-in-the-loop’ principle,” explains Tanja Maaß, Resolto’s founder and managing director. The machine learning and AI functions interpret information predictively to optimise parameters actively, or can send instructions to staff via, for example, their smartphones.

One end-user already using the technology is the appliance manufacturer, Miele, which was experiencing fluctuating quality in its production processes, but was unable to find the causes. Miele operates complex production lines, where products are manufactured sequentially. It is not sufficient to look at the individual stations separately.

The company’s production managers wanted a system that could detect anomalies in complex manufacturing flows automatically. “Deep learning seemed to be the right approach for this,” Maaß explains. An integrated database was developed that brought together different measurement systems. Additional measuring points were configured to support the database. Resolto’s software was used to model the production lines as an integrated system and, in so doing, boosted Miele’s throughput by 1.5%.

Another application of the technology was at a car-maker and involved a pneumatic clamping system costing just €100. However, unforeseen production stoppages could cost several hundred thousand euros, so the car-maker wanted an early warning system that would indicate any wear and the slowing down of cycle times. The Scraitec software provided real-time data analytics and a learning system that could be used for the predictive maintenance on any type of clamping system.

Resolto Informatik’s managing director, Tanja Maaß: the platform continuously learns from actual operation

Resolto uses Festo’s CPX-IOT IoT gateway to monitor machines and plants at field level and to link them to the cloud or Festo dashboards. A software component called ScraiField runs in a small controller close to the machines. A pre-trained model interprets data streams without needing a connection to a component called ScraiBrain located in the cloud. ScraiBrain has access to a host of preconfigured application models.

“AI algorithms can be integrated both in the cloud and directly in the components from Festo,” Maaß explains.

Resolto says that Scraitec will help users to optimise utilisation of their plants, as well as cutting their maintenance costs by predicting events and recommending action for known fault patterns.

It adds that combining its software with plants and machines will transform them into digital tools and open up new business models for machine and plant manufacturers. They will be able to offer new forms of service that add value by the automated coordination of maintenance teams.

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