German trailer manufacturer Krone’s recent project, "value chAIn", is currently using artificial intelligence (AI) to analyze optimization possibilities for product and process quality, performance, and availability.
To mitigate error management across the value chain, the Krone project team has defined four concrete use cases.
The first use is being examined in a study regarding Krone Cool Liners production in Lübtheen, Germany. To examine the "predictive quality" of the AI, the system will predict product quality based on observable variables such as plant parameters or environmental conditions. In this way, expected defects can be detected at an early stage and counteracted by optimizing the process parameters.
The second use case is about the error management of quality assurance in Werlte.
"With the help of artificial intelligence (AI), we are setting up a sensitive early warning system in the areas of defect management and complaints," project manager Felix Bartels from the Krone Business Center said. "All complaint data is recorded and algorithms are calculated, for example, whether so-called defect peaks occur in a product or a component. If the suspicion of a possible problem is confirmed, the product specialists will take a close look at the problem and decide on the further course of action.
"value chAIn provides … analysis tools and derives a recommendation for action for the employees in the specialist departments from the data. The goal is to develop a decision support system.”
The other two use cases focus on the Krone Telematik Box, whose data may be used for further digital services.
The company’s primary goal is to determine whether its data can be presented clearly and simply, but it would also like to develop further useful features based on the telematics data that make the transport of goods from A to B even more transparent.
"For example, the recording of abrupt braking or strong vibrations of the vehicle due to bad road conditions … would be conceivable here," Bartels said. "It would also be conceivable to display the specific CO2 score for a transport route."
Finally, Krone has been focusing on "predictive maintenance" for several years now.
"The main issue here is to proactively minimize possible trailer downtimes," Bartels concluded. "If the AI warns, for example, that a wearing part is very likely to fail within a foreseeable period of time, this part could be replaced directly at the next opportunity as part of an already planned maintenance."