Dürr Expands AI for New and Existing Paint Shops

Photo Credit: Dürr

Dürr Systems Inc. (Southfield, Mich., U.S.) is expanding the scope of its artificial intelligence (AI) applications with analysis software from the DXQ product family for sealing. According to Dürr, the software’s interface makes it possible to incorporate robots from existing paint shops for the first time.

Increasing application quality and plant availability using modern IT involves recording relevant machine data in real-time and uploading them to a database. This data can include information on raw materials, products, axis positions, temperatures or events (e.g., alarms, program start and end times). On expanding the AI, Dürr’s vice president of control systems, Jens Häcker, says, “The goal is to combine this with historical data and machine learning to detect previously unknown defect sources or to precisely plan maintenance intervals.”

According to Dürr, the key to leveraging this data is connectivity — in other words, having the right interface at the control level to obtain the information provided by robots, ovens, cathodic electrocoating systems or conveyor technology in the first place.

Although the demand for digital applications is high, Dürr says operators in existing plants are constrained because most of their systems do not have connectivity, and the right interface for data acquisition is found only in the later generation of Dürr robots. Previously, there was no way to connect earlier models, robots from other manufacturers and technology outside of paint application. Dürr’s solution is an adapter made up of hardware and software components that can connect to all current fieldbus technologies. The adapter is offered by Dürr in cooperation with Techno-Step (Böblingen, Germany), a specialist in process data analytics and diagnostics that has been part of the Dürr Group since 2020.

Photo Credit: Dürr

According to the company, the adapter provides connectivity to almost all common robots and disciplines, and data in the necessary resolution is available in a few milliseconds. “Operators are thus able to read the available sensor and actuator data from their existing plants and to integrate the entire spectrum of disciplines, from pretreatment to application to conveyor technology, into one piece of analytical software,” Häcker says. “With DXQequipment.analytics, they get detailed insight into the various process steps and all the systems involved in them along the entire value chain.”

Additionally, the DXQequipment.analytics software package includes the Advanced Analytics module, which Dürr claims is the first market-ready solution to use AI to increase overall equipment effectiveness (OEE) in the paint shop. Dürr has adapted the AI models that analyze the robot and process data for sealing’s specific requirements, expanding its possibilities to this discipline.

Dürr suggests that AI will make it possible to precisely detect defect sources at an early stage when applying high-viscosity materials, and to determine optimal maintenance schedules. For example, sealing material can sometimes partially clog application nozzles, which changes the material jet and leads to quality defects that require rework to fix. Unlike conventional control technology, the DXQ software detects this defect and enables earlier intervention.