Durr > Case Studies > Applying Artificial Intelligence to Paint Shop Robots

Applying Artificial Intelligence to Paint Shop Robots

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 Applying Artificial Intelligence to Paint Shop Robots - IoT ONE Case Study
Technology Category
  • Analytics & Modeling - Machine Learning
Applicable Industries
  • Automotive
Applicable Functions
  • Discrete Manufacturing
Use Cases
  • Predictive Maintenance
  • System Integration
The Challenge

Factories in the automotive industry have enormous amounts of latent data about manufacturing processes, raw materials, and products. The key to leveraging these data assets is connectivity with the right interface at the control level to get at the information provided by robots, ovens, cathodic electrocoating systems or conveyor technology. Operators in existing plants are often constrained because most of their systems do not have connectivity and the right interface for data acquisition.

The Solution

Providing this kind of interface for existing robots drove Dürr to develop its DXQequipment.analytics software to bring connectivity to many types of existing robots. The technology offered by Dürr is an adapter comprised of hardware and software components that can connect to all current fieldbus technologies and provide data in the few milliseconds range. The adapter is offered by Dürr in cooperation with Techno-Step, a specialist in systems for process data analytics and diagnostics that has been part of the Dürr Group since 2020. According to Dürr, this hardware and software combination make it possible for inventory and third-party plant equipment to be intelligently networked with Dürr’s DXQ software products.

The DXQequipment.analytics software includes an Advanced Analytics module, which uses AI to increase overall equipment effectiveness (OEE) in the paint shop.

Operational Impact
  • [Data Management - Data Access]

    This enables older generations of robots to exchange data, allowing the relevant processes to be analyzed by Dürr’s digital product portfolio.

    With DXQequipment.analytics operators get detailed insight into the various process steps and all the systems involved in them along the entire value chain

  • [Process Optimization - Predictive Maintenance]

    One example of the application of DXQequipment.analytics in paint shop robots is the detection of nozzle clogs. When the sealing material partially clogs the application nozzle, it can lead to quality defects that require rework to fix. Unlike conventional control technology, the DXQ software detects this defect and enables earlier intervention.

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