Durr Case Studies Applying Artificial Intelligence to Paint Shop Robots

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	Applying Artificial Intelligence to Paint Shop Robots Durr

Applying Artificial Intelligence to Paint Shop Robots

Durr

Technology Category	Analytics & Modeling - Machine Learning
Applicable Industries	Automotive
Applicable Functions	Discrete Manufacturing
Use Cases	Predictive Maintenance
Services	System Integration
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. Read More
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. Read More Log in to view content
Contents

Technology Category

Analytics & Modeling - Machine Learning

Applicable Industries

Automotive

Applicable Functions

Discrete Manufacturing

Use Cases

Predictive Maintenance

Services

System Integration

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.

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.

Impact #1	[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
Impact #2	[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.

Impact #1

[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

Impact #2

[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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Overview

Applying Artificial Intelligence to Paint Shop Robots

Operational Impact