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ROBOTICS

SUSPICON: Prediction of robot-related failures in spot welding applications with industrial AI methods


Reduce operational downtime caused by industrial robots by about 30%.

Industrial robots, production of MAGNA, BMW 5 series body shell

Credit: MAGNA

Project content

In the manufacturing industry, different production steps follow each other fluently and in close sequence. Any delay of a machine thus has a direct effect on all subsequent and previous work steps. In this project we try to predict the system behaviour in welding applications together with our project partners in order to reduce the number of failures significantly. The combination of different mathematical and numerical methods of reliability modelling and quality control paired with methods of industrial artificial intelligence is the foundation for this. Automatically derived instructions for action should ultimately help store floor staff to eliminate impending incidents at an early stage.

SUSPICON helps to predict future malfunctions of industrial robots and to prevent downtimes.

Goal:

Prediction of robot failures in spot welding applications and proposal of appropriate instructions
Investigation and development of process and data driven methods for the prediction of machine failures
Reduction of operational downtime by about 30%.

 

Project partner

The project is carried out in cooperation with  Fraunhofer Austria Research (consortium leadership) and Craftworks. Magna Steyr  is the challenge provider.

Project data

Financing agency: ESMERA, EU

Project period:  05/2020-03/2021

Funding
For further information please contact
ESMERA Project- SUSPICON