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A knowledge-based multipass welding distortion estimation method for a multi-robot welding off-line programming and simulation software

Hannu Lund, Sakari Penttilä, Tuomas Skriko

2020Procedia Manufacturing13 citationsDOIOpen Access PDF

Abstract

The current robotic welding off-line programming software packages do not consider the effect of welding distortions although the welding distortions are well-known phenomena. Due to the distortions, off-line programmed robot programs will have inaccuracies in robot positions. The purpose of this study is to develop a method for estimating the welding distortions during the jigless multi-robot welding production using a robot welding off-line programming software as a simulation environment. The applied methodology is to measure distortions of welded S700 workpieces with laser scanner and by manual measurement, and create knowledge-based welding distortion estimation method in the simulation software. The results of this study indicate that the distortion in welded workpiece can be measured with laser scanner or manually and during simulation the robot was able to edit its position according to the measured estimation. Laser scanning was found to be preferred measuring method as the data can be collected digitally.

Topics & Concepts

WeldingRobot weldingDistortion (music)RobotSoftwareComputer scienceLaser beam weldingMeasure (data warehouse)Artificial intelligenceComputer visionMechanical engineeringEngineeringData miningProgramming languageAmplifierBandwidth (computing)Computer networkWelding Techniques and Residual StressesManufacturing Process and OptimizationRobot Manipulation and Learning
A knowledge-based multipass welding distortion estimation method for a multi-robot welding off-line programming and simulation software | Litcius