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

Author:

Lund Hannu,Penttilä Sakari,Skriko Tuomas

Funder

Business Finland

Publisher

Elsevier BV

Subject

Artificial Intelligence,Industrial and Manufacturing Engineering

Reference7 articles.

1. A changeable jig-less welding cell for subassembly of construction machinery;Bejlegaard;IFIP Adv. Inf. Commun. Technol.,2018

2. Influences of heat input, welding sequence and external restraint on twisting distortion in an asymmetrical curved stiffened panel;Liang;Advances in Engineering Software,2018

3. Influence of thermo-mechanical material properties of different steel grades on welding residual stresses and angular distortion;Bhatti;Materials & Design (1980-2015),2015

4. Methodology for predicting the angular distortion in multi-pass butt-joint welding;Adamczuk;Journal of Materials Processing Technology,2017

5. F. Sikström, & M. Ericsson, Integration of finite element analysis and computer aided robotics for advanced programming of robotized welding. ASM Proceedings of the International Conference: Trends in Welding Research. (2009) 454-460. doi:10.1361/cp2008twr454.

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1. Progress, challenges and trends on vision sensing technologies in automatic/intelligent robotic welding: State-of-the-art review;Robotics and Computer-Integrated Manufacturing;2024-10

2. Experimental Verification of Knowledge-Based Welding Distortion Estimation Method;Lecture Notes in Mechanical Engineering;2023

3. Suppression of humping bead in high-speed triple-wire gas indirect arc welding;The International Journal of Advanced Manufacturing Technology;2022-09

4. Overview on the digitized production of welded steel structures;Welding in the World;2022-01-03

5. Robot autonomous judgment system based on improved computer algorithm;International Journal of System Assurance Engineering and Management;2021-11-13

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