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A study on the prediction of bead geometry in the robotic welding system
Journal of Mechanical Science and Technology, 2007The gas metal are (GMA) welding is one of the most widely-used processes in metal joining process that involves the melting and solidification of the joined materials. To solve this problem, we have carried out the sequential experiment based on a Taguchi method and identified the various problems that result from the robotic GMA welding process to ...
J. S. Son +5 more
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Optimization of the FCAW process by weld bead geometry analysis
Welding International, 2009The flux cored arc welding process has grown in use in recent times as a function of its characteristics of high rate of deposition, associated with suitable mechanical properties in the welded joint. However, many aspects still remain obscure in regard to greater utilization of this process.
Lucilene de Oliveira Rodrigues +2 more
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Bead geometry prediction using multiple linear regression analysis
The International Journal of Advanced Manufacturing Technology, 2021International ...
Milhomme, Sarah +3 more
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Grey-based taguchi method for optimization of bead geometry in submerged arc bead-on-plate welding
The International Journal of Advanced Manufacturing Technology, 2008A multi-response optimization problem has been developed in search of an optimal parametric combination to yield favorable bead geometry of submerged arc bead-on-plate weldment. Taguchi’s L25 orthogonal array (OA) design and the concept of signal-to-noise ratio (S/N ratio) have been used to derive objective functions to be optimized within experimental
Saurav Datta +2 more
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Seam tracking and welding bead geometry analysis for autonomous welding robot
2017 Latin American Robotics Symposium (LARS) and 2017 Brazilian Symposium on Robotics (SBR), 2017Welding is a process recognized by the laborious work and hazardous work environment it takes place, but it is an important process in different industrial scenarios, like the shipbuilding industry. The use of robots has been increasing in recent years, reducing the human interference necessary for the process.
Luciane B. Soares +6 more
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Effects of Bead Filler Formulation and Geometry in a Car Tire
Tire Science And TechnologyABSTRACT Effects of height, thickness, and formula of the bead filler in 205/55R16 car tires on rolling resistance coefficients, indoor noise, handling, and ride comfort were examined. Height, thickness, and formula of the bead filler have an impact on the rolling resistance performance, indoor noise, static performance, handling, and
Jun-Jie Liu +3 more
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Weld Bead Geometry Prediction of Additive Manufacturing Based on Neural Network
2018 11th International Symposium on Computational Intelligence and Design (ISCID), 2018Due to the large number of welding process parameters and the model output parameters, the prediction result of weld bead geometry using neural network in wire and arc welding test is not ideal. Therefore, multi-population genetic algorithm is introduced to optimize the initial weights and threshold of neural network in this paper, and this can avoid ...
Qiankun Xue +6 more
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A prediction of welding process parameters by prediction of back-bead geometry
Journal of Materials Processing Technology, 2000Abstract In this paper, results with regard to the geometry prediction of the back-bead in gas metal arc welding where a gap exists were compared. Methods using in geometry prediction were employed multiple regression analysis and artificial neural network.
J.I. Lee, K.W. Um
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Modeling of weld bead geometry for rapid manufacturing by robotic GMAW
International Journal of Modern Physics B, 2015Weld-based rapid prototyping (RP) has shown great promises for fabricating 3D complex parts. During the layered deposition of forming metallic parts with robotic gas metal arc welding, the geometry of a single weld bead has an important influence on surface finish quality, layer thickness and dimensional accuracy of the deposited layer.
Tao Yang, Jun Xiong, Hui Chen, Yong Chen
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2019
In the process of multi-layer and multi-bead wire and arc additive manufacturing (WAAM), the geometry of each layer has an important influence on the dimensional accuracy and surface quality of the final forming parts. In this paper, machine learning model is used to predict the geometrical morphology of multi-layer and multi-channel WAAM forming parts.
Junhao Deng +4 more
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In the process of multi-layer and multi-bead wire and arc additive manufacturing (WAAM), the geometry of each layer has an important influence on the dimensional accuracy and surface quality of the final forming parts. In this paper, machine learning model is used to predict the geometrical morphology of multi-layer and multi-channel WAAM forming parts.
Junhao Deng +4 more
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