Journal ArticleDOI
The use of the Taguchi method with grey relational analysis and a neural network to optimize a novel GMA welding process
TLDR
An integrated approach using the Taguchi method, grey relational analysis and a neural network to optimize the weld bead geometry in a novel gas metal arc (GMA) welding process is presented.Abstract:
The objective of this paper is to present an integrated approach using the Taguchi method (TM), grey relational analysis (GRA) and a neural network (NN) to optimize the weld bead geometry in a novel gas metal arc (GMA) welding process. The TM is first used to construct a database for the NN. The GRA is adopted to solve the problem of multiple performance characteristics in a GMA welding process using activating flux. The grey relational grade obtained from the GRA is used as the output of the back-propagation (BP) NN. Then, a NN with the Levenberg-Marquardt BP (LMBP) algorithm is used to provide the nonlinear relationship between welding parameters and grey relational grade of each weldment. The optimal parameters of the novel GMA welding process were determined by simulating parameters using a well-trained BPNN model. Experimental results illustrate the proposed approach.read more
Citations
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Journal ArticleDOI
Bead geometry prediction for robotic GMAW-based rapid manufacturing through a neural network and a second-order regression analysis
TL;DR: The results demonstrate that not only the proposed models can predict the bead width and height with reasonable accuracy, but also the neural network model has a better performance than the second-order regression model due to its great capacity of approximating any nonlinear processes.
Journal ArticleDOI
Optimization of machining parameters in turning of Al−SiC−Gr hybrid metal matrix composites using grey-fuzzy algorithm
TL;DR: In this paper, the authors tried to find the optimal level of machining parameters for multi-performance characteristics in turning of Al−SiC−Gr hybrid composites using grey-fuzzy algorithm.
Prediction of Welding Parameters for Pipeline Welding Using an Intelligent System
TL;DR: In this paper, an intelligent system to determine welding parameters for each pass and welding position in pipeline welding based on one database and FEM model, two BP neural network models and a C-NN model was developed and validated.
Journal ArticleDOI
A multi criteria decision making approach for process improvement in friction stir welding of aluminium alloy
TL;DR: In this article, an attempt to select the optimum process parameters for friction stir welding of aluminium 2024 alloy based on multiple criteria decision-making approach is made, where the response parameters measured are ultimate tensile strength, impact toughness and hardness of welded joint that determines quality of joint.
Journal ArticleDOI
Robot path planning optimization for welding complex joints
H. C. Fang,Soh-Khim Ong,Ayc Nee +2 more
TL;DR: In this article, an approach for optimal robot path planning of the centroid pass in welding a Y-joint is presented, where a solution with minimum joint movement is determined using a beam search algorithm as the optimal path for each welding pass segment.
References
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