Prediction of Resistance Spot Weld Quality of 780 MPa Grade Steel Using Adaptive Resonance Theory Artificial Neural Networks
نویسندگان
چکیده
منابع مشابه
Prediction of Weld Strength in Resistance Spot Welded Samples by Adaptive Neuro-Fuzzy Inference System (ANFIS)
Resistance Spot Welding (RSW) is one of the effective manufacturing processes used widely for joining sheet metals. Prediction of weld strength of welded samples has great importance in manufacturing and different methods are used by researchers to find the fracture force. In this article, the Adaptive Neuro-Fuzzy Inference System (ANFIS) is utilized for prediction of joint strength in welded s...
متن کاملPrediction of Weld Strength in Resistance Spot Welded Samples by Adaptive Neuro-Fuzzy Inference System (ANFIS)
Resistance Spot Welding (RSW) is one of the effective manufacturing processes used widely for joining sheet metals. Prediction of weld strength of welded samples has great importance in manufacturing and different methods are used by researchers to find the fracture force. In this article, the Adaptive Neuro-Fuzzy Inference System (ANFIS) is utilized for prediction of joint strength in welded s...
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I. Abstract: The prediction of the optimal weld bead width is an important aspect in shielded metal arc welding (SMAW) process as it is related to the strength of the weld. This paper focuses on investigation of the development of the simple and accurate model for prediction of weld bead width of butt joint of SMAW process. Artificial neural networks technique was used to train a program in C++...
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ژورنال
عنوان ژورنال: Metals
سال: 2018
ISSN: 2075-4701
DOI: 10.3390/met8060453