Abstract—Laser cutting being a complex cutting process needs a reliable model for prediction of the process performance. This research work presents a modeling study of laser cutting process. A hybrid approach of Artificial Neural Network (ANN) and Fuzzy Logic (FL), Adaptive Neuro Fuzzy Inference System (ANFIS) has been used for developing the Kerf width and Material removal rate (MRR) models. The developed ANFIS based models of Kerf width and Material removal rate have also been compared with Response Surface Methodology (RSM) based models and it has been found that the values of Kerf width and Material removal rate predicted by the ANFIS based models are more closer to the experimental values.
Index Terms—ANFIS model, Kerf width, Material removal rate, RSM model.
Arun Kumar Pandey, Avanish Kumar Dubey, Mechanical Engineering Department, Motilal Nehru National Institute of Technology Allahabad, India. arunp@mnnit.ac.in, avanish@mnnit.ac.in
Cite: Arun Kumar Pandey and Avanish Kumar Dubey, "Intelligent Modeling of Laser Cutting of Thin Sheet," International Journal of Modeling and Optimization vol. 1, no. 2, pp. 107-112, 2011.
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