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Roy, Shibendu Shekhar
- Modeling of Tool Life and Cutting Force in Turning Using a Combined Neural Networks and Fuzzy Inference System
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1 Central Mechanical Engineering Research Institute, M.G. Avenue, Durgapur-713209, West Bengal, IN
1 Central Mechanical Engineering Research Institute, M.G. Avenue, Durgapur-713209, West Bengal, IN
Source
Manufacturing Technology Today, Vol 4, No 8 (2005), Pagination: 10-14Abstract
This paper illustrates the application of combined neural networks and fuzzy inference system for modeling tool life and cutting force in turning operation for set of given cutting parameters, namely cutting speed, feed and depth of cut. The proposed methodology uses a hybrid-learning algorithm i.e., combination of the backpropagation gradient descent method and least squares method, to identify premise and consequent parameters of the first-order Sugeno-fuzzy inference system. The results obtained from proposed method are compared with the experimental results. The comparison indicates that the proposed method can produce efficient knowledge base of fuzzy inference system for modeling the tool life and cutting force in turning operation.- Prediction of Surface Finish in End Milling Operation Using Adaptive Neuro-Fuzzy System
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Authors
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1 Central Mechanical Engineering Research Institute, M.G. Avenue, Durgapur-713209, IN
1 Central Mechanical Engineering Research Institute, M.G. Avenue, Durgapur-713209, IN
Source
Manufacturing Technology Today, Vol 3, No 11 (2004), Pagination: 3-7Abstract
Surface finish is an important parameter in manufacturing engineering. It is a characteristic that could influence the performance of machined parts and the production costs. This paper proposes a method using adaptive neuro-fuzzy inference system to establish the relation between machining parameters and surface finish in end milling and consequently, can effectively predict surface finish of workpiece using input cutting parameters namely, spindle speed, feed rate and depth of cut. The results obtained with the adaptive neuro-fuzzy inference system are compared with the experimental results. The comparison indicates that the proposed method can produce optimized knowledge base of fuzzy system for predicting surface finish in end milling operation.- A Fuzzy Expert System for Solving Inverse Dynamics of Robotic Manipulator
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Authors
Affiliations
1 Central Mechanical Engineering Research Institute, Durgapur-713209, W.B., IN
1 Central Mechanical Engineering Research Institute, Durgapur-713209, W.B., IN