Selecting an artificial neural network for efficient modeling and accurate simulation of the milling process

International Journal of Machine Tools and Manufacture

Volumn 42, Issue 6, 2002, Pages 663-674

  Briceno, Jorge F ^a   El Mounayri, Hazim ^a   Mukhopadhyay, Snehasis ^b  

^a INDIANA UNIVERSITY   (United States)

^b IN 46202 USA   (United States)

Author keywords

Artificial neural networks; Back propagation; End milling; Radial basis

Indexed keywords

BACKPROPAGATION; COMPUTER SIMULATION; LEARNING SYSTEMS; METAL CUTTING; RADIAL BASIS FUNCTION NETWORKS;

END MILLING;

MILLING (MACHINING);

EID: 0036568755     PISSN: 08906955     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0890-6955(02)00008-1     Document Type: Article

References (13)

1. A mechanistic citting force model for ball-end milling
2. On-line monitoring of flank wear in turning with multi-layered feed-forward neural network
3. Neural network based adaptive control and optimisation in the milling process
4. Combining a radial basis neural network with time series analysis techniques to predict manufacturing process parameters
5. Using neural networks to predict bending angle of sheet metal formed by laser
6. Design and implementation of tool wear monitoring with radial basis function neural networks
7. Neural net approximation
8. Computational intelligence PC tools