@inproceedings{2e6b7538aca4492b81261ab4ceb49d44,
title = "Optimization of cutting parameters during cutting based on the FEA and neural networks",
abstract = "Based on the FEA (Finite Element Analysis) and neural networks, cutting parameters have been optimized under the given machining errors caused by the deformation of workpiece-fixture system. Initially, the finite element analysis approach is used to calculate the deformation of the workpiece-fixture system during machining process. The model to optimize the cutting parameters has been formulated, where the objective is maximum the productivity. High extent of non-linear relationship exists between the machining errors and the deformation of workpiece-fixture system, so neural network approach has been employed to simulate the relationship. Consequently, cutting parameters have been optimized and the production operation efficiency is maximized along with ensuring machining precision. Finally, a case study has been used to support and validate the proposed model.",
keywords = "Cutting parameters, FEA, Neural network, Optimization",
author = "Faping Zhang and Houfang Sun and Yuan Lu",
year = "2006",
doi = "10.1049/cp:20061041",
language = "English",
isbn = "0863416969",
series = "IET Conference Publications",
number = "524",
pages = "1704--1709",
booktitle = "International Technology and Innovation Conference 2006, ITIC 2006",
edition = "524",
note = "International Technology and Innovation Conference 2006, ITIC 2006 ; Conference date: 06-11-2006 Through 07-11-2006",
}