End milling: A neural approach for defining cutting conditions

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The purpose of this paper is to present a new adaptive solution based on a feed forward neural network (FNN) in order to improve the task of selecting cutting conditions for milling operations. From a set of inputs parameters, such as work material, its mechanical properties, and the type of cutting tool, the system suggests feed rate and cutting speed values. The four main issues related to the neural network-based techniques, namely, the selection of a proper topology of the neural network, the input representation, the training method and the output format are discussed. The proposed network was trained using a set of inputs parameters provided by cutting operations manuals and tool manufacturers catalogues. Some tests and results show that adaptative solution proposed yields performance improvements. Finally, future work and potential applications are outlined.

Original languageEnglish
Title of host publicationArtificial Neural Networks and Intelligent Information Processing - Proc. 4th Int. Workshop on Artificial Neural Networks and Intelligent Information Processing, ANNIIP 2008; ICINCO 2008
Pages41-50
Number of pages10
StatePublished - 1 Dec 2008
Event4th International Workshop on Artificial Neural Networks and Intelligent Information Processing, ANNIIP 2008; In Conjunction with ICINCO 2008 - Madeira, Portugal
Duration: 11 May 200815 May 2008

Publication series

NameArtificial Neural Networks and Intelligent Information Processing - Proc. 4th Int. Workshop on Artificial Neural Networks and Intelligent Information Processing, ANNIIP 2008; ICINCO 2008

Conference

Conference4th International Workshop on Artificial Neural Networks and Intelligent Information Processing, ANNIIP 2008; In Conjunction with ICINCO 2008
CountryPortugal
CityMadeira
Period11/05/0815/05/08

Fingerprint Dive into the research topics of 'End milling: A neural approach for defining cutting conditions'. Together they form a unique fingerprint.

Cite this