A bio-inspired computational high-precision dental milling system

Author

Vera, Vicente ; García, Alvaro Enrique ; Suarez, Maria Jesus ; Hernando, Beatriz ; Corchado, Emilio ; Sanchez, Maria Araceli ; Gil, Ana ; Redondo, Raquel ; Sedano, Javier

Author_Institution

Dept. de Estomatologia I & II, UCM, Madrid, Spain

fYear

2010

fDate

15-17 Dec. 2010

Firstpage

423

Lastpage

429

Abstract

A novel bio-inspired computational high-precision dental milling system is proposed in this interdisciplinar research. The system applies several bio-inspired models, based on unsupervised learning, that analyse and identify the most relevant features of high-precision dental-milling data sets and their internal structures. Finally, a supervised neural architecture and certain identification techniques are applied, in order to model and to optimize the high-precision process. This is done by empirically testing the model using a real data set taken from a dynamic high-precision machining centre with five axes.

Keywords

bio-inspired materials; data analysis; dentistry; medical computing; milling; neural net architecture; optimisation; unsupervised learning; bio-inspired computational dental milling system; bio-inspired models; dental milling data analysis; high precision machining centre; identification techniques; supervised neural architecture; unsupervised learning; Analytical models; Design automation; Production; Solid modeling; Variable speed drives; Artificial Neural Networks; Control System; Exploratory Projection Pursuit; Identification Systems; Industrial and Medical Applications;

fLanguage

English

Publisher

ieee

Conference_Titel

Nature and Biologically Inspired Computing (NaBIC), 2010 Second World Congress on

Conference_Location

Fukuoka

Print_ISBN

978-1-4244-7377-9

Type

conf

DOI

10.1109/NABIC.2010.5716341

Filename

5716341