Abstract

The use of neural networks began to be applied because the traditional control charts used for monitoring manufacturing process, in some cases, did not provide the possibility of correctly and quickly signalling the existing causes of variation. In today's manufacturing environment, neural networks present increasing usefulness for implementing the automation of statistical process control. This chapter targets issues on the use of neural networks for quality control of manufacturing processes, concerning the way of operation of each network model, the network's architecture and the results provided. Applications of neural networks for pattern recognition and for detection of mean and/or variance shifts in process are discussed. Comparisons between the performances of the neural approach and those of traditional control charts are also presented. Results prove that the neural network model is a useful alternative to the existing control schemes.

Autore Pugliese

• Pacella Massimo

Tutti gli autori

• M. Pacella , Q. Semeraro

Titolo volume/Rivista

Non Disponibile

Anno di pubblicazione

2014

ISSN

Non Disponibile

ISBN

Non Disponibile

Numero di citazioni Wos

Nessuna citazione

Ultimo Aggiornamento Citazioni

Non Disponibile

Numero di citazioni Scopus

Non Disponibile

0

Ultimo Aggiornamento Citazioni

28/04/2018

Settori ERC

Non Disponibile

Codici ASJC

Non Disponibile