The aim of the quality control in industrial application is to analyze and monitor the quality of industrial manufacturing activities. Signal processing systems and automatic visual inspection systems, which are automatic systems that perform visual inspection by means of machine vision, can play a fundamental role in quality assessment since they can guarantee a high and constant non invasive quality inspection. In the literature a comprehensive analysis of the quality control in industrial applications is not available but several ad-hoc solutions can be found. The solution of quality control problems requires being able to tackle problems of different scientific areas (signal acquisition, signal preprocessing, feature selection and extraction, data fusion and classification). The research efforts led to the development of methodologies that try to integrate all the above activities to design intelligent signal and visual inspection systems for the quality control using. Computational intelligence techniques have been recognized in the literature as a good tool which can be used by the designer to achieve these goals.

Computational intelligence in industrial quality control / C. Alippi, M. Roveri, V. Piuri, F. Scotti - In: IEEE International symposium on intelligent signal processing : University of Algarve, Portugal, 1-3 september 2005 : proceedings / [a cura di] M.G. Ruano, A.E. Ruano. - Piscataway : Institute of electrical and electronics engineers, 2005 Sep. - ISBN 078039030X. - pp. 4-9 (( convegno IEEE International Symposium on Intelligent Signal Processing tenutosi a Faro, Portugal nel 2005.

Computational intelligence in industrial quality control

V. Piuri
Penultimo
;
F. Scotti
2005

Abstract

The aim of the quality control in industrial application is to analyze and monitor the quality of industrial manufacturing activities. Signal processing systems and automatic visual inspection systems, which are automatic systems that perform visual inspection by means of machine vision, can play a fundamental role in quality assessment since they can guarantee a high and constant non invasive quality inspection. In the literature a comprehensive analysis of the quality control in industrial applications is not available but several ad-hoc solutions can be found. The solution of quality control problems requires being able to tackle problems of different scientific areas (signal acquisition, signal preprocessing, feature selection and extraction, data fusion and classification). The research efforts led to the development of methodologies that try to integrate all the above activities to design intelligent signal and visual inspection systems for the quality control using. Computational intelligence techniques have been recognized in the literature as a good tool which can be used by the designer to achieve these goals.
Computational intelligence; Fuzzy logic; Neural networks; Quality assessment; Quality control; Sofl computing
Settore INF/01 - Informatica
Settore ING-INF/05 - Sistemi di Elaborazione delle Informazioni
set-2005
Book Part (author)
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/5652
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