Published Oct 26, 2010



PLUMX
Google Scholar
 
Search GoogleScholar
Downloads


Gabriel Mauricio Zambrano-Rey

Carlos Alberto Parra-Rodríguez

Martha Ruth Manrique-Torres

César Julio Bustacara-Medina

##plugins.themes.bootstrap3.article.details##

Abstract

In this paper, the development, implementation, construction and validation of a quality control station targeted to the inspection and verification of fabrication qualities of machined parts, based on artificial vision and coupled to a computer integrated manufacturing system is presented. The system analyses the parts based on a template configured previously with a pattern. The template is applied later to each one of the images taken from the batch to be inspected. By taking into account the importance of metrology and quality control in manufacturing processes the main objective of this work was to provide the Laboratory of Industrial Automation with a measurement tool that allows inspection tasks to be executed during a process plan in a Computer Integrated Manufacturing System.

Keywords

Digital image processing, metrology, quality control, flexible manufacturing systemsprocesamiento digital de imágenes, metrología, control de calidad, sistemas flexibles de manufactura

References
ALEXANDROV, A. Computer Vision 558 Corner Detection Overview and Comparison. [Documento en línea]. 2002. [Consulta: 16-10-2006].
BAE, S., KWEON, I. S. y YOO, Ch. D. COP: A New Corner Detector. Pattern Recognition Letters. 2002, núm. 23, p. 1349-1360.
CHETVERIKOV, D. y SZABÓ, Z. Detection of High Curvature Points in Planar Curves. Image and Pattern Analysis Group Computer and Automation Research Institute. [Documento en línea]. 1999. [Hungary]: [Consulta: 10-10-2006].
CHIN, Roland T. y HARLOW, Charles A. Automated visual inspection. IEEE transactions on pattern analysis and machine intelligence. 1982, vol. 4, núm. 6.
CHIN, R. T. y YEH, C. L. Quantitative evaluation of some edge-preserving noise-smoothing techniques. Computer Vision, Graphics, and Image Processing. 1983, vol. 23, p. 67-91.
GONZÁLEZ, R. C. y WOODS, R. E. Digital Image Processing. 2nd ed. New Jersey: Prentice Hall, 2002. ISBN 0201180758.
HIMAYAT, N. y KASSAM, S. A. Approximate performance analysis of edge preserving filters. IEEE Transactions on Signal Processing. 1993, vol. 41, núm. 9, p. 2764-77.
JAIN, Anil K. Fundamentals of Digital Image Processing. Prentice-Hall International, 1989. ISBN 970133361650.
KHALILI, K., RAZAVI, S. A. y KARIMZADGAN, D. High resolution measurements using a low resolution system. Measurement Science Review. 2005, vol. l5, núm. 1.
LONNESTAD, T. y GROTTUM P. Method to estimate areas and perimeters of blob-like objects: a comparison. Norway: Department of Informatics, University of Oslo.
LÓPEZ BELTRÁN, Royman, SOTTER SOLANO, Edgar y ZUREK VARELA, Eduardo. Aplicación del sistema Robot Vision Pro para operaciones automáticas de control de calidad. Ingeniería y Desarrollo. 2001, vol. 9, p. 88-97.
LUCAS. Manual de entrenamiento FESTO.Denkendorf: Festo, 2004.
LUCAS. Getting Started An Introduction to Programming and Controlling Flexible Workcells with LUCAS. EFR-IRF. Denkendorf: Festo, 2000.
MODAYUR, B., SHAPIRO, L. y HARALICK, R. Visual Inspection of Machined Metallic Parts. University of Washington, Department of Electrical Engineering. Proceedings of IEEE Conf. on Computer Vision and Pattern Recognition, Champaign, IL: University of Washington, June 1992, pp. 393-398.
PÉREZ, ROBERTO. Caracterización y representación de los requerimientos funcionales y las tolerancias en el diseño conceptual: aportaciones para su implementación en los sistemas CAD. Memorias de Tesis Doctoral. Barcelona: Universidad Politécnica de Cataluña, 2002.
PRIETO, F., REDARCE, T., LEPAGE, R. y BOULANGER, P. An Automated Inspection System. The International Journal of Advanced Manufacturing Technology. 2002, junio. s. a. Mecánica del Taller. 3ª ed. Madrid: Mostotes, 1993.
SANDOVAL, Zulma, PRIETO, Flavio y ORTEGA, Oscar. Caracterización y clasificación de café cereza por medio de visión artificial. Memorias del VIII Simposio de Tratamiento de Señales, Imágenes y Visión Artificial. Medellín, Colombia, Noviembre 5-7 de 2003.
TOMASI, C. y MANDUCHI, R. Bilateral Filtering for Gray and Color Images. Proceedings of the 1998 IEEE International Conference on Computer Vision. 1998, p. 839-846.
YANG, L., ALBREGTSEN, F., LONNESTAD, T. y GROTTUM, P. Method to estimate areas and perimeters of blob-like objects: a comparison. Department of Informatics. Norway: University of Oslo, 1994.
ZHANG, Z. A flexible new technique for camera calibration. Microsoft Research Corporation. December 2, 1998 [Consulta: 10-8- 2002].
How to Cite
Zambrano-Rey, G. M., Parra-Rodríguez, C. A., Manrique-Torres, M. R., & Bustacara-Medina, C. J. (2010). Quality control station via artificial vision for a computer integrated manufacturing center (CIM). Ingenieria Y Universidad, 11(1). Retrieved from https://revistas.javeriana.edu.co/index.php/iyu/article/view/923
Section
Articles

Most read articles by the same author(s)