Experimental Studies Regarding the Implementation Possibilities of a Quality Control System for Ceramic Products in Continuous Flux Production
Abstract
In the current paper the authors studied the possibilities and limitations of a system intended to evaluate the quality of ceramic products directly on the production line. The system is based on a data mining specific approach in analyzing the sound produced by ceramic products when hit in a non-destructive manner.
The research showed that good results in discriminating among different quality grades can be obtained for products having similar shape and size even when working with up to six different quality grades. Reducing the number of quality grades to be discriminated increases the method’s precision. In industry the number of necessary quality grades to be discriminated is usually no higher than three, thus the authors consider that the method is suited for industrial implementation.
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References
[2]. David Hand, Heikki Mannila, Padhraic Smyth - Principles of Data Mining, The MIT Press, Cambridge, Massachusetts, 2001.
[3]. Ian H. Witten, Eibe Frank - DATA MINING Practical Machine Learning Tools and Techniques, second edition, Morgan Kaufmann Publishers, San Francisco, CA, 2005.
[4]. Philippe Renevey - Speech Recognition In Noisy Conditions Using Missing Feature Approach, Thèse présentée au département d’electricité, Lausanne, EPFL, 2000.
[5]. Tobias Bengtsson - Speech recognition using multilayer perceptron artificial neural Network, Department of Computer Science, Lund University.
[6]. http://en.wikipedia.org/wiki/Ceramic_materials - online encyclopedia, Ceramic materials section.
[7]. http://en.wikipedia.org/wiki/Wav - online encyclopedia, .wav file format section.
[8]. http://en.wikipedia.org/wiki/Linear_pulse_code_modulation - online encyclopedia,bLPCM format section.
[9]. http://en.wikipedia.org/wiki/Fft - online encyclopedia, FFT algorithm section.
[10]. Enciclopedia de chimie, vol 2, Editura Stiintifica si Enciclopedica, Bucuresti, 1986.
