An intelligent hybrid approach for industrial quality control combining neural networks, fuzzy logic and fractal theory

被引：0
|
作者：
Melin, P [1 ]
Castillo, O [1 ]
机构：
[1] Tijuana Inst Technol, Dept Comp Sci, Chula Vista, CA 91909 USA
来源：
APPLIED COMPUTATIONAL INTELLIGENCE | 2004年
关键词：
D O I：
10.1142/9789812702661_0093
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
We describe in this paper a new hybrid intelligent approach for industrial quality control combining neural networks, fuzzy logic and fractal theory. We also describe the application of the neuro-fuzzy-fractal approach to the problem of quality control in the manufacturing of sound speakers in a real plant. The quality control of the speakers was done before by manually checking the quality of sound achieved after production [4]. A human expert evaluates the quality of sound of the speakers to decide if production quality was achieved. Of course, this manual checking of the speakers is time consuming and occasionally was the cause of error in quality evaluation [8]. For this reason, it was necessary to consider automating the quality control of the sound speakers.
引用
收藏
页码：513 / 518
页数：6
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