DocumentCode :
1605036
Title :
Fuzzy inference system to inspect coating in canmaking industry
Author :
Mariño, Perfecto ; Pastoriza, Vicente ; Santamaria, Mikel ; Martínez, Emilio
Author_Institution :
Dept. of Electron. Technol., Vigo Univ., Spain
Volume :
3
fYear :
2004
Firstpage :
1144
Abstract :
The authors have been involved in developing an automated inspection system, based on machine vision, to improve the coating quality control in can ends of metal containers for fish food. In this work we present a fuzzy model building to make the acceptance/rejection decision for each can end from the information obtained by the vision system. In addition it is interesting to note that such model could be interpreted and supplemented by process operators. In order to achieve such aims, we use a fuzzy model due to its ability to favour the interpretability for many applications. Firstly, the easy open can end manufacturing process, and the current, conventional method for quality control of easy open can end repair coating, are described. Then, we show the machine vision system operations. After that, the fuzzy modeling, results obtained and their discussion are presented. Finally, concluding remarks are stated.
Keywords :
canning; computer vision; fuzzy neural nets; fuzzy systems; inference mechanisms; metal product industries; production engineering computing; quality control; automated inspection system; canmaking industry; coating quality control; fish food; fuzzy inference system; fuzzy modeling; machine vision; manufacturing process; metal containers; repair coating; Coatings; Coils; Electrical equipment industry; Food technology; Fuzzy systems; Inspection; Machine vision; Manufacturing processes; Quality control; Shape;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Industrial Technology, 2004. IEEE ICIT '04. 2004 IEEE International Conference on
Print_ISBN :
0-7803-8662-0
Type :
conf
DOI :
10.1109/ICIT.2004.1490721
Filename :
1490721
Link To Document :
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