Neuro-Fuzzy Modeling Applied to Coating Quality Control

P. Mariño, V. Pastoriza, M. Santamaría, and E. Martínez (Spain)


Fuzzy logic, neural networks, machine vision, qualitycontrol, manufacturing application


The authors have been involved in developing an auto mated 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 manu facturing 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 op erations. After that, the fuzzy modeling, results obtained and their discussion are presented. Finally, concluding remarks are stated.

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