Implantation of an on-line quality process monitoring

Because product quality level is today a key factor for companies' competitiveness and because it is really hard to control the manufacturing systems, there is a lot of scientific methods implemented on the shop-floor to improve quality at workstations. In our previous works, we have shown that the online quality control assisted by Neural Network seems to be a good alternative to the well-known industrial methods such as Taguchi Method. Nevertheless we have highlighted that a drift appears between the model and the process reality. In this paper, we propose a way to resynchronize the on-line control system behavior with it. This approach allows us to assure that the model stay robust and adaptable for the quality prediction. We will illustrate this with the Acta-Mobilier case, which is a high quality lacquerer company in the furniture industry.

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