Improving production process performance thanks to neuronal analysis
This addresses quality control and efficiency for manufacturing companies, but appears incremental as it applies existing neural network methods to a specific domain.
The paper tackles the problem of ensuring product quality in manufacturing by proposing an online quality approach using neural networks to determine optimal machine settings, illustrated with a case study from a high-quality lacquerer company.
Product quality level is become a key factor for companies' competitiveness. A lot of time and money are required to ensure and guaranty it. Besides, motivated by the need of traceability, collecting production data is now commonplace in most companies. Our paper aims to show that we can ensure the required quality thanks to an "on-line quality approch" and proposes a neural network based process to determine the optimal setting for production machines. We will illustrate this with the Acta-Mobilier case, which is a high quality lacquerer company.