Conception of a new quality control method based on neural networks
The prediction of failures in a factory is now an important area of industry that helps to reduce time and cost of non-quality from the data generated from the sensors installed on production lines, this data is used to detect anomalies and predict defects before they occur. The purpose of this article is to model an intelligent production line capable of predicting various types of non-conforming products. For that, we will utilize the neural network methodology within the specific context of a production line specialized in juice manufacturing. Firstly, we introduc