2022: Testing innovative proactive AI based feedback system for manufacturing settings evaluation
In the course of the project “Testing innovative proactive feedback system for manufacturing settings evaluation”, the possibilities of predicting the compliance of products with quality requirements based on production parameters and, based on this, providing feedback to the operator already during production regarding the suitability of the selected production parameters, were investigated and tested. During the study various machine learning algorithms were tested to create a relational model to predict finished product parameters from production parameters. The production setting parameters of already produced products, measurement data stored during production and results obtained from quality control were used to train the feedback system. As a result of the project, it was possible to show that there is a correlation between the production parameters and the measurement data obtained from the quality control of the product, and it is possible to predict this with a relational model trained with machine learning methods. The obtained accuracy was lower than expected, but it can be influenced by increasing the accuracy of measuring devices and improving data processing.