Collaborative R&D Project 2019

Do acquisition and analysis of process data in series production enable improvement of product quality and process stability?

Challenge and Motivation

• Many influencing factors and their interactions determine product quality and process stability.
• Nowadays, causes and effects can only rarely be identified in the case of production problems and rejects.
• Applying data analytics offers the possibility to identify correlations that were previously unknown.

Objective

• Identification of cause-effect relationships of process control and state variables as well as product quality in series production by applying model based data analytics and Machine Learning (ML)-algorithms.