Enabling Data Analytics in Large Scale Manufacturing
December 28, 2021
Due to ever-changing market conditions and regulations along with increasing competition, companies of the manufacturing industry are facing challenges to satisfy the high customer demands as well as coping with the increasing complexity of the manufacturing processes [1–3]. In order to face these challenges and to produce modern components with differentiating potential, high manufacturing quality and efficiency are required [4]. The current industrial practice to ensure premium product quality as well as safety of components, machines and products despite novel manufacturing processes is to conduct a large number of quality checks during manufacturing. These quality checks bind large amounts of plant investment and reduce manufacturing efficiency. Increasing knowledge about the manufacturing processes and their interdependencies will allow reduction regarding the number of quality checks by prediction of manufacturing quality utilizing big data. Therefore, knowledge generation for the modern manufacturing technologies concerning manufacturing stability, efficiency and product quality needs to be supported and sped up in order to stay competitive. Currently, finding potential optimization regarding production efficiency and quality requires documented data, a lot of experience and manual diagnostics. An emerging trend to uncover hidden relations is data analytics [5]. Collecting data, using Internet-of-Things approaches [6] and applying machine-learning or data mining approaches [5, 7, 8] by following me
