The progressing digitalization in manufacturing companies results in a continuously increasing available database. These data are a key resource for maintaining competitiveness on a global market. Nevertheless, most manufacturing companies struggle in creating benefits from these data. In an empirical study, conducted in 2017 by WZL of RWTH Aachen University and ITEM of University St. Gallen, a low level of efficiency and maturity in applying Manufacturing Data Analytics has been identified even though the potentials especially for quality management are well known. The study shows a lack of specific use cases for the application of Data Analytics in manufacturing companies as one of the most important obstacles. Therefore, this paper presents the approach of a Scenario-based Manufacturing Data Analytics. The developed approach is applied on the order processing in single and small batch production companies. Nine different Data Analytics application scenarios were derived based on the specific challenges and the data availability. With the example of order tracing, one specific scenario is described in detail by using the established CRISP-DM framework. Additionally, this paper describes a Data Analytics application scenario to improve Order Tracing by implementing a new concept for indoor-localization based on BLE-beacons.
Groggert, S., Elser, H., Ngo, Q. H., & Schmitt, R. H. (2018). Scenario-based Manufacturing Data Analytics with the Example of Order Tracing through BLE-Beacons. In Procedia Manufacturing (Vol. 24, pp. 243–249). Elsevier B.V. https://doi.org/10.1016/j.promfg.2018.06.032