|Bibliography||Gröger, Christoph; Schlaudraff, Johannes; Niedermann, Florian; Mitschang, Bernhard: Warehousing Manufacturing Data. A Holistic Process Warehouse for Advanced Manufacturing Analytics. |
In: Cuzzocrea, Alfredo (ed.); Dayal, Umeshwar (ed.): Proceedings of the 14th International Conference on Data Warehousing and Knowledge Discovery - DaWaK 2012.
University of Stuttgart, Faculty of Computer Science, Electrical Engineering, and Information Technology.
Lecture Notes in Computer Science; 7448, pp. 142-155, english.
Berlin, Heidelberg: Springer, September 2012.
Article in Proceedings (Conference Paper).
|CR-Schema||H.2.7 (Database Administration)|
J.1 (Administration Data Processing)
|Keywords||Data Warehouse; Manufacturing; Process Optimization; Analytics; Business Intelligence; Data Integration|
Strong competition in the manufacturing industry makes efficient and effective manufacturing processes a critical success factor. However, existing warehousing and analytics approaches in manufacturing are coined by substantial shortcomings, significantly preventing comprehensive process improvement. Especially, they miss a holistic data base integrating operational and process data, e. g., from Manufacturing Execution and Enterprise Resource Planning systems. To address this challenge, we introduce the Manufacturing Warehouse, a concept for a holistic manufacturing-specific process warehouse as central part of the overall Advanced Manufacturing Analytics Platform. We define a manufacturing process meta model and deduce a universal warehouse model. In addition, we develop a procedure for its instantiation and the integration of concrete source data. Finally, we describe a first proof of concept based on a prototypical implementation.
|Department(s)||University of Stuttgart, Institute of Parallel and Distributed Systems, Applications of Parallel and Distributed Systems|
|Entry date||July 24, 2012|