|Bibliography||Gröger, Christoph; Stach, Christoph; Mitschang, Bernhard; Westkämper, Engelbert: A mobile dashboard for analytics-based information provisioning on the shop floor. |
In: International Journal of Computer Integrated Manufacturing.
University of Stuttgart, Faculty of Computer Science, Electrical Engineering, and Information Technology.
pp. 1-20, english.
Taylor & Francis Inc., May 27, 2016.
Article in Journal.
|CR-Schema||H.4.0 (Information Systems Applications General)|
J.2 (Physical Sciences and Engineering)
|Keywords||dashboard; cockpit; process optimisation; data analytics; business intelligence; data mining|
Today's turbulent global environment requires agility and flexibility of manufacturing companies to stay competitive. Thus, employees have to monitor their performance continuously and react quickly to turbulences which demands real-time information provisioning across all hierarchy levels. However, existing manufacturing IT systems, for example, manufacturing execution systems (MES), do hardly address information needs of individual employees on the shop floor. Besides, they do not exploit advanced analytics to generate novel insights for process optimisation. To address these issues, the operational process dashboard for manufacturing (OPDM) is presented, a mobile data-mining-based dashboard for workers and supervisors on the shop floor. It enables proactive optimisation by providing analytical information anywhere and anytime in the factory. In this paper, first, user groups and conceptual dashboard services are defined. Then, IT design issues of a mobile shop floor application on top of the advanced manufacturing analytics platform are investigated in order to realise the OPDM. This comprises the evaluation of different types of mobile devices, the development of an appropriate context model and the investigation of security issues. Finally, an evaluation in an automotive industry case is presented using a prototype in order to demonstrate the benefits of the OPDM for data-driven process improvement and agility in manufacturing.
|Department(s)||University of Stuttgart, Institute of Parallel and Distributed Systems, Applications of Parallel and Distributed Systems|
|Entry date||June 6, 2016|