Advances in Decision Sciences
Volume 2012 (2012), Article ID 798286, 19 pages
Research Article

Key Performance Indicators for the Impact of Cognitive Assembly Planning on Ramp-Up Process

1Institute of Information Management in Mechanical Engineering IMA, RWTH Aachen University, Dennewartstrasse 27, 52068 Aachen, Germany
2Institute for Management Cybernetics e.V.(IfU), Dennewartstrasse 27, 52068 Aachen, Germany

Received 2 March 2012; Accepted 29 May 2012

Academic Editor: George Chryssolouris

Copyright © 2012 Christian Buescher et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Within the ramp-up phase of highly automated assembly systems, the planning effort forms a large part of production costs. Due to shortening product lifecycles, changing customer demands, and therefore an increasing number of ramp-up processes, these costs even rise. So assembly systems should reduce these efforts and simultaneously be flexible for quick adaption to changes in products and their variants. A cognitive interaction system in the field of assembly planning systems is developed within the Cluster of Excellence “Integrative production technology for high-wage countries” at RWTH Aachen University which integrates several cognitive capabilities according to human cognition. This approach combines the advantages of automation with the flexibility of humans. In this paper the main principles of the system's core component—the cognitive control unit—are presented to underline its advantages with respect to traditional assembly systems. Based on this, the actual innovation of this paper is the development of key performance indicators. These refer to the ramp-up process as a main objective of such a system is to minimize the planning effort during ramp-up. The KPIs are also designed to show the impact on the main idea of the Cluster of Excellence in resolving the so-called Polylemma of Production.