Key Performance Indicators for the Impact of Cognitive Assembly Planning on Ramp-Up Process
Author(s) -
Christian Buescher,
Eckart Hauck,
Daniel Schilberg,
Sabina Jeschke
Publication year - 2012
Publication title -
advances in decision sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.178
H-Index - 13
eISSN - 2090-3367
pISSN - 2090-3359
DOI - 10.1155/2012/798286
Subject(s) - process management , flexibility (engineering) , computer science , performance indicator , process (computing) , key (lock) , excellence , production (economics) , automation , cognition , product (mathematics) , component (thermodynamics) , risk analysis (engineering) , operations management , business , engineering , marketing , economics , mechanical engineering , physics , neuroscience , biology , political science , law , macroeconomics , operating system , management , geometry , computer security , mathematics , thermodynamics
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.
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