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Using Active Patterns for the Conceptual Design of Self-Optimizing Systems Exemplified by an Air Gap Adjustment System

[+] Author Affiliations
Jürgen Gausemeier, Wilhelm Dangelmaier, Detmar Zimmer, Alexander Schmidt, Ursula Frank, Benjamin Klöpper

University of Paderborn, Paderborn, Germany

Paper No. DETC2007-34642, pp. 935-944; 10 pages
  • ASME 2007 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference
  • Volume 2: 27th Computers and Information in Engineering Conference, Parts A and B
  • Las Vegas, Nevada, USA, September 4–7, 2007
  • Conference Sponsors: Design Engineering Division and Computers and Information in Engineering Division
  • ISBN: 0-7918-4803-5 | eISBN: 0-7918-3806-4
  • Copyright © 2007 by ASME


The conceivable evolution of information technology will enable mechatronic systems with inherent partial intelligence. We call this kind of systems self-optimizing. Self-optimizing systems are able to react autonomously and flexible to changing environmental conditions. They are capable of learning and optimizing their behavior at run-time. This paper presents the paradigm of self-optimization and shows how to develop self-optimizing systems. Focus is the conceptual design phase. The result of this phase is the principle solution. In this paper at first we explain how to describe the principle solution in a domain-spanning way. This is of high importance because a holistic description of the principle solution constitutes the basis for the communication and cooperation between the engineers from different domains who are engaged in developing a self-optimizing system. At second we introduce solution patterns for developing principle solutions. Solution patterns enable the reuse of design knowledge so that the development process will be more effective. This paper focuses on solution patterns including self-optimizing solutions. How the methods work we explain by the complex magnetic linear drive of a shuttle.

Copyright © 2007 by ASME



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