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Self-optimizing Production Technologies

  • Fritz Klocke
  • Dirk Abel
  • Thomas Gries
  • Christian Hopmann
  • Peter Loosen
  • Reinhard Poprawe
  • Uwe Reisgen
  • Robert Schmitt
  • Wolfgang Schulz
  • Peter Abels
  • Oliver Adams
  • Thomas Auerbach
  • Thomas Bobek
  • Guido Buchholz
  • Benjamin Döbbeler
  • Daniel Frank
  • Julian Heinisch
  • Torsten Hermanns
  • Yves-Simon Gloy
  • Gunnar Keitzel
  • Maximilian Kemper
  • Diana Suarez Martel
  • Viktor Reimer
  • Matthias Reiter
  • Marco Saggiomo
  • Max Schwenzer
  • Sebastian Stemmler
  • Stoyan Stoyanov
  • Ulrich Thombansen
  • Drazen Veselovac
  • Konrad Willms
Chapter

Abstract

Customer demands have become more individual and complex, requiring a highly flexible production. In high-wage countries, efficient and robust manufacturing processes are vital to ensure global competitiveness. One approach to solve the conflict between individualized products and high automation is Model-based Self-optimization (MBSO). It uses surrogate models to combine process measures and expert knowledge, enabling the technical system to determine its current operating point and thus optimize it accordingly. The objective is an autonomous and reliable process at its productivity limit. The MBSO concept is implemented in eight demonstrators of different production technologies such as metal cutting, plastics processing, textile processing and inspection. They all have a different focus according to their specific production process, but share in common the use of models for optimization. Different approaches to generate suitable models are developed. With respect to implementation of MBSO, the challenge is the broad range of technologies, materials, scales and optimization variables. The results encourage further examination regarding industry applications.

Keywords

Feed Rate Injection Molding Laser Cutting Inspection System Cavity Pressure 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Fritz Klocke
    • 1
  • Dirk Abel
    • 2
  • Thomas Gries
    • 3
  • Christian Hopmann
    • 4
  • Peter Loosen
    • 5
  • Reinhard Poprawe
    • 6
  • Uwe Reisgen
    • 7
  • Robert Schmitt
    • 1
  • Wolfgang Schulz
    • 6
  • Peter Abels
    • 6
  • Oliver Adams
    • 1
  • Thomas Auerbach
    • 1
  • Thomas Bobek
    • 8
  • Guido Buchholz
    • 7
  • Benjamin Döbbeler
    • 1
  • Daniel Frank
    • 1
  • Julian Heinisch
    • 4
  • Torsten Hermanns
    • 6
  • Yves-Simon Gloy
    • 3
  • Gunnar Keitzel
    • 1
  • Maximilian Kemper
    • 3
  • Diana Suarez Martel
    • 8
  • Viktor Reimer
    • 3
  • Matthias Reiter
    • 2
  • Marco Saggiomo
    • 3
  • Max Schwenzer
    • 1
  • Sebastian Stemmler
    • 2
  • Stoyan Stoyanov
    • 6
  • Ulrich Thombansen
    • 6
  • Drazen Veselovac
    • 1
  • Konrad Willms
    • 7
  1. 1.Laboratory for Machine Tools and Production Engineering (WZL)RWTH Aachen UniversityAachenGermany
  2. 2.Institute of Automatic Control (IRT)RWTH Aachen UniversityAachenGermany
  3. 3.Institute of Textile Technology (ITA)RWTH Aachen UniversityAachenGermany
  4. 4.Institute of Plastics Processing (IKV)RWTH Aachen UniversityAachenGermany
  5. 5.Chair for Technology of Optical Systems (TOS)RWTH Aachen UniversityAachenGermany
  6. 6.Fraunhofer Institute for Laser Technology (ILT)AachenGermany
  7. 7.Welding and Joining Institute (ISF)RWTH Aachen UniversityAachenGermany
  8. 8.Fraunhofer Institute for Production Technology (IPT)AachenGermany

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