Model Based Optimization of Forging Process Chains under the Consideration of Penalty Functions

Matthias Dannenberg; Alexander Georgiadis; Bernd-Arno Behrens

doi:10.4028/www.scientific.net/AMR.1018.533

Paper Titles

Energy KPI’s, Challenges for Sustainable Manufacturing Strategies, Analysis of Existing Rules and Indicators in an Industrial Environment in Relation to the Establishment of Energy Benchmark
p.501

Lean Production Systems in the Context of Social Trends: Job Satisfaction the Key Factor to Success
p.509

Learning Factories for Sustainable Manufacturing - A Generic Design Approach
p.517

Mechanical Properties of Large Three-Dimensional Specimens Build through Direct Powder Deposition
p.525

Model Based Optimization of Forging Process Chains under the Consideration of Penalty Functions
p.533

Model-Based Development Process of Cybertronic Products and Production Systems
p.539

Reference Model for the Description of Digital Engineering Tools Based on Mechatronic Principles and Concepts
p.547

Scenario-Based Determination of Alternative Product Architecture Designs
p.555

Product-Quality Based Scheduling of Automated Food Processing
p.563

HomeAdvanced Materials ResearchAdvanced Materials Research Vol. 1018Model Based Optimization of Forging Process Chains...

Model Based Optimization of Forging Process Chains under the Consideration of Penalty Functions

Abstract:

For the production of forged components, it is necessary to coordinate and optimize the production stages along the different process chains. This includes the mainstream processes as well as the associated process chains and the respective processes of die manufacturing. Until now, these processes and process chains are commonly planned and optimized independently due to different and often contradictory target criteria. This paper deals with an extended approach to a holistic planning and optimization of forging process chains by means of the optimization technique Genetic Algorithm (GA) in order to reduce production costs and time.

You might also be interested in these eBooks

View Preview

Info:

Periodical:

Advanced Materials Research (Volume 1018)

Pages:

533-538

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.1018.533

Citation:

Cite this paper

Online since:

September 2014

Authors:

Matthias Dannenberg*, Alexander Georgiadis, Bernd-Arno Behrens

Keywords:

Computer Automated Process Planning (CAPP), Forging, Optimization

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

* - Corresponding Author

References

[1] A. Brandes, Positionierung technologischer Schnittstellen – Beitrag zur ganzheitlichen Auslegung fertigungstechnischer Prozessketten, PZH-Verlag, Garbsen, (2008).

Google Scholar

[2] B. Denkena, B. -A. Behrens, F. Charlin, M. Dannenberg, Integrative process chain optimization using a Genetic Algorithm, Production Engineering - Research and Development, 6 (2012) 29-37.

DOI: 10.1007/s11740-011-0347-5

Google Scholar

[3] E. Doege, Handbuch Umformtechnik, second edition, Springer, Berlin, (2010).

Google Scholar

[4] J. Mehnen, T. Michelitsch, T. Bartz-Beielstein, N. Henkenjohann, Systematic Analyses of Multi-objective Evolutionary Algorithms Applied to Real-World Problems Using Statistical Design of Experiments, 4th CIRP International Seminar on Intelligent Computation in Manufacturing Engineering, (2004).

Google Scholar

[5] J. H. Holland, Adaption in natural and artificial systems, Univ. of Michigan, Ann Arbor, (1975).

Google Scholar

[6] D. E. Goldberg, Genetic Algorithms in Search, Optimization and Machine Learning, Addison-Wesley, Reading, (1989).

Google Scholar

[7] R. L. Haupt, S. E. Haupt, Practical Genetic Algorithms, John Wiley & Sons, Hoboken, (2004).

Google Scholar

[8] J. Garen, SGMGA: Self-guided multi-objective genetic algorithm, Proceedings of the Fifth Metaheuristics International Conference, Kyoto, (2003).

Google Scholar

[9] V. Nissen, Einführung in evolutionäre Algorithmen, Vieweg & Sohn, Braunschweig, (1997).

Google Scholar

[10] Z. Michalewicz, Genetic Algorithms + data structures, third edition, Springer, Berlin, (1996).

Google Scholar

[11] K. Weicker, Evolutionäre Algorithmen, second edition, Teubner, Wiesbaden, (2007).

Google Scholar

[12] I. Gerdes, F. Klawonn, R. Kruse, Evolutionäre Algorithmen, Vieweg, Wiesbaden, (2004).

Google Scholar