On Practical Automated Engineering Design

  • Lars NolleEmail author
  • Ralph Krause
  • Richard J. Cant
Part of the Simulation Foundations, Methods and Applications book series (SFMA)


In engineering, it is usually necessary to design systems as cheap as possible whilst ensuring that certain constraints are satisfied. Computational optimization methods can help to find optimal designs automatically. However, it is demonstrated in this work that an optimal design is often not robust against variations caused by the manufacturing process, which would result in unsatisfactory product quality. In order to avoid this, a meta-method is used in here, which can guide arbitrary optimization algorithms towards more robust solutions. This was demonstrated on a standard benchmark problem, the pressure vessel design problem, for which a robust design was found using the proposed method together with self-adaptive stepsize search, an optimization algorithm with only one control parameter to tune. The drop-out rate of a simulated manufacturing process was reduced by 30 % whilst maintaining near-minimal production costs, demonstrating the potential of the proposed method.


Automated engineering design Robust solution Optimization Parameter tuning Self-adaptive stepsize search Pressure vessel problem 


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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Department of Engineering Science, WE Applied Computer ScienceJade University of Applied ScienceWilhelmshavenGermany
  2. 2.Siemens AGEnergy ManagementErlangenGermany
  3. 3.School of Science and TechnologyNottingham Trent UniversityNottinghamUK

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