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Modeling and Optimization of Integration Processes Under Severe Uncertainties

[+] Author Affiliations
Meir Tahan, Joseph Z. Ben-Asher

Technion-Israel Institute of Technology, Haifa, Israel

Paper No. ESDA2008-59032, pp. 469-485; 17 pages
doi:10.1115/ESDA2008-59032
From:
  • ASME 2008 9th Biennial Conference on Engineering Systems Design and Analysis
  • Volume 4: Fatigue and Fracture; Fluids Engineering; Heat Transfer; Mechatronics; Micro and Nano Technology; Optical Engineering; Robotics; Systems Engineering; Industrial Applications
  • Haifa, Israel, July 7–9, 2008
  • Conference Sponsors: International
  • ISBN: 978-0-7918-4838-8 | eISBN: 0-7918-3827-7
  • Copyright © 2008 by ASME

abstract

The integration process of engineering systems frequently involves high uncertainties, such as units’ availability time, integration increment duration, testing costs, etc. In this work the uncertainty effect is investigated by three methods: statistical analysis under the assumption that the mean and variance of the underlying distributions are known, a Monte Carlo based method when the uncertain values can be bounded from below and above by known quantities, and information gap theory when only nominal values and relative weights regarding the unknown variables are given. The optimization is performed by dynamic programming. The modeling methods and the associated optimization are applied to a small tactical missile, examining and comparing the various strategies.

Copyright © 2008 by ASME

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