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Automated Fault Tree Analysis for Engineering Design Optimization

[+] Author Affiliations
Tiefu Shao, Zongfang Lin, Sundar Krishnamurty, Ian R. Grosse, Leon J. Osterweil

University of Massachusetts - Amherst, Amherst, MA

Paper No. DETC2007-35496, pp. 589-598; 10 pages
doi:10.1115/DETC2007-35496
From:
  • ASME 2007 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference
  • Volume 5: 6th International Conference on Multibody Systems, Nonlinear Dynamics, and Control, Parts A, B, and C
  • Las Vegas, Nevada, USA, September 4–7, 2007
  • Conference Sponsors: Design Engineering Division and Computers and Information in Engineering Division
  • ISBN: 0-7918-4806-X | eISBN: 0-7918-3806-4
  • Copyright © 2007 by ASME

abstract

This paper presents an automated fault tree analysis for engineering design optimization process. Specifically, a novel approach is presented in which Little-JIL, a process programming language, is applied to create a process model of engineering optimization. The process model uses a graphical language in the form of easy-to-understand block diagrams for defining processes that coordinate the activities of autonomous agents and their use of resources during the performance of a task. The use of Little-JIL facilitates agent coordination in the design optimization process and helps to model the order of and the communications between units of sub-processes. The resulting process model is easy to debug and is rigorous for simulation and formal reasoning in engineering design optimization. Furthermore, it enables the development of a clear and precise design optimization process model at different levels of granularity as perhaps preferred by the user. Moreover, since the process model allows for generation of fault trees automatically, it can be expected to be less errorprone than manually generated ones. A case study is shown to demonstrate the effectiveness and efficiency of the automated fault tree approach to design optimization and its usefulness in engineering decision making and in improving reliability of engineering design process.

Copyright © 2007 by ASME

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