Abstract
A novel configuration method for systems design has been developed, that considers, at the same time, system reliability and cost. This method helps to maximize the reliability, minimize the cost and obtain the best possible configuration for the system to be designed. To accomplish this, a combination of Bayesian networks and heuristic search are used so to help the designer find the optimum configuration in the immense search space available. The method has as entry parameters: the minimal reliability requirement or maximum cost of the computer system to be designed, the function of the system as a reliability block diagram and a description of each component. From this input, the methodology transforms automatically the reliability block diagram to Bayesian network equivalent, from which the reliability of the system is obtained through probability propagation. Starting form the initial block diagram, a set of heuristic operators is used to generate new configurations. The “best” configurations are obtained using beam search with some heuristics to improve the search efficiency. There are 3 alternatives for defining the best configurations: (i) minimize cost with a reliability restriction, (ii) maximize reliability with a cost restriction, and (iii) make a compromise between reliability and cost (Pareto set). The methodology is applied to the design of a distributed control system with promising results.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
ANSI-IEEE. IEEE Guide for General Principles of Reliability Analysis of Nuclear Power Generating Station Safety Systems. USA: American National Standards Institute, 1985.
Kapur, K., Lamberson, L. Reliability in Engineering Design. USA: John Wiley & Sons Inc., 1977.
Musa, John, Iannino, Anthony, Okumoto, Kazuhira. Software Reliability: Measurement, Prediction and Application. Singapore: McGraw-Hill International Editions, 1987.
Neapolitan, Richard. Probabilistic Reasoning in Expert Systems: Theory and Algorithms. USA: John Wiley & Sons, Inc., 1990.
Pearl, Judea. Probabilistic Reasoning in Intelligent Systems: Network of Plausible Inference. USA: Morgan Kaufmann Publisher, Inc., 1988.
Ramírez V., Carlos. “Tolerancia a faltas: conceptos y aplicaciones del departamento de Instrumentación y Control”; Boletín IEE. Morelos, México. (Jul 1996): p. 182–188.
Torres, José, Sucar, L. Enrique. “Bayesian Networks for Reliability Analysis of Complex Systems” Iberamia 1998. Portugal: 1998.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2001 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Solano-Soto, J., Sucar, L.E. (2001). A Methodology for Reliable Systems Design. In: Monostori, L., Váncza, J., Ali, M. (eds) Engineering of Intelligent Systems. IEA/AIE 2001. Lecture Notes in Computer Science(), vol 2070. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45517-5_81
Download citation
DOI: https://doi.org/10.1007/3-540-45517-5_81
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-42219-8
Online ISBN: 978-3-540-45517-2
eBook Packages: Springer Book Archive