Design of reliable systems using static and dynamic fault trees

The design process of a reliable system is, by nature, iterative. Traditional approaches to the design of a reliable system follow the requirement determination, preliminary design, analysis, evaluation, and redesign stages until what is regarded as an acceptable design is achieved. The system requirements typically consist of requirements on reliability, cost, weight, power consumption, physical size, etc. Within available resources, there can exist numerous approaches that completely satisfy all the design requirements. However as modern systems are becoming more and more complex, it is difficult to enumerate all the acceptable designs to find the optimal design configuration. A design optimization tool is greatly needed. This paper embeds a genetic algorithm (GA) into a fault tree method to determine the heuristic optimal design configuration of a reliable system. For optimization, a fault tree which can represent the failure causes of potential designs is used. Two new gates (CHO & RED) are introduced in this research. GA are developed and integrated into a fault-tree solver to find the optimal design. Improvement techniques to accelerate GA convergence and to avoid the GA-premature problem are implemented. Multi-objective optimization is discussed and methods for it are developed. Several techniques to accelerate the optimization process are implemented which appreciably reduce the calculation time. Simulation results show that the integration of GA optimization capabilities with fault-tree reliability-analysis provides a robust, powerful system-design tool. The methodology is applied to an example of a cardiac-assist system