Multi-objective genetic algorithm for optimization of system safety and reliability based on IEC 61508 requirements: A practical approach

Abstract

This paper presents a practical approach for optimization by evolutionary computation of safety instrumented system design, based on safety and reliability measures, plus life cycle cost. The standard IEC 61508 establishes the necessity of this kind of systems to meet specific safety integrity requirements, expressed in terms of safety integrity levels (SIL). The SIL is determined in terms of average probability of failure on demand (PFDavg) for control systems that operate in demand mode. The optimization executed takes into account the level of modelling detail contemplated by the standard, including multiple failure modes, diagnostic coverage, and common cause failures. This study addresses the case of series-parallel systems. Optimization is approached by treating the problem as one of redundancy and reliability allocation, together with testing intervals specifications. Modelling is made through fault tree analysis with house events. The multi-objective genetic algorithm proposed by Fonseca and Fleming is used as the optimization technique.