Research ArticleAn approach for reliability analysis of industrial systems using PSO and IFS technique

- Deal with imprecise, uncertain dependent information related to system performance.
- A new methodology, using PSO and IFS, has been proposed for reliability analysis.
- Nonlinear optimization model has been formulated for constructing the membership functions of the various reliability indices.
- Sensitivity as well as performance analysis has been performed for ranking the component of the system.
- Results are compared with existing results.

The main objective of this paper is to present a technique for computing the membership functions of the intuitionistic fuzzy set (IFS) by utilizing imprecise, uncertain and vague data. In literature so far, membership functions of IFS are computed via using fuzzy arithmetic operations within collected data and hence contain a wide range of uncertainties. Thus it is necessary for optimizing these spread by formulating a nonlinear optimization problem through ordinary arithmetic operations instead of fuzzy operations. Particle swarm optimization (PSO) has been used for constructing their membership functions. Sensitivity as well as performance analysis has also been conducted for finding the critical component of the system. Finally the computed results are compared with existing results. The suggested framework has been illustrated with the help of a case.