## 5 Conclusions  
In this paper, we developed a novel ExJ-PSI model for the analysis of complex systems that integrates the FMECA method and an integrated preference section index (PSI) approach to reduce the limitations of the conventional FMECA method. It reduces the uncertainty and vagueness in the risk assessment process and also improves the effectiveness of the traditional FMECA. The accuracy of the developed method is enhanced by collecting data from a number of experts. A case study on a boiler system validates the practicability and effectiveness of the developed model. The conclusions from the comparative study of the ExJ-PSI model, normalized median method, and the conventional FMECA method are;  
* It is required to consider various additional risk criteria, such as operational and maintenance time, human safety, and operational loss, to improve the effectiveness of the analysis. * Normalizing the rankings given by a large group of experts minimizes its uncertainty due to varying work experience and skills. * The preference section index (PSI) method uses the concept of statistics instead of weight attribute allocations in another multi-criteria decision-making (MCDM) approach and thus is observed to be more effective while deciding the relative importance when a conflict situation occurs. * The effectiveness of the model is validated over the conventional FMECA for the case of complex systems such as boilers, and it is found very useful in prioritizing failure modes to minimize the overall losses effectively due to sudden breakdown. It is observed from this research that the feedwater pump is the most critical component of the boiler system, having several critical failure modes, such as impeller failure, shaft failure, and deterioration of the bearings, leading to a complete replacement with high cost and maintenance time needed. Furthermore, the feedwater pump motor is ranked second and justified because maintenance is longer when the bearing is worn out, and the armature is seized. However, according to the conventional FMECA, the feedwater pump and feedwater pump motor ranking were three and eight, respectively, i.e., less critical. This shows that the maintenance time and cost, production loss, and safety impact the component's criticality. Similarly, in conventional FMECA, the rank of the water level controller was thirteen, and according to the proposed model, it is twenty-five, which indicates it is significantly less critical. The failure of the water level controller may affect the water tubes; therefore, its rank in conventional FMECA was high. However, the effect of its failure on production loss and maintenance or replacement cost is significantly less, so it comes in less critical according to the proposed model. The criticality rankings of the components in the proposed FMECA model are, therefore, more precise than those of the traditional FMECA when we consider additional criteria such as maintenance cost, production loss, and safety. In the traditional FMECA method, when the values of SV, O, and D are the same, the RPN will be the same, and they are assumed to have the same priority numbers. However, in reality, the two failure modes would have different O and D values. Moreover, there are many failure modes to the components, some of which do not affect SV, O, and D but the safety, maintenance time/cost, and quality. Therefore, different experts must assess failure modes to deal with this issue. They act in different roles in the risk analysis process, as they come from different fields and have different knowledge and experience. The analysis reveals that the feed water pump, feed water pump motor, supply water temperature sensor, return water temperature sensor, header, and coal feed motor are identified as some of the most critical components of the boiler system.