A Prioritized Decision Making Method for Reliability Allocation: in Optimistic and Pessimistic View

Reliability allocation is a very important problem during early design and development phases of a system. There are several reliability allocation techniques which are used to achieve the target reliability. The feasibility of objectives (FOO) technique is one of them that is widely used to perform system reliability allocation. But this technique has two fundamental shortcomings. The first is the measurement scale and the second is that it does not consider the order weight of the reliability allocation factors. The prioritization of the factors is also an important topic in decision making. Practically, all factors in multi-criteria decision making (MCDM) are not in the same priority level. Hence, in decision making situation, it is usual for decision makers to consider different priority factors. So, considering the prioritization of the factors, a reliability allocation method is proposed here to overcome the shortcomings of the FOO technique. Also, a case study on reliability allocation in airborne radar system is considered here to verify the efficiency of the proposed approach. Finally, the results are calculated in different optimistic and pessimistic view point and compared with the FOO technique. This comparison exhibits the advantages and supremacy of the proposed approach.

A knowledge based hierarchical reliability allocation (HIRAL) approach for shipboard systems

Reliability has become a greater concern in shipboard systems due to increasing amount of technology level, system complexity, and multiple design demands. Enhancement of the shipboard system’s reliability ensures safe and continuous operation onboard a ship. To enhance the reliability of the shipboard system, it is essential to identify each individual component’s reliability. Within this scope, the onerous task of reliability allocation analysis enhances the reliability of shipboard systems through the optimization of component-based designs, construction, and operations. This study proposes a hybrid reliability allocation methodology based on a hierarchical structure with the integration of an analytic hierarchy process (AHP), data envelopment analysis (DEA), and feasibility of objectives (FOO) methods. The proposed methodology provides reliability allocation analyses for systems with any number of components. The study also examines the usefulness of the adaptation of AHP-DEA into reliability allocation analysis. To demonstrate the applicability of the proposed methodology, a case study on the steering gear system is presented.

Optimization of Complex System Reliability using Hybrid Grey Wolf Optimizer

Reliability allocation to increase the total reliability has become a successful way to increase the efficiency of the complex industrial system designs. A lot of research in the past have tackled this problem to a great extent. This is evident from the different techniques developed so far to achieve the target. Stochastic metaheuristics like simulated annealing, Tabu search (TS), Particle Swarm Optimization (PSO), Cuckoo Search Optimization (CS), Genetic Algorithm (GA), Grey wolf optimization technique (GWO) etc. have been used in recent years. This paper proposes a framework for implementing a hybrid PSO-GWO algorithm for solving some reliability allocation and optimization problems. A comparison of the results obtained is done with the results of other well-known methods like PSO, GWO, etc. The supremacy/competitiveness of the proposed framework is demonstrated from the numerical experiments. These results with regard to the time taken for the computation and quality of solution outperform the previously obtained results by the other well-known optimization methods.