In the process of designing a product or a physical system, Reliability engineering is an important factor to be considered. Also, as an essential step in Reliability evaluation during the design phase, it is necessary to allocate Reliability to subsystems, in such a way that full system Reliability is satisfied. Performing this process, which is called Reliability allocation, creates a more reliable and competitive system, which, at the same time, is compatible with our limitations. The consequences of considering this phase in designing a product are improved design and manufacturing methods, and, as a result, it is possible to gain cheap and reliable products compatible with customer demand. Many parameters that exist in the process of Reliability allocation have been generated based on research investigations. These techniques have different attitudes towards performing an allocation process. By analyzing these approaches, the researchers discovered remarkable disorders. These disorders are consequences of weaknesses, some of which all techniques share. One important aspect not considered in these techniques, and considered to be a great weakness, is the importance of subsystems, regarding their place in system configuration and their contribution to full system Reliability. In this study, according to the importance and e effectiveness of Reliability importance measures, we have utilized them as an approach to suggest a new and effective technique. In this process, we use the technique of Reliability importance measures to propose a new way to overcome this weakness, and, in two examples, will show the effects of using these measures in the process of Reliability allocation. Based on a comparison between the new technique and the two most applicable techniques in literature; ARINC and MAXIMAL ENTROPY, using one hypothetical and one real example, we have shown the preferable results of the new technique.

This paper proposes a new mathematical model for multi-objective redundancy allocation problem (RAP) without component mixing in each subsystem when the redundancy strategy can be chosen for individual subsystems. Majority of the mathematical model for the multi-objective redundancy allocation problems (MORAP) assume that the redundancy strategy for each subsystem is predetermined and fixed. In general, active redundancy has received more attention in the past. However, in practice both active and cold-standby redundancies may be used within a particular system design and the choice of the redundancy strategy becomes an additional decision variable. The proposed model for MORAP simultaneously maximizes the Reliability and the net profit of the system. And finally, to clarify the proposed mathematical model a numerical example will be solved.

Reliability Redundancy allocation (RRA) is one of the most important problems facing the managers to improve the systems performance. In most RRA models, components’,Reliability used to be assumed as an exact value in (0, 1) interval, while various factors might affect components’,Reliability and change it over time. Therefore, Reliability values should be considered as uncertain parameters. In this paper, by developing a discrete-continuous inference system, an optimization-oriented decision support system is proposed considering the components’,Reliability as stochastic variables. Proposed DSS uses stochastic if-then rules to infer optimum or near optimum values for decision variables as well as objective function. Finally, by providing several numerical examples, the efficiency of the proposed DSS is evaluated.

This paper addresses the mixed integer Reliability redundancy allocation problems to determine simultaneous allocation of optimal Reliability and redundancy level of components based on three objective goals. System engineering principles suggest that the best design is the design that maximizes the system operational effectiveness and at the same time minimizes the total cost of ownership (TCO). To evaluate the performance of the TCO allocation numerical experiments were conducted and compared with previous for the series system, the series-parallel system, the complex (bridge) system and the over speed protection system. From the results of the numerical investigation, Reliability redundancy allocation based on minimum TCO will lead to a more reliable, economical design for the manufacturer as well as user compared with the initial cost optimum design and conventional Reliability optimum design.

The nature of electro-optical equipment in various industries and the pursuit of the goal of reducing costs demand high Reliability on the part of electro-optical systems. In this respect, Reliability improvement could be addressed through a Reliability allocation problem. Subsystem Reliability must be increased such that the requirements as well as defined requisite functions are ensured in accordance with the designers’ opinion. This study is an attempt to develop a multiobjective model by maximizing system Reliability and minimizing costs in order to investigate design phase costs as well as production phase costs. To investigate Reliability improvement feasibility in the design phase, effective feasibility factors in the system are used and the sigma level index is incorporated in the production phase as the Reliability improvement difficulty factor. Thus, subsystem Reliability improvement priorities are taken into consideration. Subsystem dependency degree is investigated through the design structure matrix and incorporated into the model’ s limitation together with modified criticality. The primary model is converted into a single-objective model through goal programming. This model is implemented on electro-optical systems, and the results are analyzed. In this method, Reliability allocation follows two steps. First, based on the allocation weights, a range is determined for the Reliability of subsystems. Afterward, improvement is initiated based upon the costs and priorities of subsystem Reliability improvement.