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 atmosphere of the Red Planet or Mars contains 95% of carbon dioxide, 3% of nitrogen, 1.6% of argon and only a small amount of oxygen, and in terms of concentration is about one percent of the planet's atmosphere, which makes it virtually impossible for humans to live and survive on Mars. Therefore, it is necessary to find a solution that can provide the necessary oxygen for the survival of living organisms, especially humans, in the Martian atmosphere. Photosynthesis is the most important biochemical reaction on which almost all life depends. This complex process occurs in higher plants, algae and some bacteria such as cyanobacteria. Due to the very low percentage of oxygen in the Martian atmosphere, it seems that the use of photosynthetic species that are anaerobic and tolerant of adverse ecological conditions such as cyanobacteria can provide the oxygen needed by the Red Planet.

Electric distribution systems are wide separate parts of power systems. These networks are interface between load and transmission, generation systems with respect to radial configuration of distribution feeders. The main methods for improvement in Reliability of distribution systems are installation of switching devices such as sectionalize rand tie point. In this paper, an attempt has been made to develop a new and efficient algorithm for sectionalizer and tie point allocation simultaneously. A genetic algorithm based approach for determining optimal location and number of sectionalizers and tie points in distribution networks is presented. Costs of switches, lines and outage cost are considered in cost function. Test results verify the feasibility of applying the proposed method to manipulate the combinatorial switching device allocation in distribution networks.

One of the novel approaches in supply chain management is Vendor-managed inventory (VMI). The aim of this policy is to establish a long-term relationship between retailers and vendors. The prerequisite for the long-term relationship of vendors with retailers is to select retailers who can meet the most criteria from the vendors' perspective and have a considerable level of Reliability. In this paper, a two-tier supply chain with multiple retailers and multiple vendors has been developed using a combination of multi-criteria decision-making methods and multi-objective programming under the VMI policy. The developed model is such that, in order to establish long-term relationships and reduce supply chain costs, each retailer can only participate with one vendor. In general, the aim of the present study is to minimize costs, increase the Reliability of retailers, and select retailers who have relative prominence compared to other retailers. To this end, a            hierarchical analysis process (AHP) has been performed for each vendor, and the weights of retailers relative to the suppliers have been calculated. Then, the obtained weights were input into the three-objective model designed. The proposed model, considering a combination of qualitative and quantitative criteria in selecting retailers under VMI, can find a combination of the best      retailers by balancing between the criteria. In order to maintain the long-term relationship of the vendor with the retailers, it is better for the vendor to consider important criteria that are  necessary in selecting retailers.

Background: In spite of many advantages in Lenke classification of adolescent idiopathic scoliosis, the latest study of Richards et al showed that the King classification is better than had been reported recently and the Lenke classification system of adolescent idiopathic scoliosis is less reliable than previously reported.Methods: In this study, we performed a multi-surgeon comparison of these two classification systems. After teaching and discussing all available data of these classification systems with four spine surgeons, a pilot classification was performed. Then, they independently evaluated preoperative radiographs (standing posteroanterior, lateral, and two supine side-bending views) of 99 patients with adolescent idiopathic scoliosis. The results were determined by calculating the average percentage of intraobserver and interobserver agreement. Reliability was quantified using kappa statistics.Findings: The King classification demonstrated good intraobserver and interobserver Reliability, with an intraobserver agreement of 85.8% (kappa coefficient, 0.80). Interobserver percentage of agreement averaged 80.8% (kappa coefficient, 0.74). The complete Lenke classification, combining curve type, lumbar modifier, and sagittal thoracic modifier, demonstrated good Reliability for both intraobserver and interobserver measurements. The intraobserver percentage of agreement averaged 85.8% (kappa coefficient, 0.82). The interobserver percentage of agreement averaged 80.8% (kappa coefficient, 0.77).Conclusion: In this study, with each investigator performing the radiographic measurements, the King and Lenke classifications were almost similar (the Lenke classification had slightly better results). Such better results might be due to more training of this complex classification system. So, because of greater coverage of idiopathic scoliosis curve and usefulness of Lenke classification system, we prefer using this classification system in our center.

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.