###### Abstract
proposed a belief reliability modeling and analysis method for harmonic gear transmission efficiency and discovered the main factors affecting transmission efficiency and reliability by analyzing and quantifying multiple sources of uncertainty. [PERSON] [16] et al. proposed a function-oriented design and optimization method of belief reliability based on performance margin. They proved that the uncertainty analysis results of the belief reliability theory could guide product design by applying it in the design phase of torsion spring electrical connectors. The above research results show that the belief reliability theory has good applicability for evaluating different products. It can give valid evaluation results for small sample test data, and considering uncertainty can give guidance suggestions for product improvement. AEMRs are widely used in vital positions in aerospace and weaponry systems due to their high reliability, long life, and solid on-off performance. They are mainly used to undertake the system power supply, distribution, and timing logic control. Therefore, once one fails, it will undoubtedly produce a devastating blow to the whole system [17]. At the same time, because AEMRs are the least reliable of the many military electronics components, it is reasonable to assume that the reliability of AEMRs determines the reliability of the aerospace and weapon system, based on the Bucket theory. However, similar to missiles, torpedoes and other long-storage weapons and equipment, from production to use, often go through a storage period of up to ten years [18]. During the storage process, even in a relatively stable environment, external stresses inevitably affect the AEMRs, resulting in internal degradation and eventual failure [19]. Thus, the storage reliability of aerospace relays is of great importance for effective weapon systems and even national security. Therefore, it is necessary to study AEMRs' storage reliability assessment technology. With the development of manufacturing process technology, electronic devices are becoming more and more reliable. AEMRs are no exception, and even if storage accelerated life testing is used for them, it is difficult to achieve effective evaluation in the short term. Especially for products in the early stages of development, the time, labor, and material costs associated with multiple rounds of design modifications and large batch reliability testing of the related products are incalculable. Therefore, for the design phase of AEMR, it is not friendly to use traditional methods for reliability assessment. [PERSON] [20] and [PERSON] [21]modeled the performance degradation of sensitive parameters, such as suction time and contact resistance, starting from the degradation mechanism, which laid the foundation for the storage reliability assessment work. However, the \"one-sample-one-assessment\" model is unsuitable for generalization, and the calculation is very tedious when facing the reliability assessment of batch AEMRs. Therefore, a stochastic process-based approach [22,23] to storage reliability assessment was further proposed. Assuming that the model parameters obey a normal-gamma distribution to reflect the individual differences between batches, a storage reliability assessment model for batch AEMRs is established. However, the storage reliability of batch AEMRs is not only affected by individual heterogeneity but also by uncertainty, due to unclear knowledge of the degradation process and the inherent uncertainty of the product itself. Therefore, measuring the multiple sources of uncertainty, in the development stage of AEMRs, will play an important role in the modeling. As seen above, with the development of modern industry, the problems faced in the field of reliability engineering tend to become more complex, with many influencing factors of uncertainty. The proposed belief reliability theory provides new solutions to problems in the reliability discipline field.