## 4 Case Study
### Parameter Estimation and Result Analysis  
Based on the SDSADT data for the specific missile tank, the parameters in Equation (24) are estimated using the MC method. The estimated values for the parameters are \(\hat{a}_{0}=-10.5291\), \(\hat{a}_{1}=0.7985\), \(\hat{\delta}=3.2602\), \(\hat{\gamma}=3.395\times 10^{-6}\), and \(\hat{\sigma}_{\varepsilon}^{2}=0.1226\). By substituting the above parameter values into Equation (26), the storage life of the missile tank under normal stress levels can be obtained. In addition, the relationship function between product degradation path and stress level can be obtained by substituting the parameter estimates \(\hat{a}_{0}=-10.5291\) and \(\hat{a}_{1}=0.7985\) into Formula (3), as shown in Figure 4. As can be seen from the figure, the higher the stress level applied, the more obvious the product degradation path. Generally, the missile tank is considered to have failed when its reliability is below 0.9. From Equation (26), it is evident that when the reliability of the product under normal stress is 0.9, the storage time of the product is 43,401 h. Therefore, the average storage life of the missile tank based on the SDRD method is 43,401 h.  
Figure 3: Degradation path curve of the missile tank under the SDSADT. Compared with the method proposed in this article, the parameter estimates of the SNADM model are \(\hat{\alpha}_{0}=1.1025\), \(\hat{\alpha}=21.6517\), and \(\hat{b}=9897.7\). By substituting the parameter values into the reliability function, the storage life of the product under normal stress conditions can be calculated as 42,291 h. The parameter estimates of the simple IG model are \(\hat{\alpha}_{0}=-10.4705\), \(\hat{\alpha}_{1}=-1.2701\), and \(\hat{\lambda}=1.9431\times 10^{-8}\). By substituting the parameter values into the reliability function of Equation (9), the storage life of the product under normal stress conditions can be calculated as 43,028 h. The parameter estimates of the IG process model considering random effects are \(\hat{\alpha}_{0}=-4.7091\), \(\hat{\alpha}_{1}=0.3864\), \(\hat{\delta}=8.2703\times 10^{-6}\), and \(\hat{\gamma}=3.7615\times 10^{-7}\). By substituting the parameter values into the reliability function, the storage life of the product under normal stress can be calculated as 43,359 h.  
The storage life values of the missile tank calculated by each method are shown in Table 2. As shown in Table 2, the storage life assessment methods based on the SNADM and the simple IG process model do not consider the impact of random factors between different samples and the impact of uncertain factors such as detection environment and detection equipment. Therefore, their life assessment results are not satisfactory. The IG process model that considers random effects does take into account the randomness of and difference in product degradation paths. However, it still cannot avoid the impact of detection errors. Therefore, the effectiveness of this model in life assessment is second only to the SDRD model. The storage life assessment results indicate that the proposed SDRD model performs well in assessing the storage life of high-reliability and long-life products, and the assessment value is close to the index storage life. This is primarily due to the following reasons: First, the Gamma distribution is introduced to characterize the randomness among the degradation paths of different products. This approach enhances the life assessment capability of the IG performance degradation model. Second, considering the impact of detection errors on product degradation, the normal distribution is used to describe the detection errors of performance parameters. In addition, the MC method is used to replace traditional parameter estimation methods for estimating model parameters. This method can enhance calculation accuracy and efficiency. Therefore, the proposed SDRD model is more effective for assessing the storage life of high-reliability, long-life products.