## 3 Planning Strategy and Basic Assumptions  
### Planning Strategy  
General tests for multiple purposes should be performed to verify design conformity and the performance for novel products during the development stage. As the number of specimens is insufficient at this stage, the specimens must be used efficiently to maximize the specimen utility. If information from general tests can be applied to estimate the reliability of the novel product, it is possible to effectively use the specimens for reliability estimations. Therefore, the strategic planning of PADTs is required to gather sufficient reliability information for both use and accelerated conditions when two stress variables are applied. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**Authors**} & **Test Type** & \multirow{2}{*}{**Stress Loading**} & **Lifetime** & \multirow{2}{*}{**Optimization**} & **Decision** \\  & **(The Number of** & & & **Method** & **Depgradation Model** & **Criterion** & **Variable** \\ \hline [PERSON] and [PERSON] [2] & ALT (1) & [PERSON], [PERSON] & Exponential & [PERSON] & \(\pi\), SCT \\ [PERSON] [3] & ALT (1) & [PERSON] & [PERSON] & [PERSON] & \(\pi\), \(\pi\) \\ [PERSON] and [PERSON] [4] & ALT (1) & [PERSON] & [PERSON] & Avar & \(\pi\) \\ [PERSON] and [PERSON] [5] & ALT (1) & Constant & [PERSON] & [PERSON] & \(\pi\), \(s\) \\ [PERSON] [6] & ALT (1) & Constant & [PERSON] & [PERSON] & \(\pi\) \\ [PERSON] and [PERSON] [7] & ALT (1) & Constant & Burr XII & Avar & \(\pi\) \\ [PERSON] et al. [8] & ALT (1) & Step & Lognormal & Avar & SCT \\ [PERSON] [9] & ALT (1) & Step & [PERSON] & [PERSON] & SCT \\ [PERSON] and [PERSON] [10] & ALT (1) & Step & [PERSON] & [PERSON] & SCT \\ [PERSON] and [PERSON] [11] & ALT (1) & Step & Logistic & Avar & SCT \\ [PERSON] and [PERSON] [12] & ALT (1) & Step & Inverse [PERSON] & Avar & SCF \\ [PERSON] [13] & ALT (1) & Step & [PERSON] & [PERSON] & SCT \\ [PERSON] [14] & ALT (1) & Step & Exponentiated & & \\ inverse Weibull & & & & & \\ [PERSON] and [PERSON] [1] & ADT (1) & Step & WP & [PERSON] & \(s\) \\ [PERSON] et al. [17] & ADT (1) & Constant & WP & [PERSON] & \(\pi\), \(s\) \\ \hline \hline \end{tabular} Note, WP: Wiener process, Avar: asymptotic variance, D-opt: D-optimality, \(\pi\): sample proportions, \(s\): stress level, SCT: stress change time, SCF: SCT based on the number of failures.  
\end{table} 
Table 1: The literature on the design of PAT (partially accelerated test) plans [1]. This strategic approach is a two-phase process. In the first phase, the general tests are performed under use and accelerated conditions to obtain degradation data. For statistical efficiency, the accelerated condition of each stress variable is mostly determined at the maximum stress level; two stress levels of each stress variable are required. Four test points, which are combined with two stress variables, are considered to utilize the degradation data. The basic reliability information is gathered through these tests as there is no information when the novel products are developed. The information is used to estimate the parameters of the acceleration model. Thus, the allocation ratios for each of the test points are determined by the D-optimality criteria to minimize the variance of the estimated parameters [36]. In the above phase, each stress variable is tested at two levels to reduce the test time, cost, and specimen usage. However, this approach cannot identify the curvature effect of the model or estimate an accurate lifetime from the degradation data. Generally, three levels of each stress variable should be considered to provide reliable performance when solving this problem. In particular, the compromise concept with three levels has been used to resolve this problem in the accelerated degradation test (ADT) literature [24; 37]. Therefore, an extra test point should be considered alongside the previously mentioned test points in the first and second phase. The new test point is tested at the combined middle level of each stress variable.