## 2 Literature Review
First, the usage patterns and the end of life conditions of used products are not known or fully understood in detail, and this contributes to the increase in uncertainty. Many usage conditions, like maintenance history and operating conditions, are processes that the remanufacturer does not fully understand, and it would be expensive and time-consuming to obtain all the relevant data. Second, the measurement errors that arise between inspectors or from improper gauging are generally seen as a strong contributor to quality uncertainty. \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline
**Uncertainty** & **Research** & **Policy** & **Primary Set** & **Description** & **Procedure** & **Data** & **Procedure** & **Objective** & **Data** \\  
There are a number of studies that have suggested an application of grey system theory to handle uncertainty in remanufacturing. These methods are effective in evaluation processes and for reducing uncertainty in decision-making processes regarding remanufacturing systems. [PERSON] et al. [18] proposed a tool for decision-making based on grey system theory to provide the classification of the sustainability level of remanufacturing. They categorized three classes of remanufacturers, which related to the different sustainability levels. This tool aids to define the existing state of remanufacturing and then recognize and prioritize company activities that need to be improved. Following their previous research, [PERSON] et al. [25] developed a mixed method for the sustainability assessment of remanufacturing processes by employing grey decision making for small- and medium-sized remanufacturers. The levels of sustainability were classified into three levels, namely, acceptable (requires minor improvement actions), conditionally acceptable (major corrective actions), and unacceptable (full corrective actions). [PERSON] [19] evaluated the remanufacturability of used automotive components based on a grey fixed weight clustering approach. The results showed that the proposed indices could be applied for effective evaluation. Most studies in the field of grey system theory for handling uncertainty in remanufacturing have only focused on remanufacturing operations. The above literature review presents some gaps in the research on the application of grey system theory to handle quality uncertainty regarding sorting during core acquisition in remanufacturing, as detailed in Table 3. The differences between the scopes and proposed models from the past studies are evident in the table. One of the substantial differences between the proposed model and previous works is that in the present study, the evaluation criteria for incoming core quality are considered in the sorting model. In achieving the research objectives, this study contributes to filling the gap in the scope of core acquisition management and determining quality evaluation criteria for incoming cores by considering technological, physical, and usage conditions in remanufacturing in the context of a circular economy. Figure 1: The uncertainties in remanufacturing (adapted and extended from [PERSON] et al. [24]. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**References**} & \multirow{2}{*}{**Methods**} & \multicolumn{5}{c}{**Research Contribution**} \\ \cline{3-6}  & & \multicolumn{2}{c}{**Remanufacturing Activities**} & \multicolumn{2}{c}{**Evaluating Criteria**} \\ \cline{3-6}  & & **Cores** & **Remanufacturing** & **Sustainability** & **Remanufacturability** & **Quality** \\ \hline \multirow{3}{*}{
\begin{tabular}{c} [PERSON] et al. \\ [18] \\ \end{tabular} } & \multirow{3}{*}{Grey clustering} & \multirow{3}{*}{\(\surd\)} & 1. & Economic & \\  & & & 2. & Environment & \\ \cline{1-1}  & & & 3. & Social & \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Comparison of previous works with the proposed models. AHP: analytical hierarchy process.