# Circular Economy Strategy Selection Through a Digital Twin Approach
## 3 Materials and Methods
### \"To-Be\" Scenarios
#### 3.2.3 Design of Experiment  
As already asserted, the aim of this study was to evaluate the sustainability of two RL strategies and assess their suitability in practice. Three factors were identified to evaluate the response of the system. The following key factors that may have a potential impact on  
Figure 4: “to-be 2” operational flows (blue blocks) and logistic flows (green blocks). Figure 5: “to-be 2” simulation model. the performance of the system were considered: the distance between manufacturer and customer, the flooring thickness, and the quality of the returned flooring. These factors were selected based on their direct relevance to the operational, economic, and environmental performance of the reverse logistics process in this specific industrial context. In particular, they reflect the main sources of variability that were identified through discussions with industry experts and company management and are considered to be the most critical in shaping the outcomes of the two scenarios under study. Two possible distances from the manufacturing facility to the customer location were simulated. Additionally, eight different quality scenarios were considered, each simulating a different percentage of returned flooring in low-, medium- and high-quality conditions. These scenarios were simulated to provide a comprehensive overview of the potential end-of-life conditions of the flooring. Finally, the effect of flooring thickness was evaluated. Three different thickness scenarios were defined, each with different demands for low-, medium-, and high-thickness flooring. These scenarios were used to assess the probability of customer demand for a specific thickness, which has a direct impact on both the production and transportation phases. For each experiment, the simulation model provides the results for the two \"to-be\" scenarios. Overall, 128 different experiments were designed. Each one was replicated 25 times using a one-minute time step to simulate a typical working day. For each scenario, the average values across replications were calculated and used for the key performance indicators to ensure the consistency and robustness of the comparison of the reverse logistics strategies. Tables 1-3 provide an overview of the data used for each scenario. Table 1 presents two transportation distance scenarios representing short and long return distances between the customer and manufacturer. These distances were used to evaluate how logistics impact both economic costs and CO2 emissions in each reverse logistics strategy. Table 2 defines eight quality scenarios that had varying proportions of returned flooring classified as high, medium, or low quality. These scenarios influence the choice of a CE strategy (remanufacturing, recycling, or disposal) and allow for the assessment of how the product condition affects profitability and sustainability. Table 3 shows four scenarios reflecting the customer demand distributions for flooring with different thicknesses. Since thickness affects the product weight, these scenarios were used to analyze its impact on production costs, transportation efficiency, and overall system performance. \begin{table}
\begin{tabular}{l l l} \hline \hline
**Scenario** & **Distance [km]** \\ \hline Scenario 1 & 300 \\ Scenario 2 & 1000 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Distance scenarios. \begin{table}
\begin{tabular}{l l l l} \hline \hline
**Scenario** & **High Quality [\%]** & **Medium Quality [\%]** & **Low Quality [\%]** \\ \hline Scenario 1 & 50\% & 30\% & 20\% \\ Scenario 2 & 50\% & 40\% & 10\% \\ Scenario 3 & 60\% & 20\% & 20\% \\ Scenario 4 & 60\% & 30\% & 10\% \\ Scenario 5 & 70\% & 20\% & 10\% \\ Scenario 6 & 70\% &  
The following key performance indicators (KPIs) were used to assess the sustainability of the \"to-be\" scenarios:  
* Average profit [EUR/kg];
* Average CO2 emissions [kgCO2/kg]. The average profit represents the mean profit per kg of flooring produced and reflects the economic efficiency of the strategy.