## 4 Design and Simulation of the Conceptual Model for Capacity Planning of an OEM Plant
### Simulation Results for the Case Study of an Automotive Plant
Moreover, the customer order lead time was 8.1 days larger in the nonviable system model due to a long decision-making process that led to an investment to increase production by 200 units per day. The VSM model increased production by only 100 units per day. Therefore, as in the first scenario, from the comparison of the models, the results show that the VSM simulation model would be selected as desirable in this demand scenario due to its combination \begin{table}
\begin{tabular}{c c c c c} \hline
**Simulation** & **Demand Scenario 1** & **Key performance** & **VSM Simulation** & **Nonviable** \\
**Level** & **Demand Scenario 2** & **Indicator (KPI)** & **Model** & **Simulation Model** \\ \hline \multirow{8}{*}{Plant level} & & Profits (million euros) & 1021 & 1012 \\  & - & Launch curve until & Total production (units) & 660,129 & 655,761 \\  & - & t = 100 days & Capacity utilization (\%) & 94.3 & 82.0 \\  & - & Stationary demand & Maximum production & 700 & 800 \\  &  for the new model at & Service level (\%) & 98.5 & 97.6 \\  & & for the 2 nd model at & Customer order lead time & 49.7 & 58.6 \\  & & (days) & Operational savings & 1.0 & 0.0 \\  & & (million euros) & 30.0 & 60.0 \\  & & & Return on investment & 70.0 & 70.0 \\ \hline \end{tabular}
\end{table} 
Table 1: Simulation results for demand scenario 1, stationary scenario, at the plant level. VSM, viable system model. \begin{table}
\begin{tabular}{c c c c c} \hline
**Simulation** & **Key Performance** & **VSM Simulation** & **Nonviable** \\
**Level** & **Demand Scenario 2** & **Indicator (KPI)** & **Model** & **Simulation Model** \\ \hline \multirow{8}{*}{Plant level} & & Profits (million euros) & 934 & 925 \\  & - & Trend until t = 250 days until stationary demand for new model at units/day and the 2 nd model at & Total production (units) & 617,021 & 612,520 \\  & - & Trend until t = 250 days until stationary demand for new model at 400 units/day and the 2 nd model at & Capacity utilization (\%) & 88.2 & 76.7 \\  & - & Maximum production capacity (units/day) & 700 & 800 \\  & - & Service level (\%) & 97.2 & 95.3 \\  & - & Customer order lead time (days) & 46.3 & 54.4 \\  & - & Operational savings & 3.5 & 0.0 \\  & - & Investment value (million euros) & 30.0 & 60.0 \\  & - & Return on investment & 28.8 & 15.4 \\ \hline \end{tabular}
\end{table} 
Table 2: Simulation results for demand scenario 2, trend/stationary scenario, at the plant level. VSM, viable system model. of a low investment, operational savings, and highly efficient deployment (lead time, service level, and capacity utilization). In the third scenario, according to Table 3, the VSM produced better results for all relevant indicators except capacity utilization due to the fact that the nonviable system model did not increase its capacity. As this decision was never made, the viable system model produced a higher total number of delivered units but lower capacity utilization. This situation arises from the fact that, as the demand was volatile and had a trend pattern, the nonviable system model was not able to identify the need for a new investment. This led to a volume loss of almost 45,000 units during the four-year period and a profit loss of 91 million euros. In addition, the VSM was able to generate savings of 10.0 million euros. As the nonviable system model did not increase its capacity, the capacity utilization was 6.4% higher than in the VSM, which increased its capacity by 100 units per day. The return on investment of this increase is positive and accounts for 70 million euros. Moreover, the customer order lead time in the nonviable system model was almost 30 days longer than in the VSM model. In addition, the service level was also 2.3% higher in the VSM model.