## 6 Analysis of Results and Discussion
### Analysis of Results
This contributed to a decrease in repair costs, maintenance costs, and unplanned downtime costs, as shown in the table, evidencing the effectiveness of the system in improving operational cost management. In addition to operational and cost-related improvements, the SIRPM model contributed to significant sustainability gains. By improving operational efficiency and reducing waste, energy consumption, and emissions, the model helped Alpha achieve its environmental goals (Table 16). \begin{table}
\begin{tabular}{l l l l} \hline \hline
**Cost Category** & **Before Implementation** & **After Implementation** & **Reduction** \\ \hline Average Repair Costs & EUR 2500 per incident & EUR 1200 per incident & \(-\)52\% \\ \hline Total Maintenance Costs & EUR 4000/month & EUR 2500/month & \(-\)37.5\% \\ \hline Unplanned & EUR 3500/month & EUR 1000/month & \(-\)71.4\% \\ \hline Total Operational Costs & EUR 30,000/month & EUR 25,000/month & \(-\)16.67\% \\ \hline \hline \end{tabular}
\end{table} 
Table 15: Cost reduction. The energy consumption was reduced by 25%, from 10,000 kWh to 7500 kWh per month, as a result of a more efficient use of equipment and fewer unplanned downtimes. CO\({}_{2}\) emissions saw a reduction of 40%, from 5000 kg to 3000 kg per month, contributing to a lower environmental footprint. Similarly, waste produced decreased by 30%, from 500 kg to 350 kg per month, while material usage was reduced by 18.75%, from 8000 kg to 6500 kg per month. The recycling rate also improved, rising by 21.43%, from 70% to 85%, reflecting better resource management and sustainability practices. The values presented in Table 16 regarding environmental and sustainability improvements were provided by the company, based on data collected during a period of 6 months, before and after the implementation of the predictive maintenance model (SIRPM). These values reflect the average of the environmental indicators during this study period and were used to compare the results before and after the application of the model. Energy and CO\({}_{2}\) emissions reduction can be analyzed against recognized standards such as those defined by ISO 50001 (energy management system) [67], which provide essential guidelines for companies to manage energy efficiently and reduce environmental impacts. These standards are widely adopted by companies worldwide to promote continuous improvement in energy and environmental performance. * ISO 50001 focuses on the continuous improvement of energy performance, with the main goal of reducing energy consumption. The standard suggests a reduction of 5% to 10% per year in companies that implement energy management systems [68]. The 25% reduction in energy consumption observed at Alpha significantly exceeds the standard's objectives, demonstrating excellent performance in terms of energy efficiency. The cost reductions and efficiency improvements also translated into stronger financial performance for Alpha, demonstrating the long-term economic benefits of adopting predictive maintenance technologies (Table 17). As seen in the table, the profit margin increased from 5% to 12%, reflecting the overall financial benefit of reduced maintenance and operational costs. This increase in profitability highlights the effectiveness of the SIRPM model in not only enhancing operational efficiency but also contributing to the company's financial growth. The calculations and surveys performed to measure improvements in maintenance performance, energy consumption, and emissions were based on manual records from the maintenance team before and after the implementation of the SIRPM model. During the period in which the model was not applied, the maintenance team recorded all failures,