## 3 Results and Discussion
### Analysis of Features
#### 3.3.3 Correlation Analysis  
The parametric [PERSON]'s and non-parametric [PERSON]'s correlations are performed as the last step in the inferential statistical analysis of features. In the preliminary study, we first perform multivariate and bivariate normality testing. The results suggest a violation of multivariate normality (\(p<0.001\)), while in bivariate normality, only the relationship between time to oil refilling (TTOR) and MTBF did not violate the normality assumption (\(p=0.149\)). Therefore, based on [PERSON]'s correlation, the TTOR and FRT are eliminated as they do not provide significant results (\(p<0.05\)). In the following, we provide [PERSON]'s heatmap (Figure 10) for a more straightforward interpretation and discussion of the results. \begin{table}
\begin{tabular}{c c c c c c c c c c c} \hline \hline
**Comparison** & **Mean Diff.** & **95\%CI\({}^{\ddagger}\)** & **95\%CI\({}_{\mathbf{U}}\)\({}^{\ddagger}\)** & **SE** & **Bias** & \(\mathbf{t}\) & \(\mathbf{d}\)\({}^{\ast}\) & \(\mathbf{p_{\text{tukey}}}\)\({}^{\ast}\) & \(\mathbf{p_{\text{bofof}}}\)\({}^{\ast}\)** \\ \hline \(1\) & \(2\) & \(-300.638\) & \(-695.270\) & \(116.112\) & \(205.510\) & \(3.273\) & \(-1.434\) & \(-0.423\) & \(0.481\) & \(0.928\) \\  & \(3\) & \(-199.358\) & \(-564.709\) & \(216.667\) & \(200.520\) & \(3.055\) & \(-1.013\) & \(-0.282\) & \(0.742\) & \(1.000\) \\  & \(4\) & \(-649.846\) & \(-1095.630\) & \(-280.948\) & \(205.606\) & \(6.667\) & \(-3.391\) & \(-0.928\) & \(0.005\) & \(0.006\) \\ \(2\) & \(3\) & \(105.039\) & \(-281.666\) & \(459.568\) & \(184.677\) & \(-0.218\) & \(0.518\) & \(0.141\) & \(0.955\) & \(1.000\) \\  & \(4\) & \(-351.316\) & \(-770.825\) & \(-2.045\) & \(191.945\) & \(3.394\) & \(-1.894\) & \(-0.505\) & \(0.237\) & \(0.366\) \\ \(3\) & \(4\) & \(-455.082\) & \(-855.195\) & \(-108.529\) & \(183.477\) & \(3.612\) & \(-2.600\) & \(-0.646\) & \(0.051\) & \(0.064\) \\ \hline \hline \end{tabular} \({}^{\dagger}\) Bias corrected accelerated (95\% lower and upper control limits). \({}^{\ast}\)\(d\) = Cohen’s d statistic; \(p\)-value adjusted using Tukey and Bonferroni correction.  
\end{table} 
Table 13: Post hoc ANOVA test of CMS. Figure 9: The distributions with point estimates of (**a**) CMS (1 = None, 2 = Pressure, 3 = Pressure, Flow and Temperature, 4 = Pressure, Flow, Temperature and Contamination Control) (\(y\)-axis) and MTBF_Est (\(x\)-axis); and (**b**) Quantile–Quantile plot of residuals. The MPPM (Maintenance Personnel Per Machine) metric, which describes the number of personnel responsible for the maintenance of assets, suggests a positive correlation with the WOM metric (\(\rho\) = 0.234, \(p\) = 0.013, \(z\) = 0.225). As previously reported, this may be attributed to the confounding effect of company size and type. Next, the assets' age suggests a positive correlation with MTTR (\(\rho\) = 0.266, \(p\) = 0.01) and a negative correlation with MTPF (\(\rho\) = \(-0.409,p\leq 0.001\)). This suggests a significant increase in machine downtime, while in contrast, reduced time between failures, ultimately confirming that as an asset gets older, the availability decreases, ultimately affecting equipment effectiveness. The NWEC predictor, which is derived as a fluid power system capacity expressed via nominal working power (in [kW] power unit), results in a positive correlation with MTTR (\(\rho\) = 0.320, \(p\leq 0.001\)) and WOM (\(\rho\) = 0.385, \(p\leq 0.001\)). This, in turn, shows that fluid power systems with higher capacity tend to consume repair time and produce excessive fluid waste, which is expected in practice. Interestingly, there was no effect between NWEC and MTBF, which was surprising given that the literature often reports an increased failure rate as the capacity of a power system is higher [48]. Similarly, as the oil capacity or machine oil filling tends to be related to the power capacity of fluid power systems, the positive correlation with WOM is reported (\(\rho\) = 0.491, \(p\leq 0.001\)), which was expected.