# Maintenance Time Prediction for Predictive Maintenance of Ship Engines
## 3 Results and Discussion  
The results of the maintenance time prediction algorithm based on the RGCCV and that based on the exhaust gas temperature of the cylinder were analyzed and compared, and the results are as follows. Figure 3 shows the exhaust gas temperature of cylinder no. 6 of GE no. 2 during operation, specifically its changes with the (a) operating time and (b) power output. In the AMS, the normal operating range for the cylinder exhaust gas in the GE is below 580 \({}^{\circ}\)C (yellow dotted line in Figure 3), and the data of VOYAGE 21113 cannot be identified based on the exhaust gas temperature alone [4]. Figure 4 shows the RGCCVs of the RGCCV-based algorithm considering the operating environment of cylinder no. 6 of GE no. 2 with the (a) operating time, along with the (b) voyage averages. In Figure 4, the yellow dotted line is the reference line for judging the concern stage (1) and the red dotted line is the reference line for judging the abnormal stage (2). Unlike the exhaust gas temperatures in Figure 3, which show simple changes, the RGCCVs in Figure 4 exhibit a decreasing trend versus the operating time for VOYAGE, indicating anomalous symptoms. These anomalies are further highlighted by the average voyage data in Figure 4b [4]. The MCRG, used to calculate the PTMRG (the result of the RGCCV-based maintenance time prediction algorithm), was selected for each cylinder (Table 5) by analyzing the exhaust gas temperature of the no. 2 GE in Table 4.  
Figure 4: Revision GE condition criterion values (RGCCVs) during operation of cylinder no. 6 of GE no. 2: (**a**) RGCCV vs. operating time and (**b**) average value per voyage. Figure 3: Exhaust gas temperature of cylinder no. 2 of GE no. 6 during operation as a function of (**a**) operating time and (**b**) power output. \begin{table}
\begin{tabular}{l c c c c c c} \hline \hline
**Item\(\backslash\)Cylinder** & **1** & **2** & **3** & **4** & **5** & **6** \\ \hline MCRG & 20 & 20 & 10 & 20 & 20 & 0 \\ PIRG & 886.73 & 819.27 & 939.94 & 924.18 & 1037.33 & 1026.28 \\ PSRG & \(-9.64\times 10^{-5}\) & \(-8.79\times 10^{-5}\) & \(-10.4\times 10^{-5}\) & \(-10.0\times 10^{-5}\) & \(-11.4\times 10^{-5}\) & \(-11.6\times 10^{-5}\) \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Calculation factors for predicted maintenance time by RGCCV (PTMRG). Figure 5 shows the (a) regression analysis results of the RGCCVs of cylinder no. 6 of GE no. 2 in VOYAGE 21113 versus the engine operating time, along with the (b) calculated PRMRG and PTROPRG. Figure 5a indicates that PIRG and PSRG (Table 5) are derived through the regression analysis of the engine operation time and RGCCV. Then, the GE maintenance time prediction algorithm is used to predict the maintenance time for cylinder no. 6 of GE no. 2 (Figure 5b). The PTMRG value for cylinder no. 6 of GE no. 2 is 2465.9 h, and PTROPRG is 118.2 h. As for the maintenance time prediction algorithm based on the exhaust gas temperature of the cylinders, PTMET and PTROPET were calculated by setting MCET for each cylinder of GE no. 2 (Table 6) based on the MCRG ('X' mark in Figure 5b) values in Table 5. As shown in Figure 6a, PIET and PSET were set through the regression analysis of the exhaust gas temperature and the engine operation time for cylinder no. 6 of GE no. 2 in VOYAGE 21113 (Table 6). PTMET and PTROPET were calculated, as shown in Figure 6b based on the MCET ('X' mark in Figure 6b) values in Table 6.  
Figure 5: RGCCV-based prediction of maintenance time for cylinder no. 6 of GE no. 2: (**a**) RGCCVs of VOYAGE 21113 (voyage with anomalous symptoms) vs. running time and (**b**) results of mainte-nance time prediction. Figure 6: Exhaust-gas-temperature-based prediction of maintenance time for cylinder no. 6 of GE no. 2: (**a**) exhaust gas temperature vs. running time of VOYAGE 21113 and (**b**) results of maintenance time prediction. For cylinder no. 2 of GE no. 6, the PTMET is 2498.3 h and the PTROPET is 150.6 h, predicting a maintenance point 32.4 h later than the PTMRG (2465.9 h) and PTROPRG (118.2 h).