Comprehensive analysis of engine performance metrics and predictive maintenance
1500+
7
65%
35%
The dataset contains engine performance metrics including RPM, oil pressure, fuel pressure, coolant pressure, oil temperature, coolant temperature, and engine condition (1 = healthy, 0 = faulty).
Analyze the proportion of healthy vs faulty engines in the dataset.
Determine if there's a correlation between engine RPM and failure likelihood.
Explore relationships between different pressure and temperature readings.
Identify combinations of metrics that best predict engine failure.
Find critical thresholds for various metrics that indicate potential failure.
Build a model to predict engine condition based on sensor readings.
Identify unusual patterns in engine behavior that may indicate issues.
Analyze how engine performance changes over operational cycles.
845
3.42
7.31
2.45
78.2°C
78.9°C
Approximately 65% of engines in the dataset are in healthy condition, while 35% show signs of fault or potential failure.
Faulty engines are more prevalent at higher RPM ranges, suggesting that sustained high RPM operation may contribute to engine failure.
Oil pressure shows the most consistent distribution, while fuel pressure has the widest variance across engines.
Both oil and coolant temperatures follow similar distributions, with most engines operating in the 70-85°C range.
Faulty engines show stronger correlations between temperature metrics and failure, while healthy engines maintain more stable pressure readings.
Healthy engines maintain a more consistent relationship between metrics, while faulty engines show more extreme values.
Engines with oil pressure below 2.0 or above 5.0 have a significantly higher failure rate.
Approximately 8% of engines show anomalous behavior patterns that could indicate early-stage issues.
Oil temperature and fuel pressure are the most important predictors of engine failure in our model.
The model achieves 87% accuracy in predicting engine failure, with higher confidence for extreme parameter values.
Engine performance shows a gradual decline over time, with significant drops occurring after approximately 800-1000 operational hours.
Based on current trends, 22% of engines require immediate maintenance, while 45% should be scheduled for maintenance within 30 days.