Predicting ship machinery system condition through analytical reliability tools and artificial neural networks

Engineering

• Artificial Neural Network 100%
• Machinery 100%
• Ships 100%
• Reliability 100%
• Main Engine 83%
• Engine System 66%
• System Component 50%
• Fault-Tree Analysis 50%
• Failure Mode and Effect Analysis 50%
• Critical System 33%
• Prediction 33%
• Networks 33%
• Physical Parameter 33%
• Downtime 16%
• Exhaust Gas 16%
• Gas Temperature 16%
• Demonstrates 16%
• Reliability Analysis 16%
• Systematic Approach 16%
• Environment 16%
• Artificial Neural Network Model 16%
• Accidents 16%
• Business Loss 16%
• Failure (Mechanical) 16%
• Performance 16%
• Decision Maker 16%
• Predictive Maintenance 16%
• Maintenance Strategy 16%
• Container Ship 16%
• Engine Cylinders 16%
• Maintenance Action 16%