of machine components that are lubricated. Through wear particle analysis, you can identify the composition of the solid material present and evaluate particle type, size, concentration, distribution, and morphology. The use of Model Based Condition Monitoring for predictive maintenance programs is becoming increasingly popular over time. This method involves spectral analysis on the motor's current and voltage signals and then compares the measured parameters to a known and learned model of the motor to diagnose various electrical and mechanical anomalies. This process of "model based" condition monitoring was originally designed and used on NASA's space shuttle to monitor and detect developing faults in the space shuttle's main engine. It allows for the automation of data collection and analysis tasks, providing round the clock condition monitoring and warnings about faults as they develop. Other predictive maintenance methods are related to smart testing strategies. Applications (by industry) Railway Detect warning signs before they cause downtime for linear, fixed and mobile assets. Improving safety and track void detection through a new vehicle cab-based monitoring system Can also identify the type of track asset that the void is located under and provide an indication of the severity of the void Health Monitoring of point Machines (devices used to operate railway turnouts) can aid in detecting early symptoms of degradation prior to failure.· Manufacturing Early fault detection and diagnosis in the manufacturing industry. Manufacturers increasingly collect big data from Internet of Things (IoT) sensors in their factories and products and using different algorithms for the collected data to detect warning signs of expensive failures before they occur. Oil and Gas Oil and gas companies often lack visibility into the condition of their equipment, especially in remote offshore and deep-water locations. Big data can provide insight to oil and gas companies, this way equipment failures and the optimal lifetime of the system and components can be analyzed and predicted. See also Computerized maintenance management system Intelligent maintenance system Production flow analysis RCASE Root cause analysis References Safety engineering Maintenance