Condition Monitoring involves techniques used to monitor the condition of equipment and predict failures. It encompasses various methods to ensure machinery operates efficiently and to anticipate potential breakdowns.
A digital twin is a virtual model of a physical object or system, used to simulate, predict, and optimize performance and maintenance needs in real-time.
Predictive maintenance employs data analytics to forecast when maintenance should occur, thus optimizing maintenance schedules and enhancing operational efficiency.
Prognostics involves the prediction of the future performance and the remaining useful life of a system using data analysis, statistical models, and machine learning techniques. This field is crucial in various industries to prevent system failures and optimize maintenance.
