Predictive Maintenance
A maintenance strategy that uses sensor data, analytics, and machine learning to predict when equipment is likely to fail, enabling repairs before breakdowns occur. Predictive maintenance reduces unplanned downtime and maintenance costs compared to reactive or time-based maintenance approaches.
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Total Productive Maintenance
A holistic approach to equipment maintenance that aims to achieve perfect production with no breakdowns, no defects, and no accidents. TPM involves operators in routine maintenance tasks and focuses on proactive and preventive maintenance to maximize equipment effectiveness throughout its lifecycle.
Industrial Internet of Things
The application of Internet of Things technology in industrial settings, connecting machines, sensors, and systems to collect and exchange data for improved manufacturing operations. IIoT enables real-time monitoring, predictive maintenance, and data-driven decision-making across the production environment.
Mean Time Between Failures
The predicted average time between equipment breakdowns during normal operation. MTBF is used to assess equipment reliability, plan preventive maintenance schedules, and make decisions about equipment replacement or upgrades.
Machine Learning in Manufacturing
The application of artificial intelligence algorithms that learn from historical and real-time production data to improve manufacturing processes. Machine learning enables predictive maintenance, quality prediction, process optimization, and demand forecasting by identifying patterns humans might miss.
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