Editing Ai Manufacturing (section)

== <span style="color: #FFFFFF;">Remembering</span> ==
* '''Industry 4.0''' — The fourth industrial revolution: integration of digital technologies (AI, IoT, cloud) into manufacturing.
* '''Predictive maintenance (PdM)''' — Using sensor data and ML to predict equipment failures before they occur.
* '''Condition monitoring''' — Continuously measuring machine parameters (vibration, temperature, current) to assess health.
* '''Digital twin''' — A virtual model of a physical asset, process, or system that mirrors its real-world counterpart in real time.
* '''Computer vision for quality''' — Using cameras and CNNs to automatically detect product defects on production lines.
* '''Anomaly detection (manufacturing)''' — Identifying abnormal process conditions that may indicate quality problems or impending failures.
* '''OEE (Overall Equipment Effectiveness)''' — Key manufacturing metric: Availability × Performance × Quality; AI aims to maximize this.
* '''Process optimization''' — Using AI to continuously tune process parameters (temperature, pressure, speed) for optimal output.
* '''Yield optimization''' — Maximizing the fraction of manufactured items that meet quality specifications.
* '''SCADA (Supervisory Control and Data Acquisition)''' — Industrial control systems providing real-time monitoring and control of equipment.
* '''PLC (Programmable Logic Controller)''' — Industrial computers controlling manufacturing machinery.
* '''IIoT (Industrial Internet of Things)''' — Sensors, actuators, and computing devices networked in industrial settings.
* '''FMEA (Failure Mode and Effects Analysis)''' — A reliability engineering method for identifying potential failure modes; ML can automate this.
* '''Root cause analysis''' — Identifying the underlying cause of a quality defect or equipment failure.
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