Ensure and raise spare part transaction request procedures and ensure equipment are maintained in safe and good operating conditions with high OEE and low spoilage
Perform equipment operating parameters check according to standard operating procedures or manufacture recommendation and carry out effective and prompt corrective action and report to his superior for further action
Perform breakdowns repair and ensure recovery plans are executed effectively and on timely basis
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Ensure and raise spare part transaction request procedures and ensure equipment are maintained in safe and good operating conditions with high OEE and low spoilage
Perform equipment operating parameters check according to standard operating procedures or manufacture recommendation and carry out effective and prompt corrective action and report to his superior for further action
Perform breakdowns repair and ensure recovery plans are executed effectively and on timely basis
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Support production line coordinator to pursue the fulfillment of all production goals.
Have clear understanding about different kinds of raw/auxiliary material/tools and know how to use them correctly to support high efficiency/cost effective manufacturing.
Implement TPM and other activities which is helpful to line continuous improvement.
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Process Optimization: Use regression and reinforcement learning to suggest optimal machine parameters (e.g., bond force, temperature profiles) for new product introductions (NPI).
Data Engineering: Build and manage data pipelines that ingest high-frequency sensor data from packaging equipment (e.g., Die Attach, Wire Bonders) via SECS/GEM or MQTT protocols.A/B Testing & Monitoring: Design experiments to validate model performance on the shop floor and monitor for "model drift" as machine parts wear down over time.
Core ML: 2+ years of experience with Python (Scikit-Learn, XGBoost, Pandas) and Deep Learning frameworks (PyTorch or TensorFlow).
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Production Deployment: Transition models from local environments (Jupyter/Python) into the factory’s execution system using Docker and REST APIs .
Process Optimization: Use regression and reinforcement learning to suggest optimal machine parameters (e.g., bond force, temperature profiles) for new product introductions (NPI).
Data Engineering: Build and manage data pipelines that ingest high-frequency sensor data from packaging equipment (e.g., Die Attach, Wire Bonders) via SECS/GEM or MQTT protocols. A/B Testing & Monitoring: Design experiments to validate model performance on the shop floor and monitor for "model drift" as machine parts wear down over time. Required Technical Skills
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