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  • Control and optimization
  • Manufacturing

Parameter Tuning Automation: Achieving a 52% Time Reduction and 20% Increase in Accuracy

Improve software-based motion control accuracy through data-driven simulators and reinforcement learning for automated parameter tuning. This approach minimizes the gap between commanded and actual control values.

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  • Control and optimization
  • Manufacturing

Surface Mount Technology (SMT) Optimization: Achieving Peak Performance in Just 8 Weeks

Leverage reinforcement learning algorithms to strategically plan efficient electronic component mounting sequences on PCBs, minimizing overall process time, including Surface Mount Technology (SMT).

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  • Automobile
  • Anomaly detection

Industrial Robot Anomaly Detection: Anticipating Failures 5 Days in Advance Across 400+ Units

Predict critical failures and minimize downtime in an automotive assembly process with over 10,000 robotic arms by implementing anomaly detection within AI operating environments (MLOps).

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  • Control and optimization
  • Manufacturing

Robot Offline Programming Automation: A Jounrey from 6 Weeks to Days

Automate multi-robot chassis welding routes and tasks using AI and robotics, leading to a substantial reduction in labor hours and product production time.

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  • Control and optimization
  • Automobile

Electric Vehicle HVAC Control Optimization: 10% Reduction in Energy Consumption

Create an AI simulator using real-world electric vehicle data to optimize vehicle energy control with a lightweight model for enhanced computational speed.

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  • Control and optimization
  • Semiconductor

Chip Design Automation: 85% Reduction in Execution Time with 49% Performance Enhancement

Boost operational efficiency and performance through automated optimal component placement within custom-designed application-specific integrated circuits(ASICs) using AI-based simulators and reinforcement learning agents.

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  • Predictive analysis
  • Energy

Solar Power Prediction: Over 3,000 Predictive Models Deployed Across 787 Plants

Develop an AI operating environment (MLOps) utilizing diverse ensemble models to enhance predictive accuracy, seamlessly operate across 787 power plants, and expedite the retraining and deployment of over 3,000 models.

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  • Chemical
  • Anomaly detection

Emergency Shutdown (ESD) Prediction for PP Process: Anticipating Events 7 Days in Advance

Leverage battery management system data and electric vehicle(EV) driving patterns for predicting lithium battery residual life and lifecycle monitoring.

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  • Predictive analysis
  • Battery

EV Battery Life Prediction: Covering 2,700+ Vehicles with 4.6X Improved Model Performance

Leverage battery management system data and electric vehicle(EV) driving patterns for predicting lithium battery residual life and lifecycle monitoring.

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  • Energy
  • Anomaly detection

Energy Storage System (ESS) Anomaly Detection: Predicting Irregularities 12 Hours in Advance

ESS anomaly detection models are designed to predict and monitor anomalies before a fire occurs and provide safety indicators.

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  • Semiconductor
  • Anomaly detection

Semiconductor Equipment Anomaly Detection: Achieving 90% Accuracy with 24-Hour Advanced Detection

Predict anomalies and time to failure with anomaly detection models that can respond quickly to recipe changes using minimal data from semiconductor production equipment.

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