MakinaRocks Use Cases

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  • Manufacturing
  • Anomaly detection

Industrial Motor Anomaly Detection: Data System Ready in Under a Week

Reduce production line downtime resulting from motor failures with an advanced data collection framework and an AI-driven operational platform (MLOps), tailored for the efficient oversight of extensive machinery networks.

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  • Control and optimization
  • Manufacturing

Parameter Tuning Automation: 52% Faster, 20% More Accurate

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

SMT Performance: Optimized in 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: Failures Predicted 5 Days Ahead

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: 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

EV HVAC Control Optimization: Energy Use Cut by 10%

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% Faster Execution, 49% Better Performance

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: 3,000+ 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 Prediction: Anticipating Events 7 Days in Advance

Implement a deep learning-based anomaly detection model in a continuous process reactor for petrochemical polypropylene (PP) to proactively predict emergency shutdowns (ESD) and gain insights into anomaly characteristics.

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  • Predictive analysis
  • Battery

EV Battery Life Prediction: 4.6X Model Performance Boost

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: 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 Anomaly Detection: 90% Accuracy, 24-Hour Alert Lead Time

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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