RL-based Control Optimization Solution with a Data-centric Simulator

Key features

Closest to Reality
  • Real-time (Dynamics Model-based) simulation of actual equipment (What-If Simulations)
  • Improved simulation accuracy by minimizing the Sim2Real Gap through training neural networks with actual equipment and manufacturing data
  • Customize condition and control values to experiment with different inputs and view the results in real-time
Global Optimization
  • Derive a reinforcement learning-based optimization model that simultaneously optimizes multiple target variables by comprehensively considering future situations
  • Flexible and versatile application to various equipment and environments - such as production lines and HVAC systems
Rapid Adoption
  • Quickly derive optimal control values using only a small amount of data collected from equipments and manufacturing processes
  • Flexible solution applicable to customers' environments and governance systems - including On-Premise or Cloud applications
Rapid Adoption
  • 수집된 장비 및 공정 데이터만으로도 신속한 최적 제어 값 도출 가능
  • 클라우드, On-Premise 등 고객의 환경과 거버넌스에 적합한 유연한 솔루션 제공

Optimization Solution for intelligent equipment control

MRX CtrL enhances manufacturing productivity and equipment efficiency by deriving optimal control inputs with Reinforcement Learning methods and a data-centric simulator

Implementation process

Feasibility Check

  • Confirm collected equipment data
  • Set control optimization goals (define target variables)
  • Perform a Quick Feasibility Check using MakinaRocks' specialized QFC environment

Model Development

  • Develop data-centric simulator based on actual equipment data (Dynamics Model-based)
  • Develop a reinforcement learning model to explore the optimal control values in conjunction with the simulator


  • Install the control optimization solution
  • Customized development to satisfy different interface requirements for each user

Advanced Service

  • Monitor optimization solution performance
  • Retrain/Redeploy models based on changes to target equipment or process
  • Integrate optimization results with legacy systems (DCS etc.)
2-3 weeks
2 months
Consultation Needed
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