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
