# ThinkMachine

> ThinkMachine builds Equipment Agents (EA) — autonomous cyber-physical cognitive nodes that embed first-principles physics (thermodynamics, fluid mechanics, mass-transfer kinetics) into edge-compute for closed-loop industrial control. Each EA node executes a Perceive-Reason-Plan-Act cognitive loop at millisecond latency, delivering physics-guaranteed perception, real-time reasoning, and optimal control without human in the loop. Validated at R² +700% and NRMSE -52% vs. classic deep learning.

- Equipment Agents for industrial manufacturing
- Physics-Informed ML with embedded PDE/ODE constraints
- Closed-loop autonomous control on edge compute
- Soft sensing of unmeasurable internal states
- Target industries: metals, chemicals, biopharma, mining

## Core Pages

- [Landing Page (Chinese)](https://www.thinkmachine.work/): Full product overview, 5-layer architecture, agent foundry, industrial scenarios, and contact form
- [Landing Page (English)](https://www.thinkmachine.work/index_en.html): English version with identical structure and content

## Technology — Agent Cognitive Stack

Five-layer architecture from first principles to industrial applications:

- L0: First Principles — PDEs, ODEs, thermodynamics, fluid dynamics, reaction kinetics
- L1: Physics-Informed ML — PINNs, neural operators, physics-constrained loss functions
- L2: Equipment Agent Node (EA) — Autonomous cognitive core executing Perceive → Reason → Plan → Act
- L3: Multi-Agent Swarm (MAS) — Cross-equipment P2P coordination for plant-wide closed-loop optimization
- L4: Industrial Applications — Autonomous process optimization, energy management, predictive maintenance

## EA Capabilities

- Perception: Multi-modal sensor fusion + PINNs-based soft sensing of unmeasurable internal states
- Reasoning: Conservation-law-embedded inference + inverse identification of key physical parameters
- Planning: MPC / Safe RL within Control Barrier Function (CBF) safety envelope
- Action: Direct output to PLC/DCS with P2P multi-agent coordination
- Deployment: Edge-compute ready, few-shot fine-tuning with dozens of on-site samples

## Agent Foundry

- [Fermenter Agent](https://www.thinkmachine.work/#foundry): Autonomous metabolic pathway optimization via cell kinetics and O₂ transfer
- [Furnace Agent](https://www.thinkmachine.work/#foundry): Multi-phase thermodynamics control with electrode/lining wear sensing
- [Hydrocyclone Agent](https://www.thinkmachine.work/#foundry): Turbulent fluid dynamics separation with dynamic underflow/overflow tuning
- [Hydrocyclone Agent Cockpit Demo](https://hydrocyclone-simulator.vercel.app/): Live interactive demo with real-time PSD curves, mass balance, CBF safety envelope, and MAS swarm topology

## Industrial Scenarios

- [Process Optimization](https://www.thinkmachine.work/#scenarios-l4): Agent searches golden batch parameters within CBF safety boundaries
- [Energy Reduction](https://www.thinkmachine.work/#scenarios-l4): Agent learns energy-yield Pareto frontiers in real time
- [Predictive Maintenance](https://www.thinkmachine.work/#scenarios-l4): Agent tracks physical parameter degradation and predicts RUL
- [Operator Training](https://www.thinkmachine.work/#scenarios-l4): Real-time physics feedback and decision recommendations

## Contact

- [Schedule a Demo](https://www.thinkmachine.work/#contact): Partnership inquiry form (name, company, email, pain points)

## Optional

- [Architecture Diagram](https://www.thinkmachine.work/images/agent_cognitive_stack.jpeg): Agent Cognitive Stack 5-layer visual
- [Sitemap](https://www.thinkmachine.work/sitemap.xml): XML sitemap for all pages