Autonomy for industrial control systems
Autonomous systems use reinforcement learning and machine teaching to bring autonomy to industrial control systems across multiple industries.
Maximize throughput
Dynamically adapt to multiple and changing optimization goals to maximize the throughput of many processes.
Reduce operation costs
Reduce operation costs by improving process efficiency and reducing machine downtime through autonomous machine calibration and optimization.
Enable new levels of automation
Intelligent control systems can tackle industrial processes that were previously too dynamic and complex to automate.
Manage resources efficiently
Make your people more efficient and your industrial processes more sustainable.

Process optimization
Automatically control dynamic and complex processes for maximum output, minimum downtime, and reduction in part failure.

Machine calibration
Faster machine calibration and tuning exceeding operator-level precision.

Motion control
Optimize movement and trajectory for robotic arms, bulldozer blades, forklifts, underground drilling, rescue vehicles and more.
Chemical processing
Explore use cases in the chemical processing sector to learn how autonomous solutions are streamlining costs while improving production.
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Food extrusion line automation
Control the food extrusion process to optimize throughput while maintaining quality.
Business problem
A consumer-packaged goods manufacturer produces food using >50 extrusion lines. Each extruder is different and extruder behavior and process inputs change over time.
Current limitations
Operators manually control the extruder. Changes in the feed composition and moisture content make it very difficult for human operators or existing control systems to extrude puffs of consistent quality.
Project Bonsai solution
Maximized the throughput of product produced while maintaining the quality standard.

Calibrate and Control Polymer Reactors
Reduce the amount of time and product loss when calibrating your polymer reactor.
Business problem
Time required to achieve target polymer quality varies dramatically based on operator experience and dynamic ambient conditions.
Current limitations
Lengthy equipment calibration process required for each batch, and extensive experience required to control highly dynamic reaction.
Project Bonsai solution
Reduced the amount of time required to calibrate the simulation from several months to a few weeks.
Reduced the loss of non-prime grade polymer by 5%.

Partners in autonomous systems
Our system integration consulting partners can tailor our autonomous systems technology to your specific industry and use case. Leverage our network of experienced partners and simulation solutions to help you build intelligent autonomy into your industrial processes.

Get your business AI-ready
Learn how Microsoft AI is helping your industry with resources, tools, and case studies.

Autonomous systems overview
Microsoft is leading digital transformation with artificial intelligence that automates and simplifies everyday processes.

Explore Microsoft AI platform
Microsoft AI is a robust framework for developing AI solutions in conversational AI, machine learning, data sciences, robotics, IoT, and more.

AI Lab
Learn from labs that demonstrate how autonomous solutions can be applied to drone simulations, intelligent robotics, and more.