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.
Logistics
AI is helping to create autonomous systems across industries. Learn how these dynamic solutions can streamline operations in warehouses, supply chain management, transportation, and more.
Get the logistics infographic

Warehouse Storage and Retrieval Optimization
Dynamically optimize and balance throughput and efficiency within the warehouse to maximize financial return.
Business problem
Inefficient storage and retrieval decisions can have severe negative financial impacts.
Current limitations
Human operators and rules-based algorithms dictate storage location upon loading, and retrieval policies upon shipment. Manual methods are static and do not adapt to changing customer and market demands.
Project Bonsai solution
Balance warehouse fill density and labor efficiency. Balance fill density with long term throughput. Maximize financial return by choosing optimal actions in varying warehouse states and inventory storage patterns.

Supply Chain Inventory Optimization
Dynamically optimize regional inventory replenishment to create stable and predictable stocking levels, avoiding lost sales.
Business problem
Many to many relationships between distribution centers and local supply locations force complex allocation decisions. Poor regional replenishment decisions lead to local stock out conditions and lost sales.
Current limitations
Linear optimization decisions using SAP APO. Struggles to adapt to forecast inaccuracies and rapidly changing local demand.
Project Bonsai solution
Decompose inventory allocation options into product and distribution center combinations. Simulate and train AI against dramatically different and changing demand profiles. Combine different inventory allocation alternatives into master optimization strategy.

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.