Business value of autonomous systems

Autonomous systems can make industrial control solutions more adaptable to changing environments, tackle complex processes, and combine human and machine intelligence.

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.

Build intelligent industrial control systems

Program your unique expertise into AI models that deliver impactful results for industrial applications.

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Logistics and supply chain use cases

Learn how dynamic autonomous systems can streamline operations in warehouses, supply chain management, transportation, and more.

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Business problem

Navigating a warehouse to get an order filled quickly can be daunting.

Current limitations

Existing plans are not flexible, when changes to conditions, items, or bins occur, it is difficult to react quickly.

Project Bonsai solution

Optimize packing by following the recommendations that take into consideration the location, size, and quantity of each item in order and find the optimal position within the shipping bin or container.

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.

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.

More resources for autonomous systems

Bring autonomy to your use case

Ready to bring intelligence and autonomy to your industrial control systems? Our Project Bonsai team will help you determine how autonomous systems will power your business.

Get started with Project Bonsai