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.

Explore use cases

Discover examples related to your industry and learn how autonomous systems can impact your operations and processes by leveraging your subject matter expertise.

Tech Minute: Watch how it works
Discrete manufacturing Chemical processing Logistics Energy Mining

 

 

Business problem

Sub-optimal control of the SAG mill grinding process increases energy cost, long term machine cost, and potential disruptions in the downstream mining process.

Current limitations

Humans monitor operational process, control machine set-points, and episodically add steel balls to the grinder. Human operators struggle to optimize processing of varying particle size distributions as well as hardness of input ore.

Project Bonsai solution

Autonomously control input feed tonnage, water addition, mill rotation speed, material recirculation rates and recommend episodic ball introduction actions.

Business problem

Sub-optimal control of the initial rock crushing process increases energy cost, long term machine cost, and potential disruptions in the downstream mining process.

Current limitations

Humans monitor operational process, periodically changing material feed speeds and machine set-points, struggling to optimize processing of varying particle size distributions as well as hardness of input ore.

Project Bonsai solution

Autonomously control conveyor speed, material feed speed, and throat crusher gap.

Business problem

An operator must tune a PID controller for each piece of equipment & cutting material. Each new piece of equipment must be tuned separately. This is a repetitive and time intensive process.

Current limitations

Currently dozer blade lift and lower is controlled by 5 PD parameters. The operator may need to increase or decrease the parameters on-site if the default settings for the PID controller are not suitable. PD controllers take time to tune, requiring different tuning settings for each dozer model and for some cutting materials.

Project Bonsai solution

Achieved a waviness number (from the cut) that exceeded the PID benchmark across multiple dozer models at multiple speeds.


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.

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