Autonomy for industrial control systems
Autonomous systems use reinforcement learning and machine teaching to bring autonomy to industrial control systems across multiple industries.
Dynamically adapt to multiple and changing optimisation goals to maximise the throughput of many processes.
Reduce operation costs
Reduce operation costs by improving process efficiency and reducing machine downtime through autonomous machine calibration and optimisation.
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.
Automatically control dynamic and complex processes for maximum output, minimum downtime and a reduction in part failure.
Faster machine calibration and tuning, exceeding operator-level precision.
Optimise movement and trajectory for robotic arms, bulldozer blades, forklifts, underground drilling, rescue vehicles, and more.
Explore use cases in the discrete manufacturing sector to learn how autonomous solutions are streamlining costs while improving production.
CNC Machine Calibration
Automate the calibration of machines in seconds or minutes instead of hours or days.
Machine calibration was a manual, time intensive process, often performed by an out-of-town expert, which required machine downtime.
A manual process requiring expert human operators averaging 20–25 iterative steps over 2+ hours.
Achieved 2 micron precision at an average of 4–5 iterative steps over 13 seconds. System achieved superhuman precision (<1 micron) in ~10 iterative steps.
Wafer manufacturing process control
Automatically control reactors that grow silicon epitaxy rapidly and cost effectively.
Silicon epitaxy is grown in thermal reactors, which must be tightly controlled for uniform heating
Different phases of the process require different heat lamp settings to maintain optimal conditions in the reactor (called a recipe).
PID controller provides error correction in order to manage consistent temperature. PID singularly focused on heat distribution and doesn’t consider optimisation goals of speed or energy use.
Minimised time and cost of growing wafer substrate above a target quality consistency.
Capgemini’s autonomous systems service is designed to ensure your transformation reaches its full business potential.
Fresh can help experts in their fields deploy the power of machine learning to real-world applications without the need for in-depth data science expertise.
GlobalLogic’s deep cross-industry expertise enables global brands to hit the ground running as you imagine (or re-imagine) your products, services or capabilities.
Insight supports your operational efficiency and preventative maintenance initiatives by creating autonomous systems with machine teaching.
Neal Analytics understands how to properly instrument, deploy and use autonomous systems to solve real-world business problems in the cloud or at the edge.
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Autonomous systems overview
Microsoft is leading digital transformation with artificial intelligence that automates and simplifies everyday processes.
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Microsoft AI is a robust framework for developing AI solutions in conversational AI, machine learning, data sciences, robotics, IoT, and more.
Learn from labs that demonstrate how autonomous solutions can be applied to drone simulations, intelligent robotics, and more.