How AI is helping reinvent the world of manufacturing

Throughout each industrial era, the companies best able to embrace change have become the most likely to succeed. This dates back to the development of steam and combustion engines through to electricity, microprocessors and now artificial intelligence.

In The Future Computed: AI and Manufacturing, Microsoft Senior Director Greg Shaw explores how AI, automation and the internet of things (IoT) present new challenges and opportunities.

Here are some of the manufacturers already demonstrating how the latest tech advances are changing the way they work.


A collaboration between Thyssenkrupp and Microsoft has led to the development of the elevator industry’s first real-time, cloud-based predictive maintenance system.

This means an elevator can accurately predict when it is about to fail and summon an engineer, making it far less likely that people could get trapped inside.  It is an effective way of managing maintenance resources, too, as they can be called in ahead of time.

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The manufacturing solutions company Jabil has moved toward more cross-functional workstreams and automation across the entire organization is the goal.

Its Factory of the Future initiative is based on a connected system that can correct itself before problems arise. As the firm’s Vice-President of Operational Technology says: “Don’t make a defect, fix it now. Do it automatically, rather than using charts to diagnose later.”

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Failure could lead to unthinkable consequences in the aerospace sector, where a small mistake anywhere in the manufacturing process could be amplified into a catastrophe.

The industrial group MTorres uses machine learning and AI to laminate airplane wings with carbon fiber at speeds of 60 meters per minute. That means greater efficiency, improved productivity and higher rates of accuracy. It also has an automated inspection module that uses a high-resolution camera and a laser to spot defects on the surface of the carbon fiber layers in real time.

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Toyota Material Handling

The movement of stock at a warehouse belonging to the logistics firm Toyota Material Handling is now under the control of an army of small robots.

The company uses Microsoft Bonsai and Microsoft AirSim to train these stock management robots and analyze their operations. The bots are part of an autonomous “swarm” that collects a variety of parts and transports them to the correct area of the warehouse. They can navigate around racks and pallets, and identify the right bar code on a shelf full of products. Eventually, they will be able to recognize a part on sight, rather than via scanning.

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ZF Group

The auto parts giant ZF Group is using AI and algorithms to make production more reliable and more sustainable.

The main goal for its digital tech tools is to detect and predict mechanical failures ahead of time. That can prevent disruption to output and help save energy. The company has also developed a tool for its workforce called XReality. It is a combination of augmented and mixed reality that helps workers identify machines and parts, access data or solve problems.


The packaging firm TetraPak is using AI-powered predictive maintenance to prevent unseen failures of this kind. It can spot potential problems weeks ahead of them becoming critical.

With around 600 data points per piece of production equipment, TetraPak generates far too much data for a human operative to trawl through and spot potential component problems. But processing the data via Microsoft Azure means there is now a smooth pipeline of replacement parts on order well in advance of maintenance issues occurring.

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Connecting customers across a variety of industry sectors has helped ESAB create a platform that enables the identification of trends in the issues they sometimes face.

A subsidiary of industrial services business Colfax, ESAB specializes in welding equipment, cutting machines and fabrication solutions. Its latest creation is the “connected welder.” Every welder using ESAB equipment is linked to a platform that offers insights into more efficient use of materials and how to optimize consumables. It can also alert users to any potential supply chain issues.


The first industrial robots were kept behind bars. Not for their own safety, but for that of the people working nearby. ABB is changing that relationship.

With roots in robotics that go back to the 1970s, ABB is looking beyond the usual when it comes to automation. “We have been able to free robots from their cages to collaborate with humans,” says Bazmi Husain, ABB’s Chief Technology Officer. The company is taking AI to new places – its intelligent autopilot made it possible for a passenger ferry to be remotely piloted through a test harbor in Helsinki, Finland.

Schneider Electric

The energy management firm Schneider Electric is using AI to tame maintenance issues.

Using Microsoft’s Cortana Intelligence Suite, Schneider monitors trends in solar panel performance at a facility in Nigeria. This means technicians can address issues before they lead to outages. For example, a drop in the amount of electricity generated by a particular solar panel can indicate that it needs to be checked within 12 hours to avoid failure.


The Spanish oil and gas company Repsol is working with Microsoft to make AI-powered decisions on where and when to drill. AI and data analysis are helping to make drilling more precise. That means the need to drill fewer wells, and the opportunity for greater efficiency when drilling them. The time from site acquisition to commercialization of extracted resources is reduced, as is the overall impact of the activity.

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