Manufacturing

Harriet Green, Hannover Fair: Perspectives on industry 4.0

Share this post:

What is Cognitive Manufacturing?

Cognitive Manufacturing (or industry 4.0) is what happens when we combine sensors, robotics, and data capture of the fourth industrial revolution with the machine learning and advanced data analytics of Watson. It’s what happens when we move beyond current connected systems that simply gather data, to industrial machines that use data to understand, sense, reason and take action.

We’re already seeing some staggering productivity results from this powerful capability. We’re training Watson with millions of images of products on the assembly line. With Watson IoT Visual Inspection, we can detect defects so small they are invisible to the human eye. And we can avoid costly production mistakes, on everything from computer chips to car doors. In fact, we’re already seeing a 10 percent reduction in manufacturing defects in tests of Watson IoT Visual Inspection.

We’re also using Watson to serve up decades of expertise – what we call “tribal knowledge” –  from generations of oil rig engineers at Woodside Energy in Australia, helping them bring new engineers up to speed, improve uptime, and ensure safety.

And at KONE, who are using Watson to keep a billion people moving on escalators and elevators each day. Using technology to transform the very nature a century-old company.

We are in the process of making history. We are using Watson and cognitive computing to transform the way we interact with the physical world. And in the process, we are redefining the way we Make, Design, and Operate the systems that facilitate life on this planet.

Make: IBM and ABB

ABB and IBM are working together to usher in the era of Cognitive Manufacturing. ABB is one of the great “makers” of our lifetime, a company that has pioneered industrial automation for more than a century, carrying the world from one industrial revolution to another.

They will be using Watson IoT for Manufacturing to bring real-time cognitive insights to the factory floor. And going to market with IBM on a cognitive energy solution that will use predictive analytics to help energy producers manage the supply-and-demand dynamics of renewable energy.

It’s cutting edge stuff. And you can read more about it on our blog.

Design: IBM and Schaeffler

We all know that to make great products, you first need a great plan. And that’s where our friends in design and engineering come in. This critical step in the process has always been part art, part science.

But in the cognitive era, we’re starting to remove some of the mystery from the design phase, so that engineers can work in a more informed.

The ways Schaeffler is using Watson IoT to inform the design of their bearings is nothing short of revolutionary. But it’s only the first step.

The company has already begun working with IBM to develop Digital Twins that inform every step of their manufacturing operation, from design to service. These digital representations of physical systems are going to fundamentally change the way we manage the engineering of complex products.

By visualizing and manipulating digital twins, we can understand and manage systems more quickly, more intimately. We can extend this management beyond design and engineering too, and into manufacturing systems and the ongoing operation of connected products.

And with Watson, the data from Digital twins—including unstructured audio, image and video data— will inform decisions across the organization. It will feed insight to industrial designers. It will spot defects on the assembly line. And it will enable true predictive maintenance.

In fact, with Watson, digital twins can enhance your entire industrial ecosystem, sharing critical information, and providing a single source across the value chain.

Operate: IBM and KONE

In the era of cognitive manufacturing, insight continues well past the end of the assembly line. Products that continuously monitor their use, report on their condition, and learn over time change the way we interact with the physical world.

This is not just a clever advert. This is real. It is happening today. Real-time analytics. Predictive analytics. A total transformation of the way products are operated in real-world environments. How they are experienced by our customers. And how we can build new services around these products to define our competitive differentiation.

Watson is already, quite literally, changing the world. This year alone at least 1 billion people will be touched in some way by Watson. Some through cognitive robotics. Some through cognitive ball bearings. And some through cognitive elevators.

And the most exciting part is, we’re only getting started. Through our work, our creativity, our innovation, we get to shape history. We get to define this era of cognitive manufacturing.

Add Comment
No Comments

Leave a Reply

Your email address will not be published.Required fields are marked *

More Manufacturing Stories
By Wired Brand Lab on November 1, 2017

Manufacturing is about to cross the physical-digital divide

If you’re curious about what the future of manufacturing holds for years to come, you won’t necessarily find it by touring an assembly line or a cutting-edge chip fab. Nor would you appreciate its potential by sitting down in a new car or powering up an Intel-powered laptop. It’s not really so much about the […]

Continue reading

By Sapna Nauhria on September 25, 2017

Best-in-class manufacturers usher in the fourth Industrial Revolution

The introduction of Internet of Things (IoT) into the manufacturing world has ushered in the fourth industrial revolution, also known as Industry 4.0. Not surprisingly, this era will be unlike any that has come before it. It will introduce systems and machines that can communicate with each other, and use artificial intelligence (AI) and cognitive […]

Continue reading

By Greg Milwid on September 1, 2017

Optimize equipment reliability by listening to your data

The world is more connected than ever before. Using Internet of Things (IoT) technologies, manufacturers are collecting large amounts of data from their machines but do not know how to optimize it. It’s as if their machines are speaking on mute. They have so much to say but we simply cannot hear them. To help […]

Continue reading