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Industry 4.0 Brings Opportunities To Infuse Artificial Intelligence Into Manufacturing

We live in the age of Industry 4.0. This Fourth Industrial Revolution with its unprecedented speed and scale allows you to take a more data-driven approach to operations. This data, pulled from your assets, adds value and enables smarter decisions. As you integrate more assets into business workflows, along with technologies like 5G and edge computing, your challenge becomes uncovering what matters – finding the right insights, at scale. In the midst of this unusual and global disruption, these insights can be a vital key to operational resilience.

Start with collecting data, then add AI

Modern manufacturing relies heavily on the Internet of Things (IoT). It connects machines, computers, and sensors for a holistic view of the manufacturing facility and its assets to bolster production and quality.

Data is one component. But it is the ability to use AI and machine learning to visualize that data that matters more. Businesses are increasingly looking to AI to help them separate the signal from the noise in their systems. In a recent IBM survey, 34% of companies said they are adopting AI technology, up from 14% a year ago. That’s because these new technologies are what will ultimately provide operators with a way to more intelligently address asset maintenance and operations.

How AI adds intelligence to manufacturing

In a manufacturing plant where IT and OT may operate in information silos or in an organization where processes differ in varying degrees from plant to plant, connecting the data between the teams is pivotal. That connection enables you to deliver the right information, to the right people, in the right context, all for  better decisions. This collaborative view helps drive improved production efficiency and cost containment. AI-powered manufacturing can drive up to 30% yield improvements and 15% waste reduction.1

For example, when maintenance activities are carried out too frequently, a company incurs unnecessary costs. A smart factory, however, can use anomalies to predict the failure of assets and schedule maintenance only when it’s needed. That means you can reduce both downtime and costs. The beauty of AI lies in its ability to find those hidden anomalies while the system is behaving in a seemingly normal fashion.

Consider this: you may have two parameters that you watch. Both of them might be within their thresholds, and don’t send out alerts or notifications that something is going wrong. However, AI allows us to see that if ‘param1’ is on the upper end but within range, and ‘param2’ is on the lower end but within range, then there’s a potential problem. Now think about patterns across dozens or even hundreds of parameters. It’s the ability to analyze the complex relationships of these parameters that let us uncover a true anomaly. And this analysis, which would normally take hours to days to complete (and is sometimes even impossible to do manually), is now done in real time to keep operations running smoothly.

Accelerated response times with 5G + edge computing

When Klaus Schwab, founder and chairman of the World Economic Forum, first wrote about the Fourth Industrial Revolution in 2016, 5G networks had not even been introduced.

Now, 5G reduces response times from minutes and seconds, to sub-seconds. That accelerates communications to sensors and actuators, and delivers amazingly faster results. Then, couple this with edge computing. You realize how much easier it is to compute the massive amount of data from ubiquitous assets since you are no longer transmitting information across the network. Instead, you’re inferencing and scoring your AI by the data source, so that only the results are transmitted. This becomes especially powerful as you scale your operations. For example, if you have 500 machines in a manufacturing plant that each uses visual analytics and inferences there on the spot. then you still have 500 machines that can submit videos or pictures, which are large files, to a server for storage if they detect an issue.

Build a more resilient organization with AI-powered manufacturing

These are unusual times for manufacturing. Game-changing capabilities compete with unpresented disruption as companies work to address both the short- and long-term implications to their business. It’s also an opportunity to rethink operations, enhance data streams, automate and apply AI insights that build more flexible and resilient operations.

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Author: Philipp Schume – Associate Partner in IBM’s Global Intelligent Connected Operations Center of Competency.