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.
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.
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.
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.
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.
We invite you to learn about the current state of the EAM market, and what it means to organizations in asset-intensive industries. You can also explore how intelligent asset maintenance and operations can help you capitalize on Industry 4.0 and deliver value to your organization. And learn more about IBM’s services for intelligent connected operations.
AI-powered manufacturing—with solutions deployed at the edge—can drive up to 30% yield improvements and 15% waste reduction, and 5-10% reduction in operating costs. It can also accelerate your journey to Industry 4.0. Fortunately, IBM possesses the essential combination of software, services, and industry expertise to build intelligent workflows that respond to rapidly changing conditions. Wherever you are in your digital journey, we will partner with you to deliver the AI-powered insights and consultative services required for more resilient business operations.
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In today’s fast-paced world of data analytics and AI, optimizing your data infrastructure is key to unlocking valuable insights and driving innovation.
In today’s fast-paced world of data analytics and AI, optimizing your data infrastructure is key to unlocking valuable insights and driving innovation.
In today’s fast-paced world of data analytics and AI, optimizing your data infrastructure is key to unlocking valuable insights and driving innovation.
At Pragma Edge, we are a forward-thinking technology services provider dedicated to driving innovation and transformation across industries.
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IBM Partner Engagement Manager Standard is the right solution
addressing the following business challenges
IBM Partner Engagement Manager Standard is the right solution
addressing the following business challenges
IBM Partner Engagement Manager Standard is the right solution
addressing the following business challenges
