As more and more generative AI (GenAI) engines seem to emerge every day, it is easy to forget that GenAI isn’t the only artificial intelligence people and companies are using to drive efficiency and reliability. It’s true that GenAI is opening up new vistas of potential for operational excellence, but there’s a lot more to AI than just that.
As Drew Mackley explained in a recent round table with other automation experts at Plant Engineering magazine,
“AI can mean a lot of different things to a lot of different people.”
For example, machine learning-based AI has been in existence for a long time. Much of today’s modern industrial AI software has its roots in machine learning.
So, what does this mean for process manufacturers who are beginning to explore AI software for their organizations? It means they may have simple, reliable options to get started with AI, rather than jumping in all at once—if they’re selective in how they apply the technology.
On-board AI
Emerson has many AI-driven solutions in its portfolio. While some use GenAI, others use embedded AI software to deliver instant insights at the edge.
“For example, AI is built into wireless monitoring solutions to help identify and assess bearing and lubrication health — two common asset fault conditions. Some technologies even have first principles rules built in to guide the AI for a deeper dive into asset and process health. In both cases, the AI can help not only identify the problems but also provide severity, so personnel know how quickly they need to act.”
On the most basic level, Emerson’s AMS Wireless Vibration Monitor uses Emerson’s PeakVue Plus prescriptive analytics to help reliability personnel of any experience level more quickly turn data into action. PeakVue translates raw vibration data into a simple, reliable indication of equipment health via a single trend. This solves a lot of the problems that often slow reactiveness for reliability teams,
“There’s a lot of data and it can point to a lot of problems in rotating equipment, but they don’t all have the same severity or the same capacity to impact operations. Balance, misalignment, looseness and more are all common, but in many cases, an asset can run for years with those conditions. The most challenging solutions require some intelligence to sort out. People can do that, but it takes time to go through all that data and often, those expert personnel need to be doing other things.”
Other solutions, like Emerson’s AMS Asset Monitor, leverage AI-driven edge analytics to provide even more insight. It applies embedded auto analytics to alert personnel to common faults for a wide range of assets like fans, motors, gearboxes, pumps, and other rotating machinery.
Comprehensive software
When reliability teams are ready for even more advanced AI tools, many look to AMS Optics software. AMS Optics is an enterprise-level asset management and reliability platform for data management, predictive maintenance, and automated workflow orchestration. Not only does AMS Optics leverage Aspen Mtell® software to provide AI-driven guidance for assets across the enterprise, but it also creates a foundation to connect to other AI/ML analytics platforms for better visibility of enterprise health.
Though implementing AI can be a complex undertaking, Emerson offers a wide range of tools designed to bring it into the plant intuitively, empowering operators and maintenance personnel through better visibility, improved decision support, and faster answers so they can focus on the most valuable tasks in the facility.
