{"id":37171,"date":"2024-10-23T10:08:16","date_gmt":"2024-10-23T14:08:16","guid":{"rendered":"https:\/\/eptura.wpengine.com\/?p=37171"},"modified":"2025-02-19T10:46:52","modified_gmt":"2025-02-19T15:46:52","slug":"new-uses-for-ai-in-maintenance","status":"publish","type":"post","link":"https:\/\/eptura.com\/discover-more\/blog\/new-uses-for-ai-in-maintenance\/","title":{"rendered":"AI in action: Innovative uses for enhanced maintenance strategies"},"content":{"rendered":"

Modern maintenance management is all about working with large data sets. Often, it\u2019s to track key performance indicators, but increasingly to use predictive maintenance (PdM), where, for example, you feed an asset\u2019s digital twin a steady stream of real-time data so it can warn you about future failures long before they happen.\u00a0\u00a0<\/span>\u00a0<\/span><\/p>\n

And that\u2019s just the start of the endless applications of artificial intelligence (AI) in maintenance.<\/span>\u00a0<\/span><\/p>\n

What is artificial intelligence (AI)?<\/span>\u00a0<\/span><\/h2>\n

Before looking at its future in maintenance, it\u2019s important to have a solid sense of what AI is and where it\u2019s heading.\u00a0<\/span>\u00a0<\/span><\/p>\n

A basic definition of AI is that it\u2019s an intelligent entity created by humans that can perform tasks without explicit instructions. Also, it can think and act rationally and humanly. Because of how often humans are irrational and sometimes biased, it\u2019s possible to define AI as the best possible version of ourselves. But that\u2019s a bit philosophical.<\/span>\u00a0<\/span><\/p>\n

Back down at a more practical level, a good way to understand AI is to look at some of the common ways researchers divide it into different types.\u00a0<\/span>\u00a0<\/span><\/p>\n

Strong and weak AI\u00a0<\/span>\u00a0<\/span><\/h3>\n

So, you can classify AI as strong or weak. Strong AI has a wider scope, human-level intelligence, and can cluster and associate data. Weak AI has a relatively narrower scope, is only good at specific tasks, and can use a combination of supervised and unsupervised learning to process data. A good example of weak AI is a simple computer chess game.\u00a0<\/span><\/p>\n

Artificial narrow intelligence (ANI), artificial general intelligence (AGI), and artificial super intelligence (ASI)\u00a0<\/span>\u00a0<\/span><\/h3>\n

ANI is currently the most common and most established type of AI application. It\u2019s able to do one task well, but only that one task. An example could be an AI that can guess what products you might also be interested in by looking at past purchases. Another would be an AI that can predict the weather.\u00a0\u00a0<\/span>\u00a0<\/span><\/p>\n

For facility and maintenance managers, an ANI would be able to predict future occupancy rates by looking at historical data or tell you the best time to change out the air filters on a piece of equipment based on sensor data fed into a digital twin. Another example is an AI that can make data-back suggestions for space planning and help employees reserve desks that best fit their work goals, including positioning team members close together to support connection and collaboration on in-office days.<\/span>\u00a0<\/span><\/p>\n

AGI is growing in research and implementation. Instead of being good at one task, an AGI would excel at a range of competencies, including:\u00a0<\/span>\u00a0<\/span><\/p>\n