November 2, 2025
November 2, 2025
Most industrial machine failures donβt come with a warning. In fact, according to ARC, 82% of them appear random.
But, as you may already know, theyβre not.
Youβve just never looked deeply enough into the conditions behind those failures?
If you can surface conditions from within operational data, you can make better decisions, faster and with fewer surprises.
This goes beyond Condition-Based Maintenance.
Itβs called Condition-Based Actions.
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Traditional approaches rely on whatβs already known. They work great, if the failure mode is familiar.
But in modern manufacturing, new conditions are emerging all the time, and often, no oneβs seen them before.
Still, the system gives you clues. You just need to know how to listen.
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Act on emerging conditions, not just historical ones
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Improve reliability by catching the βrandomβ failures
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Go beyond maintenance: impact energy, safety, emissions
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Reduce reliance on guesswork and tribal knowledge
Whether itβs a spike in vibration, a shift in power consumption, or an anomaly in fluid dynamics, every condition tells a story. One you can act on.
Kudzai Manditereza is an Industry4.0 technology evangelist and creator of Industry40.tv, an independent media and education platform focused on industrial data and AI for smart manufacturing. He specializes in Industrial AI, IIoT, Unified Namespace, Digital Twins, and Industrial DataOps, helping digital manufacturing leaders implement and scale AI initiatives.
Kudzai hosts the AI in Manufacturing podcast and writes the Smart Factory Playbook newsletter, where he shares practical guidance on building the data backbone that makes industrial AI work in real-world manufacturing environments. He currently serves as Senior Industry Solutions Advocate at HiveMQ.