Description
Don't start with AI for AI's sake. Your maintenance strategy shouldn't be a science experiment, or technology for technology's sake.
In this video, Matthew Wise, PhD shares a straightforward framework for getting started with AI for predictive maintenance, and for getting results:
Start with outcomes, not AI. Which business KPIs and asset performance goals are you trying to move?
Find your bang for your buck. Which assets have the highest failure rates, or the highest cost when they fail? Start there.
Audit your data landscape. Do you have the IoT devices and sensors you need to feed the AI machine, or are there gaps?
Plumb it in. AI predictive maintenance only delivers when it's connected to your systems. That's where seamless, AI-driven workflows come to life.
🔗 Learn more: https://www.abb.com/global/en/company/stories/ai-predictive-maintenance?utm_source=linkedin&utm_medium=organic_social&utm_campaign=2026_gfcc_ai&utm_content=video
Where does your organization typically start, and where does it get stuck?
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