Predictive Maintenance Using Edge AI in Brownfield Factories

“Predictive Maintenance Using Edge AI in Brownfield Factories” explores an architecture that combines retrofitted vibration sensors, TinyML, Fast Fourier Transform signal processing, and LSTM autoencoders to detect equipment anomalies locally. By processing high-frequency data at the edge, the system avoids cloud latency and bandwidth constraints while supporting rapid safety responses.

The case demonstrates that successful industrial AI depends as much on domain expertise, cybersecurity, and physical operating conditions as on algorithms. Its central lesson is clear: in brownfield environments, AI must conform to industrial physics; not the reverse.

Smart Manufacturing - Case no6_Predictive Maintenance Using Edge AI in Brownfield Factorie.

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