Industry 4.0 is based on digitization, information crosslinking and networks. In this investigation an Industrial Internet of Things (IIoT) architecture developed by the authors is used in conjunction with NDE datasets for near real-time diagnostics of crack initiation. Acoustic Emission datasets were acquired using aerospace-grade aluminum alloy and were subsequently used in the IIoT system, which is capable of Edge, Fog, and Cloud computing. The main innovation of this approach is a combination of hardware, computing and Machine Learning analysis proves to be advantageous in implementing a data structure that can successfully flag the incubation and subsequent initiation of fracture.
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