AI and IIoT-based predictive maintenance system for soybean processing

Abstract

This article presents an industrial predictive maintenance (PdM) system used in soybean processing based on artificial intelligence (AI) and Industrial Internet of Things (IIoT) technologies. The PdM system allows for the continuous monitoring of relevant production equipment/motor parameters, such as vibration, sound/noise, temperature, and current/voltage. It is designed to identify abnormalities and potentially break down situations to prevent damage, reduce maintenance costs and increase productivity. Condition monitoring is combined with AI-based methods and edge processing to identify the parameter changes and unusual patterns that occur before a failure and predict impending failure modes well before they occur. The PdM demonstrator currently under evaluation is planned to integrate intelligent IIoT-based sensors to measure parameters, convolutional neural network and Wi-Fi, LoRaWAN, Bluetooth low energy (BLE) technologies for intelligent communication.