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AI and IIoT-based Predicitive 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.

Category

Academic chapter

Language

English

Author(s)

  • Ovidiu Vermesan
  • Roy Bahr
  • Ronnie Otto Bellmann
  • Jøran Edell Martinsen
  • Anders Kristoffersen
  • Torgeir Hjertaker
  • John Breiland
  • Karl Andersen
  • Hans Erik Sand
  • Parsa Rahmanpour
  • David Lindberg

Affiliation

  • SINTEF Digital / Sustainable Communication Technologies
  • NxTech AS
  • DENOFA
  • Diverse norske bedrifter og organisasjoner

Year

2021

Publisher

River Publishers

Book

Artificial Intelligence for Digitising Industry: Applications

ISBN

9788770226646

View this publication at Norwegian Research Information Repository