Harnessing IoT Data and Knowledge in Smart Manufacturing

Joseph Shun Ming Yuen, King Lun Tommy Choy, Yung Po Tsang, Hoi Yan Lam

Research output: Chapter in book / Conference proceedingChapter in an edited book (as author)Academic researchpeer-review

Abstract

In the modern digitalized era, the use of electronic devices is a necessity in daily life, with most end users requiring high product quality of these devices. During the electronics manufacturing process, environmental control, for monitoring ambient temperature and relative humidity, is one of the critical elements affecting product quality. However, the manufacturing process is complicated and involves numerous sections, such as processing workshops and storage facilities. Each section has its own specific requirements for environmental conditions, which are checked regularly and manually, such that the whole environmental control process becomes time-consuming and inefficient. In addition, the reporting mechanism when conditions are out of specification is done manually at regular intervals, resulting in a certain likelihood of serious quality deviation. There is a substantial need for improving knowledge management under smart manufacturing for full integration of Internet of Things (IoT) data and manufacturing knowledge. In this chapter, an Internet-of-Things Quality Prediction System (IQPS), which is a mission critical system in electronics manufacturing, is proposed in adopting the advanced IoT technologies to develop a real-time environmental monitoring scheme in electronics manufacturing. By deploying IQPS, the total intelligent environmental monitoring is achieved, while product quality is predicted in a systematic manner.
Original languageEnglish
Title of host publicationHarnessing Knowledge, Innovation and Competence in Engineering of Mission Critical Systems
EditorsAli G. Hessami
PublisherIntechOpen
Chapter10
Pages161-175
Number of pages15
ISBN (Electronic)978-1-78984-467-2, 978-1-78984-110-7
ISBN (Print)978-1-78984-109-1
DOIs
Publication statusPublished - 4 Mar 2020

Keywords

  • Smart manufacturing
  • Internet of Things
  • Knowledge Management
  • Quality Prediction
  • Fuzzy logic

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