Internet of things (IoT) and big data analytics (BDA) for digital manufacturing (DM)

Zhuming Bi, Yan Jin, Paul Maropoulos, Wen-Jun Zhang, Lihui Wang

Research output: Contribution to journalArticlepeer-review

Abstract

This paper aims to investigate the impact of enterprise architecture (EA) on system capabilities in dealing with changes and uncertainties in globalised business environments. Enterprise information systems are viewed as information systems to acquire, process, and utilise data in decision-making supports at all levels and domains of businesses, and Internet of things (IoT), big data analytics (BDA), and digital manufacturing (DM) are introduced as representative enabling technologies for data collection, processing, and utilisation in manufacturing applications. The historical development of manufacturing technologies is examined to understand the evolution of system paradigms. The Shannon entropy is adopted to measure the complexity of systems and illustrate the roles of EAs in managing system complexity and achieving system stability in the long term. It is our argument that
existing EAs sacrifice system flexibility, resilience, and adaptability for the reduction of system complexity; note that higher adaptability is critical to make a manufacturing system successfully. New EA is proposed to maximise system capabilities for higher flexibility, resilience, and adaptability. The potentials of the proposed EA to modern manufacturing are explored to identify critical research topics with illustrative examples from an application perspective.
Original languageEnglish
Number of pages19
JournalInternational Journal of Production Research
Early online date19 Jul 2021
DOIs
Publication statusEarly online date - 19 Jul 2021

Keywords

  • Sustainable manufacturing
  • Internet of things
  • big data analytics
  • digital manufacturing
  • Cyber-physical systems
  • enterprise architecture

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