Assessing Factory’s Industry 4.0 Readiness: A Practical Method for IIoT Sensor and Network Analysis

Sabari Nathan Anbalagan*, Melissa Schwarz, R.H. Bemthuis, Paul J.M. Havinga

*Corresponding author for this work

Research output: Contribution to journalConference articleAcademicpeer-review

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Abstract

Manufacturing industries are aware of the benefits of Industry 4.0 (I4.0) and the pivotal role of the Industrial Internet of Things (IIoT) to facilitate the transition. However, they often underestimate the intricate connection between the implementation of IIoT and their existing sensing and communication systems. Hindering their progress towards I4.0 implementation, many factories still rely on rigid sensing systems, characterized by limited adaptability and inflexibility. This raises questions regarding the industrial readiness for I4.0 implementation and its ability to meet the sensing and connectivity standards of IIoT. Specifically, it is unclear whether the current brownfield installations, consisting of sensors and networking systems, adequately support the demanding I4.0 applications that necessitate a multi-functional and collaborative IIoT system. Our objective is to assess a factory’s progress towards I4.0 by examining the readiness of its sensing system and the communication capabilities of its network. We propose a two-stage analysis of factory readiness, including a functional segment-based sensor analysis and an application class-based network analysis. We present a case study conducted at an iron-making plant in The Netherlands to illustrate our method. Key findings of the case study include: (1) a lack of multi-functionality across segments for the majority of sensors (90%), (2) a considerable portion of network traffic (73%) requires high reliability, and (3) only 3% of the current network traffic necessitate ultra-reliable, low latency communication. Furthermore, we discuss how our method provides decision-makers with valuable guidance for the digital transformation of established and newly built manufacturing industries.
Original languageEnglish
Pages (from-to)2730-2739
Number of pages10
JournalProcedia computer science
Volume232
DOIs
Publication statusPublished - 20 Mar 2024
Event5th International Conference on Industry 4.0 and Smart Manufacturing, ISM 2023 - Iscte - University Institute of Lisbon, Lisbon, Portugal
Duration: 22 Nov 202324 Nov 2023
Conference number: 5
https://www.msc-les.org/ism2023/

Keywords

  • Industrial IoT
  • Factory readiness
  • Network traffic characterization
  • Manufacturing industries
  • Industry 4.0

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