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The internet of things for smart manufacturing: A review

Author

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  • Hui Yang
  • Soundar Kumara
  • Satish T.S. Bukkapatnam
  • Fugee Tsung

Abstract

The modern manufacturing industry is investing in new technologies such as the Internet of Things (IoT), big data analytics, cloud computing and cybersecurity to cope with system complexity, increase information visibility, improve production performance, and gain competitive advantages in the global market. These advances are rapidly enabling a new generation of smart manufacturing, i.e., a cyber-physical system tightly integrating manufacturing enterprises in the physical world with virtual enterprises in cyberspace. To a great extent, realizing the full potential of cyber-physical systems depends on the development of new methodologies on the Internet of Manufacturing Things (IoMT) for data-enabled engineering innovations. This article presents a review of the IoT technologies and systems that are the drivers and foundations of data-driven innovations in smart manufacturing. We discuss the evolution of internet from computer networks to human networks to the latest era of smart and connected networks of manufacturing things (e.g., materials, sensors, equipment, people, products, and supply chain). In addition, we present a new framework that leverages IoMT and cloud computing to develop a virtual machine network. We further extend our review to IoMT cybersecurity issues that are of paramount importance to businesses and operations, as well as IoT and smart manufacturing policies that are laid out by governments around the world for the future of smart factory. Finally, we present the challenges and opportunities arising from IoMT. We hope this work will help catalyze more in-depth investigations and multi-disciplinary research efforts to advance IoMT technologies.

Suggested Citation

  • Hui Yang & Soundar Kumara & Satish T.S. Bukkapatnam & Fugee Tsung, 2019. "The internet of things for smart manufacturing: A review," IISE Transactions, Taylor & Francis Journals, vol. 51(11), pages 1190-1216, November.
    • Handle: RePEc:taf:uiiexx:v:51:y:2019:i:11:p:1190-1216
    DOI: 10.1080/24725854.2018.1555383
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    Cited by:

    1. Mingxing Li & Ray Y. Zhong & Ting Qu & George Q. Huang, 2022. "Spatial–temporal out-of-order execution for advanced planning and scheduling in cyber-physical factories," Journal of Intelligent Manufacturing, Springer, vol. 33(5), pages 1355-1372, June.
    2. Omar, Yamila M. & Minoufekr, Meysam & Plapper, Peter, 2019. "Business analytics in manufacturing: Current trends, challenges and pathway to market leadership," Operations Research Perspectives, Elsevier, vol. 6(C).
    3. Ragosebo Kgaugelo Modise & Khumbulani Mpofu & Olukorede Tijani Adenuga, 2021. "Energy and Carbon Emission Efficiency Prediction: Applications in Future Transport Manufacturing," Energies, MDPI, vol. 14(24), pages 1-15, December.
    4. Salem Ahmed Alabdali & Salvatore Flavio Pileggi & Dilek Cetindamar, 2023. "Influential Factors, Enablers, and Barriers to Adopting Smart Technology in Rural Regions: A Literature Review," Sustainability, MDPI, vol. 15(10), pages 1-38, May.
    5. Peng Zhan & Shaokun Wang & Jun Wang & Leigang Qu & Kun Wang & Yupeng Hu & Xueqing Li, 2021. "Temporal anomaly detection on IIoT-enabled manufacturing," Journal of Intelligent Manufacturing, Springer, vol. 32(6), pages 1669-1678, August.
    6. Matsumoto, Takao & Chen, Yijun & Nakatsuka, Akihiro & Wang, Qunzhi, 2020. "Research on horizontal system model for food factories: A case study of process cheese manufacturer," International Journal of Production Economics, Elsevier, vol. 226(C).
    7. Olukorede Tijani Adenuga & Khumbulani Mpofu & Ragosebo Kgaugelo Modise, 2022. "Energy–Carbon Emissions Nexus Causal Model towards Low-Carbon Products in Future Transport-Manufacturing Industries," Energies, MDPI, vol. 15(17), pages 1-13, August.
    8. Asadi, Shahla & Nilashi, Mehrbakhsh & Iranmanesh, Mohammad & Hyun, Sunghyup Sean & Rezvani, Azadeh, 2022. "Effect of internet of things on manufacturing performance: A hybrid multi-criteria decision-making and neuro-fuzzy approach," Technovation, Elsevier, vol. 118(C).
    9. Ivanov, Dmitry & Dolgui, Alexandre & Sokolov, Boris, 2022. "Cloud supply chain: Integrating Industry 4.0 and digital platforms in the “Supply Chain-as-a-Service”," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 160(C).
    10. Ye, Zhenggeng & Cai, Zhiqiang & Yang, Hui & Si, Shubin & Zhou, Fuli, 2023. "Joint optimization of maintenance and quality inspection for manufacturing networks based on deep reinforcement learning," Reliability Engineering and System Safety, Elsevier, vol. 236(C).
    11. Sun, Wenqiang & Wang, Qiang & Zhou, Yue & Wu, Jianzhong, 2020. "Material and energy flows of the iron and steel industry: Status quo, challenges and perspectives," Applied Energy, Elsevier, vol. 268(C).
    12. Ye, Zhenggeng & Yang, Hui & Cai, Zhiqiang & Si, Shubin & Zhou, Fuli, 2021. "Performance evaluation of serial-parallel manufacturing systems based on the impact of heterogeneous feedstocks on machine degradation," Reliability Engineering and System Safety, Elsevier, vol. 207(C).
    13. Masoud Zafarzadeh & Magnus Wiktorsson & Jannicke Baalsrud Hauge, 2021. "A Systematic Review on Technologies for Data-Driven Production Logistics: Their Role from a Holistic and Value Creation Perspective," Logistics, MDPI, vol. 5(2), pages 1-32, April.
    14. Miguel Castillo & Roberto Monroy & Rafiq Ahmad, 2024. "Scientometric analysis and systematic review of smart manufacturing technologies applied to the 3D printing polymer material extrusion system," Journal of Intelligent Manufacturing, Springer, vol. 35(1), pages 3-33, January.
    15. Ali Amiri, 2022. "The application grouping problem in Software-as-a-Service (SaaS) networks," Information Technology and Management, Springer, vol. 23(2), pages 125-137, June.
    16. Ronny Seiger & Marco Franceschetti & Barbara Weber, 2023. "An Interactive Method for Detection of Process Activity Executions from IoT Data," Future Internet, MDPI, vol. 15(2), pages 1-31, February.
    17. Rinaldi, Marta & Bottani, Eleonora, 2023. "How did COVID-19 affect logistics and supply chain processes? Immediate, short and medium-term evidence from some industrial fields of Italy," International Journal of Production Economics, Elsevier, vol. 262(C).

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