Applying Industrial Internet of Things Analytics to Manufacturing

被引:2
|
作者
Wu, Chun-Ho [1 ]
Ng, Stephen Chi-Hung [1 ]
Kwok, Keith Chun-Man [2 ]
Yung, Kai-Leung [3 ]
机构
[1] Hang Seng Univ Hong Kong, Dept Supply Chain & Informat Management, Shatin, Hong Kong, Peoples R China
[2] Ka Shui Int Holdings Ltd, Ka Shui Enterprise Acad, Hong Kong, Peoples R China
[3] Hong Kong Polytech Univ, Dept Ind & Syst Engn, Hong Kong, Peoples R China
关键词
industrial Internet of Things; idle time; Industry; 4; 0; data-driven analytics; smart factory;
D O I
10.3390/machines11040448
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The proliferation of Industry 4.0 (I4.0) technologies has created a new manufacturing landscape for manufacturing, requiring that companies follow I4.0 trends to stay competitive. However, in this novel digital automated environment, these companies must also ensure that lean manufacturing principles are upheld. This study proposes a data-driven framework for analysing raw data across machines in manufacturing systems that can provide a comprehensive understanding of idle time and facilitate adjustments to reduce defect rates. This framework offers an alternative approach to improving manufacturing processes that involves utilising the power of I4.0 technologies in conjunction with lean manufacturing principles. This study's examination of unprocessed data also provides guidance on improving legislation. The findings of this study provide direction for future research in the field of manufacturing and offer useful advice to businesses wishing to integrate I4.0 technologies into their operations.
引用
收藏
页数:18
相关论文
共 50 条
  • [1] Manufacturing Analytics and Industrial Internet of Things
    Lade, Prasanth
    Ghosh, Rumi
    Srinivasan, Soundar
    [J]. IEEE INTELLIGENT SYSTEMS, 2017, 32 (03) : 74 - 79
  • [2] Applying Runtime Monitoring to the Industrial Internet of Things
    Grochowski, Marco
    Kowalewski, Stefan
    Buchsbaum, Melanie
    Brecher, Christian
    [J]. 2019 24TH IEEE INTERNATIONAL CONFERENCE ON EMERGING TECHNOLOGIES AND FACTORY AUTOMATION (ETFA), 2019, : 348 - 355
  • [3] Social Internet of Industrial Things for Industrial and Manufacturing Assets
    Li, H.
    Parlikad, A. K.
    [J]. IFAC PAPERSONLINE, 2016, 49 (28): : 208 - 213
  • [4] The role of big data analytics in industrial Internet of Things
    Rehman, Muhammad Habib Ur
    Yaqoob, Ibrar
    Salah, Khaled
    Imran, Muhammad
    Jayaraman, Prem Prakash
    Perera, Charith
    [J]. FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, 2019, 99 : 247 - 259
  • [5] Securing Manufacturing Intelligence for the Industrial Internet of Things
    Al-Aqrabi, Hussain
    Hill, Richard
    Lane, Phil
    Aagela, Hamza
    [J]. FOURTH INTERNATIONAL CONGRESS ON INFORMATION AND COMMUNICATION TECHNOLOGY, VOL 2, 2020, 1027 : 267 - 282
  • [6] A Configurable Distributed Data Analytics Infrastructure for the Industrial Internet of Things
    Kefalakis, Nikos
    Roukounaki, Aikaterini
    Soldatos, John
    [J]. 2019 15TH INTERNATIONAL CONFERENCE ON DISTRIBUTED COMPUTING IN SENSOR SYSTEMS (DCOSS), 2019, : 179 - 181
  • [7] Smart Industrial Internet of Things Framework for Composites Manufacturing
    Chai, Boon Xian
    Gunaratne, Maheshi
    Ravandi, Mohammad
    Wang, Jinze
    Dharmawickrema, Tharun
    Di Pietro, Adriano
    Jin, Jiong
    Georgakopoulos, Dimitrios
    [J]. SENSORS, 2024, 24 (15)
  • [8] Industrial Internet of things over tactile Internet in the context of intelligent manufacturing
    Bai, Yun
    [J]. CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS, 2018, 21 (01): : 869 - 877
  • [9] Industrial Internet of things over tactile Internet in the context of intelligent manufacturing
    Yun Bai
    [J]. Cluster Computing, 2018, 21 : 869 - 877
  • [10] Big data analytics challenges to implementing the intelligent Industrial Internet of Things (IIoT) systems in sustainable manufacturing operations
    Qi, Quansong
    Xu, Zhiyong
    Rani, Pratibha
    [J]. TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE, 2023, 190