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Developing performance measurement system for Internet of Things and smart factory environment

Author

Listed:
  • Gyusun Hwang
  • Jeongcheol Lee
  • Jinwoo Park
  • Tai-Woo Chang

Abstract

To cope with large fluctuations in the demand of a commodity, it is necessary for the manufacturing system to have rapid reactive ability. This requirement may be secured by performance measurement. Although manufacturing companies have used information systems to manage performance, there has been the difficulty of capturing real-time data to depict real situations. The recent development and application of the Internet of Things (IoT) has enabled the resolution of this problem. In demonstration of the functionality of IoT, we developed an IoT-based performance model consistent with the ISA-95 and ISO-22400 standards, which define manufacturing processes and performance indicator formulas. The development comprised three steps: (1) Selection of the Key Performance Indicators of the Overall Equipment Effectiveness (OEE), and the development of an IoT-based production performance model, (2) Implementation of the IoT-based architecture and performance measurement process using Business Process Modelling and (3) Validation of the proposed model through virtual factory simulation. We investigated the effect of the IoT-workability on the OEE, based on the final results of the simulation, both for the planned and actual productions. The simulation results showed that the proposed model represented the timestamp data acquired by IoT and captured the entire production process, thus enabling the determination of real-time performance indicators.

Suggested Citation

  • Gyusun Hwang & Jeongcheol Lee & Jinwoo Park & Tai-Woo Chang, 2017. "Developing performance measurement system for Internet of Things and smart factory environment," International Journal of Production Research, Taylor & Francis Journals, vol. 55(9), pages 2590-2602, May.
    • Handle: RePEc:taf:tprsxx:v:55:y:2017:i:9:p:2590-2602
    DOI: 10.1080/00207543.2016.1245883
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    Citations

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    Cited by:

    1. Delgosha, Mohammad Soltani & Hajiheydari, Nastaran & Talafidaryani, Mojtaba, 2022. "Discovering IoT implications in business and management: A computational thematic analysis," Technovation, Elsevier, vol. 118(C).
    2. Jonghyuk Kim & Hyunwoo Hwangbo, 2019. "Real-Time Early Warning System for Sustainable and Intelligent Plastic Film Manufacturing," Sustainability, MDPI, vol. 11(5), pages 1-13, March.
    3. Jeongcheol Lee & Sungbum Jun & Tai-Woo Chang & Jinwoo Park, 2017. "A Smartness Assessment Framework for Smart Factories Using Analytic Network Process," Sustainability, MDPI, vol. 9(5), pages 1-15, May.
    4. Thi Kim Tuoi, Truong & Van Toan, Nguyen & Ono, Takahito, 2022. "Self-powered wireless sensing system driven by daily ambient temperature energy harvesting," Applied Energy, Elsevier, vol. 311(C).
    5. Hyun-Lim Yang & Tai-Woo Chang & Yerim Choi, 2018. "Exploring the Research Trend of Smart Factory with Topic Modeling," Sustainability, MDPI, vol. 10(8), pages 1-15, August.
    6. Anis Ur Rehman & Mazhar Abbas & Faraz Ahmad Abbasi & Shoaib Khan, 2023. "How Tourist Experience Quality, Perceived Price Reasonableness and Regenerative Tourism Involvement Influence Tourist Satisfaction: A Study of Ha’il Region, Saudi Arabia," Sustainability, MDPI, vol. 15(2), pages 1-27, January.
    7. Priyanshu Kumar Singh & R. Maheswaran & Naveen Virmani & Rakesh D. Raut & Kamalakanta Muduli, 2023. "Prioritizing the Solutions to Overcome Lean Six Sigma 4.0 Challenges in SMEs: A Contemporary Research Framework to Enhance Business Operations," Sustainability, MDPI, vol. 15(4), pages 1-19, February.
    8. Qian Long Kweh & Wen-Min Lu & Fengyi Lin & Yung-Jr Deng, 2022. "Impact of research and development tax credits on the innovation and operational efficiencies of Internet of things companies in Taiwan," Annals of Operations Research, Springer, vol. 315(2), pages 1217-1241, August.
    9. Leogrande, Angelo, 2021. "The Destruction of Price-Representativeness," MPRA Paper 111239, University Library of Munich, Germany.
    10. de Villiers, Charl & Kuruppu, Sanjaya & Dissanayake, Dinithi, 2021. "A (new) role for business – Promoting the United Nations’ Sustainable Development Goals through the internet-of-things and blockchain technology," Journal of Business Research, Elsevier, vol. 131(C), pages 598-609.
    11. Rita Martinho & Jéssica Lopes & Diogo Jorge & Luís Caldas de Oliveira & Carlos Henriques & Paulo Peças, 2022. "IoT Based Automatic Diagnosis for Continuous Improvement," Sustainability, MDPI, vol. 14(15), pages 1-28, August.
    12. 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.
    13. Zhan Shi & Yongping Xie & Wei Xue & Yong Chen & Liuliu Fu & Xiaobo Xu, 2020. "Smart factory in Industry 4.0," Systems Research and Behavioral Science, Wiley Blackwell, vol. 37(4), pages 607-617, July.
    14. Mitsuhiro Fukuzawa & Ryosuke Sugie & Youngwon Park & Jin Shi, 2022. "An Exploratory Case Study on the Metrics and Performance of IoT Investment in Japanese Manufacturing Firms," Sustainability, MDPI, vol. 14(5), pages 1-21, February.

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