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An Analytic Approach for Workers’ Fatigue Examination Using RFID-Enabled Production Data

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LISS 2020

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Abstract

With the advantages of long-distance contactless identification and data storage capacity, the use of radio frequency identification (RFID) technology in the fields of manufacturing, transportation and logistics has been widely reported. Fatigue of workers plays a critical role in impacting the manufacturing efficiency because it reduces productivity and increases accident rates. Therefore, the workers’ fatigue must be well examined and addressed. This paper thus proposes an analytic approach to use RFID captured production data and builds an effective method for mining the structural insight to predict the fatigue trajectory in workplace from a huge number of RFID data which may be full of inaccurate, incomplete and missing records. In this research, realistic processing time is used to measure the workers’ fatigue. Based on a general framework for the fatigue examination, the proposed approach is able to estimate the employees’ fatigue trajectory within designated period of time using RFID-enabled production data. Different genders and shifts are considered to find the key impact factors on fatigue.

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Acknowledgements

We would like to acknowledge the support from Seed Fund for Basic Research in HKU (201906159001), The Knowledge Exchange impact project scheme in Faculty of Engineering, HKU (KE-IP-2019/20-31). Thanks for the data support from Huaiji Dengyun Auto-parts Holding Co Ltd.

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Authors and Affiliations

  1. Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Hong Kong, China

    Yishu Yang & Ray Y. Zhong

Authors
  1. Yishu Yang
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  2. Ray Y. Zhong
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Corresponding author

Correspondence to Ray Y. Zhong .

Editor information

Editors and Affiliations

  1. Beijing Jiaotong University, Beijing, China

    Shifeng Liu

  2. Budapest University of Technology and Economics, Budapest, Hungary

    Gábor Bohács

  3. Beijing Jiaotong University, Beijing, China

    Xianliang Shi

  4. International Center for Informatics Research, Beijing Jiaotong University, Beijing, China

    Xiaopu Shang

  5. Beijing Logistics Informatics Research Base, Beijing Jiaotong University, Beijing, China

    Anqiang Huang

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Yang, Y., Zhong, R.Y. (2021). An Analytic Approach for Workers’ Fatigue Examination Using RFID-Enabled Production Data. In: Liu, S., Bohács, G., Shi, X., Shang, X., Huang, A. (eds) LISS 2020. Springer, Singapore. https://doi.org/10.1007/978-981-33-4359-7_9

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