Automatic Discovery of Basic Motion Classification Rules (original) (raw)

Abstract

There is a keen demand for a method of sharing better work practices in a factory because better work practices are the key to improving productivity. We have developed a system that can measure a worker’s motion and automatically generate a manual that describes his movements. This system employs motion study as used in Industrial Engineering to identify the important steps in a job, and it has proven to be effective especially in the fields of factory machine operation and maintenance. However, work procedures often include unique basic motions. The determination of basic motions and the creation of an algorithm that can classify these basic motions are time consuming and complex tasks. Therefore we have employed the C4.5 algorithm to discover rules that classify the basic motions. Experimental results prove that our method can successfully discover rules for various work procedures.

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Authors and Affiliations

  1. Monotsukuri Institute of Technologists, 333 Maeya, Gyoda, 361-0038, Japan
    Satoshi Hori & Mizuho Sasaki
  2. Wakayama University, 930 Sakaedani, Wakayama, 640-8510, Japan
    Hirokazu Taki

Authors

  1. Satoshi Hori
  2. Mizuho Sasaki
  3. Hirokazu Taki

Editor information

Editors and Affiliations

  1. School of Design, Engineering and Computing, Bournemouth University, UK
    Bogdan Gabrys
  2. Centre for SMART Systems, School of Environment and Technology, University of Brighton, BN2 4GJ, Brighton, UK
    Robert J. Howlett
  3. School of Electrical and Information Engineering, Knowledge Based Intelligent Engineering Systems Centre, University of South Australia, SA, 5095, Mawson Lakes, Australia
    Lakhmi C. Jain

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© 2006 Springer-Verlag Berlin Heidelberg

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Hori, S., Sasaki, M., Taki, H. (2006). Automatic Discovery of Basic Motion Classification Rules. In: Gabrys, B., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2006. Lecture Notes in Computer Science(), vol 4252. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11893004\_79

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