NDLI: Prediction of high-risk operation time for new on-the-job training in anthropocentric cell manufacturing system

Content Provider	IEEE Xplore Digital Library
Author	Suksawat, B. Obi, A. Yabuta, D. Umeda, K. Ihara, T.
Copyright Year	2008
Description	Author affiliation: Dept. of Precision Mech., Chuo Univ., Tokyo (Suksawat, B.)
Abstract	This paper aims to propose the core concept of a high-risk operation time prediction based on human cognitive science and information technologies for new OJT using an artificial neural network. The prediction intends to notice an educator who sits in the remote site and alerts him to concentrate on a learnerpsilas operation on the shop floor. The high-risk operation in New OJT is analyzed and integrated into the human tension extent. Then alpha-brain wave, a frequency level of the highest attention to stimulant, of the educator is measured by an electroencephalography in order to investigate educatorpsilas tension extent. The result shows that educatorpsilas tension extent is 60 seconds after stimulation. Finally, the neural network is designed for the prediction of high-risk operation time in new OJT. Twenty eight samples are used for neural network training and experiments during new OJT. The results reveal that the proposed neural network model performs high precision of prediction with 97.65% confidence and all of the predicted high-risk operation times are within the interval of educatorpsilas tension extent.
Starting Page	508
Ending Page	513
File Size	767753
Page Count	6
File Format	PDF
ISBN	9781424414895
DOI	10.1109/DEST.2008.4635139
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-02-26
Publisher Place	Thailand
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Training safety management prediction modelling Biological system modeling anthropocentric system Pressing Artificial neural networks Predictive models Safety safety-ecosystem Computer numerical control neural network
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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