IEICE Technical Committee Submission System
Conference Paper's Information
Online Proceedings
[Sign in]
Tech. Rep. Archives
 Go Top Page Go Previous   [Japanese] / [English] 

Paper Abstract and Keywords
Presentation 2022-03-29 15:20
Process Division Learning Method for Input-Output Signals of Production Equipment
Daiki Nakahara, Masahiko Shibata, Tsuyoshi Kobayashi (Mitsubishi Electric) MSS2021-79 NLP2021-150
Abstract (in Japanese) (See Japanese page) 
(in English) When a problem occurs at a production line, the cause should be found out immediately. The authors have proposed a predictive method to detect anomalous signal changes caused by production problems. The prediction model is constructed by machine learning of only normal patterns of digital input-output signals with Time Delay Neural Network. In this paper, we report a process division learning method to shorten the learning time and reduce the amount of required training data. With the result of evaluation, we conclude that the proposed method could shorten the learning time and reduce the required training data.
Keyword (in Japanese) (See Japanese page) 
(in English) Factory Automation(FA) / Anomaly Detection / Time Delay Neural Network / Bit Signal / / / /  
Reference Info. IEICE Tech. Rep., vol. 121, no. 443, MSS2021-79, pp. 127-132, March 2022.
Paper # MSS2021-79 
Date of Issue 2022-03-21 (MSS, NLP) 
ISSN Online edition: ISSN 2432-6380
Copyright
and
reproduction
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
Download PDF MSS2021-79 NLP2021-150

Conference Information
Committee MSS NLP  
Conference Date 2022-03-28 - 2022-03-29 
Place (in Japanese) (See Japanese page) 
Place (in English) Online 
Topics (in Japanese) (See Japanese page) 
Topics (in English) MSS, NLP, Work In Progress (MSS only), and etc. 
Paper Information
Registration To MSS 
Conference Code 2022-03-MSS-NLP 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Process Division Learning Method for Input-Output Signals of Production Equipment 
Sub Title (in English)  
Keyword(1) Factory Automation(FA)  
Keyword(2) Anomaly Detection  
Keyword(3) Time Delay Neural Network  
Keyword(4) Bit Signal  
Keyword(5)  
Keyword(6)  
Keyword(7)  
Keyword(8)  
1st Author's Name Daiki Nakahara  
1st Author's Affiliation Mitsubishi Electric Corporation (Mitsubishi Electric)
2nd Author's Name Masahiko Shibata  
2nd Author's Affiliation Mitsubishi Electric Corporation (Mitsubishi Electric)
3rd Author's Name Tsuyoshi Kobayashi  
3rd Author's Affiliation Mitsubishi Electric Corporation (Mitsubishi Electric)
4th Author's Name  
4th Author's Affiliation ()
5th Author's Name  
5th Author's Affiliation ()
6th Author's Name  
6th Author's Affiliation ()
7th Author's Name  
7th Author's Affiliation ()
8th Author's Name  
8th Author's Affiliation ()
9th Author's Name  
9th Author's Affiliation ()
10th Author's Name  
10th Author's Affiliation ()
11th Author's Name  
11th Author's Affiliation ()
12th Author's Name  
12th Author's Affiliation ()
13th Author's Name  
13th Author's Affiliation ()
14th Author's Name  
14th Author's Affiliation ()
15th Author's Name  
15th Author's Affiliation ()
16th Author's Name  
16th Author's Affiliation ()
17th Author's Name  
17th Author's Affiliation ()
18th Author's Name  
18th Author's Affiliation ()
19th Author's Name  
19th Author's Affiliation ()
20th Author's Name  
20th Author's Affiliation ()
Speaker Author-1 
Date Time 2022-03-29 15:20:00 
Presentation Time 25 minutes 
Registration for MSS 
Paper # MSS2021-79, NLP2021-150 
Volume (vol) vol.121 
Number (no) no.443(MSS), no.444(NLP) 
Page pp.127-132 
#Pages
Date of Issue 2022-03-21 (MSS, NLP) 


[Return to Top Page]

[Return to IEICE Web Page]


The Institute of Electronics, Information and Communication Engineers (IEICE), Japan