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Paper Abstract and Keywords
Presentation 2025-02-14 15:10
AI-based prediction of defects in plastic injection molding
Daiki Kishita (SIST), Yuki Aratsu (i Co., Ltd.), Atsushi Togashi (SIST), Shoichi Noguchi (SFAIS) SWIM2024-26
Abstract (in Japanese) (See Japanese page) 
(in English) Injection molding is a crucial manufacturing process, but defects are a problem. This study aims to predict defects in injection molding using AI technology. Various models, including Random Forest, OneClassSVM, Isolation Forest, Ridge Regression, Decision Tree, NN, and AE, were evaluated. Ridge Regression, Decision Tree, and NN had high recall but low precision. AE improved both precision and recall, but overfitting was observed. Future work requires improving data balance and hyperparameter adjustments.
Keyword (in Japanese) (See Japanese page) 
(in English) defect prediction / cause analysis / / / / / /  
Reference Info. IEICE Tech. Rep., vol. 124, no. 371, SWIM2024-26, pp. 48-54, Feb. 2025.
Paper # SWIM2024-26 
Date of Issue 2025-02-07 (SWIM) 
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 SWIM2024-26

Conference Information
Committee SWIM  
Conference Date 2025-02-14 - 2025-02-14 
Place (in Japanese) (See Japanese page) 
Place (in English) Online (Zoom) 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Business Valuation and Reliability,Student Session,GeneralBusiness Valuation and Reliability,Student Session,GeneralBusiness Valuation and Reliability,Student Session,GeneralBusiness Valuation and Reliability,Student Session,General 
Paper Information
Registration To SWIM 
Conference Code 2025-02-SWIM 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) AI-based prediction of defects in plastic injection molding 
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Keyword(1) defect prediction  
Keyword(2) cause analysis  
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1st Author's Name Daiki Kishita  
1st Author's Affiliation Shizuoka Institute of Science and Technology (SIST)
2nd Author's Name Yuki Aratsu  
2nd Author's Affiliation Ai Kogyo Co., Ltd. (i Co., Ltd.)
3rd Author's Name Atsushi Togashi  
3rd Author's Affiliation Shizuoka Institute of Science and Technology (SIST)
4th Author's Name Shoichi Noguchi  
4th Author's Affiliation Sendai Foundation for Applied Information Sciences (SFAIS)
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Speaker Author-1 
Date Time 2025-02-14 15:10:00 
Presentation Time 30 minutes 
Registration for SWIM 
Paper # SWIM2024-26 
Volume (vol) vol.124 
Number (no) no.371 
Page pp.48-54 
#Pages 7 
Date of Issue 2025-02-07 (SWIM) 

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