Migration from the traditional to the smart factory in the die-casting industry: Novel process data acquisition and fault detection based on artificial neural network-Reference-Cited by-同舟云学术

Migration from the traditional to the smart factory in the die-casting industry: Novel process data acquisition and fault detection based on artificial neural network

Published:2021-04 Issue: Volume:290 Page:116972
ISSN:0924-0136
Container-title:Journal of Materials Processing Technology
language:en
Short-container-title:Journal of Materials Processing Technology

Author:

Lee Jeongsu,Lee Young Chul,Kim Jeong Tae

Funder

Korea Institute of Industrial Technology

Publisher

Elsevier BV

Subject

Industrial and Manufacturing Engineering,Metals and Alloys,Computer Science Applications,Modeling and Simulation,Ceramics and Composites

Reference19 articles.

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2. High-pressure die-casting: contradictions and challenges;Bonollo;J. Miner. Met. Mater. Soc.,2015

3. SMOTE: synthetic minority over-sampling technique;Chawla;J. Artif. Intell. Res.,2002

4. Process monitoring and fault detection strategies: a review;Das;Int. J. Qual. Reliab. Manag.,2012

5. New classification of defects and imperfections for aluminum alloy castings;Fiorese;Int. J. Metalcast.,2015

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