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2022년 22권 29호 p.1 ~ p.26
Generation of Time-Series Working Patterns for Manufacturing High-Quality Products through Auxiliary Classifier Generative Adversarial Network
Generation of Time-Series Working Patterns for Manufacturing High-Quality Products through Auxiliary Classifier Generative Adversarial Network
Manas Bazarbaev
Tserenpurev Chuluunsaikhan, Hyoseok Oh, Ga-Ae Ryu, Aziz Nasridinov, Kwan-Hee Yoo
- Abstract -
Abstract: Product quality is a major concern in manufacturing. In the metal processing industry, low-quality products must be remanufactured, which requires additional labor, money, and time. Therefore, user-controllable variables for machines and raw material compositions are key factors for ensuring product quality. In this study, we propose a method for generating the time-series working patterns of the control variables for metal-melting induction furnaces and continuous casting machines, thus improving product quality by aiding machine operators. We used an auxiliary classifier generative adversarial network (AC-GAN) model to generate time-series working patterns of two processes depending on product type and additional material data. To check accuracy, the difference between the generated time-series data of the model and the ground truth data was calculated. Specifically, the proposed model results were compared with those of other deep learning models: multilayer perceptron (MLP), convolutional neural network (CNN), long short-term memory (LSTM), and gated recurrent unit (GRU). It was demonstrated that the proposed model outperformed the other deep learning models. Moreover, the proposed method generated different time-series data for different inputs, whereas the other deep learning models generated the same time-series data.
- Key Words -
continuous casting machine, deep learning, induction furnace, time-series working patterns, auxiliary classifier generative adversarial network
continuous casting machine, deep learning, induction furnace, time-series working patterns, auxiliary classifier generative adversarial network
- 논문 구분 -
국외전문학술지
- 사사 정보 -
- Downloads -
sensors-22-00029-v2.pdf