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사출성형 CAE와 기계학습을 활용한 모바일 렌즈의 성형조건 최적화 KCI 등재

Optimization of Molding Conditions for Mobile Lens using Injection Molding CAE and Machine Learning

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한국기계기술학회지 (Journal of the Korean Society of Mechanical Technology)
한국기계기술학회 (Korean Society of Mechanical Technology)
초록

In this paper, to improve the optical quality of aspherical plastic lenses for mobile use, the optimal molding conditions that can minimize the phase difference are derived using injection molding simulation, design of experiments, and machine learning. First, factors affecting the phase difference were derived using the design of the experiment method, and a data set was created using the derived factors, followed by the machine learning process. After predicting the model trained using the generated training data as test data and verifying it with the performance evaluation index, the model with the best predictive performance was the random forest model. Therefore, to derive the optimal molding conditions, random forests were used to predict 10,000 random pieces of data. As a result of applying the derived optimal molding conditions to the injection molding simulation, the phase difference of the lens could be reduced by 8.2%.

저자
  • 이용선(공주대학교) | Lee yong sun
  • 주지용(공주대학교(천안공과대학)) | Ji Yong Joo
  • 임세종(공주대학교) | Sae Jong Lim
  • 이정원(공주대학교 금형설계공학과) | Jung-Won Lee
  • 한성렬(공주대학교) | Han Seong Ryeol Corresponding author