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1. p. 357 Study on Pneumatic Flow Control Algorithm Based on Physics-Informed Bayesian Optimization for Flow Cytometry
Suhwan Choi, Sangho Lee, Seungtaek Kim, Jaehyun Park
DOI: https://doi.org/10.7735/ksmte.2026.35.5.357 |
3. p. 372 Machine-, Workpiece-, and Process-Induced Acoustic Signatures in Turning: Characterization and Random Forest-Based Classification
Seung-Min Lee, Gyu-Min Kim, Chae-Won Kim, Dong-Hyeon Jo, Su-Been Park, Dong-Geon Kim, Seung-Jae Lee, Jung-Hwan Kook, Su-Jin Kim
DOI: https://doi.org/10.7735/ksmte.2026.35.5.372 |
9. p. 420 Two-Layer Productivity Diagnosis–Prescription Methodology Using Manufacturing Data: A Data-Driven Preliminary Stage Toward SME AI Transformation (AX)
Geun Young Kim, Seong Su Park, Joon Saam Yoon, Bok Kyu Lim
DOI: https://doi.org/10.7735/ksmte.2026.35.5.420 |
11. p. 439 Deep Learning–Based Real-Time Tool State Prediction System for Titanium Alloy Machining
Hwi-Hyeop Kim, Wang-Ho Yun, Chul-Min Kim, Mi-Ru Kim
DOI: https://doi.org/10.7735/ksmte.2026.35.5.439 |
13. p. 454 Quality-Variability Prediction in Injection-Molding Processes Using Standardized Manufacturing Data and Time-Series Analysis Based on AI DX FOM Cycle
Doo Won Park, Beom tae Kim, Hwa Seok Keum, Su Young Kim
DOI: https://doi.org/10.7735/ksmte.2026.35.5.454 |
15. p. 472 Development of Economic Weight-Based FOM-OEE Model for Performance Evaluation of Hydraulic Component Machining Processes
Hwa Seog Keum, Doo Won Park, Wan Ho Jeong, Su Young Kim
DOI: https://doi.org/10.7735/ksmte.2026.35.5.472 |