Enhancing Diagnosis of Rotating Elements in Roll-to-Roll Manufacturing Systems through Feature Selection Approach Considering Overlapping Data Density and Distance Analysis
Author:
Lee Haemi1ORCID, Lee Yoonjae1ORCID, Jo Minho1, Nam Sanghoon2, Jo Jeongdai3, Lee Changwoo4ORCID
Affiliation:
1. Department of Mechanical Design and Production Engineering, Konkuk University, 120 Neungdong-ro, Gwangjin-gu, Seoul 05030, Republic of Korea 2. Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA 3. Department of Printed Electronics, Korea Institute of Machinery and Materials, 156, Gajeongbuk-ro, Yuseong-gu, Daejeon 34103, Republic of Korea 4. Department of Mechanical and Aerospace Engineering, Konkuk University, 120 Neungdong-ro, Gwangjin-gu, Seoul 05030, Republic of Korea
Abstract
Roll-to-roll manufacturing systems have been widely adopted for their cost-effectiveness, eco-friendliness, and mass-production capabilities, utilizing thin and flexible substrates. However, in these systems, defects in the rotating components such as the rollers and bearings can result in severe defects in the functional layers. Therefore, the development of an intelligent diagnostic model is crucial for effectively identifying these rotating component defects. In this study, a quantitative feature-selection method, feature partial density, to develop high-efficiency diagnostic models was proposed. The feature combinations extracted from the measured signals were evaluated based on the partial density, which is the density of the remaining data excluding the highest class in overlapping regions and the Mahalanobis distance by class to assess the classification performance of the models. The validity of the proposed algorithm was verified through the construction of ranked model groups and comparison with existing feature-selection methods. The high-ranking group selected by the algorithm outperformed the other groups in terms of training time, accuracy, and positive predictive value. Moreover, the top feature combination demonstrated superior performance across all indicators compared to existing methods.
Funder
Korea Institute for Advancement of Technology National Research Council of Science & Technology
Subject
Electrical and Electronic Engineering,Biochemistry,Instrumentation,Atomic and Molecular Physics, and Optics,Analytical Chemistry
Reference72 articles.
1. Schwartz, E.L., Schwartz, E., and Ober, C. (2023, July 26). Roll to Roll Processing for Flexible Electronics. Researchgate.net. Available online: https://www.researchgate.net/profile/Evan-Schwartz-2/publication/267400209_Roll_to_Roll_Processing_for_Flexible_Electronics/links/55d1d37608ae3dc86a4f30b6/Roll-to-Roll-Processing-for-Flexible-Electronics.pdf. 2. Ng, L.W.T., Lee, S.W., Chang, D.W., Hodgkiss, J.M., and Vak, D. (2022). Organic Photovoltaics’ New Renaissance: Advances Toward Roll-to-Roll Manufacturing of Non-fullerene Acceptor Organic Photovoltaics. Adv. Mater. Technol., 7. 3. Othman, M., Zheng, F., Seeber, A., Chesman, A.S.R., Scully, A.D., Ghiggino, K.P., Gao, M., Etheridge, J., and Angmo, D. (2022). Millimeter-Sized Clusters of Triple Cation Perovskite Enables Highly Efficient and Reproducible Roll-to-Roll Fabricated Inverted Perovskite Solar Cells. Adv. Funct. Mater., 32. 4. Product Integration of Compact Roll-to-Roll Processed Polymer Solar Cell Modules: Methods and Manufacture Using Flexographic Printing, Slot-Die Coating and Rotary Screen Printing;Krebs;J. Mater. Chem.,2010 5. Roll-to-Roll Gravure Printing of Organic Photovoltaic Modules—Insulation of Processing Defects by an Interfacial Layer;Apilo;Prog. Photovolt Res. Appl.,2015
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