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Lee Y, Yun J, Lee S, Lee C. Image Data-Centric Visual Feature Selection on Roll-to-Roll Slot-Die Coating Systems for Edge Wave Coating Defect Detection. Polymers (Basel) 2024; 16:1156. [PMID: 38675075 PMCID: PMC11054432 DOI: 10.3390/polym16081156] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2024] [Revised: 04/16/2024] [Accepted: 04/18/2024] [Indexed: 04/28/2024] Open
Abstract
Roll-to-roll (R2R) manufacturing depends on a system's capability to deposit high-quality coatings with precise thickness, width, and uniformity. Therefore, consistent maintenance requires the immediate and accurate detection of coating defects. This study proposes a primary color selection (PCS) method to detect edge defects in R2R systems. This method addresses challenges associated with training data demands, complexity, and defect adaptability through a vision data-centric approach, ensuring precise edge coating defect detection. Using color information, high accuracy was achieved while minimizing data capacity requirements and processing time. Precise edge detection was facilitated by accurately distinguishing coated and noncoated regions by selecting the primary color channel based on color variability. The PCS method achieved superior accuracy (95.8%), outperforming the traditional weighted sum method (78.3%). This method is suitable for real-time detection in manufacturing systems and mitigates edge coating defects, thus facilitating quality control and production optimization.
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Affiliation(s)
- Yoonjae Lee
- Department of Mechanical Design and Production Engineering, Konkuk University, 120 Neungdong-ro, Gwangjin-gu, Seoul 05029, Republic of Korea; (Y.L.); (J.Y.); (S.L.)
| | - Junyoung Yun
- Department of Mechanical Design and Production Engineering, Konkuk University, 120 Neungdong-ro, Gwangjin-gu, Seoul 05029, Republic of Korea; (Y.L.); (J.Y.); (S.L.)
| | - Sangbin Lee
- Department of Mechanical Design and Production Engineering, Konkuk University, 120 Neungdong-ro, Gwangjin-gu, Seoul 05029, Republic of Korea; (Y.L.); (J.Y.); (S.L.)
| | - Changwoo Lee
- Department of Mechanical Engineering, Konkuk University, 120 Neungdong-ro, Gwangjin-gu, Seoul 05029, Republic of Korea
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Ahn J, Han H, Ha JH, Jeong Y, Jung Y, Choi J, Cho S, Jeon S, Jeong JH, Park I. Micro-/Nanohierarchical Structures Physically Engineered on Surfaces: Analysis and Perspective. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2024; 36:e2300871. [PMID: 37083149 DOI: 10.1002/adma.202300871] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/29/2023] [Revised: 04/06/2023] [Indexed: 05/03/2023]
Abstract
The high demand for micro-/nanohierarchical structures as components of functional substrates, bioinspired devices, energy-related electronics, and chemical/physical transducers has inspired their in-depth studies and active development of the related fabrication techniques. In particular, significant progress has been achieved in hierarchical structures physically engineered on surfaces, which offer the advantages of wide-range material compatibility, design diversity, and mechanical stability, and numerous unique structures with important niche applications have been developed. This review categorizes the basic components of hierarchical structures physically engineered on surfaces according to function/shape and comprehensively summarizes the related advances, focusing on the fabrication strategies, ways of combining basic components, potential applications, and future research directions. Moreover, the physicochemical properties of hierarchical structures physically engineered on surfaces are compared based on the function of their basic components, which may help to avoid the bottlenecks of conventional single-scale functional substrates. Thus, the present work is expected to provide a useful reference for scientists working on multicomponent functional substrates and inspire further research in this field.
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Affiliation(s)
- Junseong Ahn
- Department of Mechanical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, 34141, Republic of Korea
- Department of Nano Manufacturing Technology, Korea Institute of Machinery and Materials (KIMM), Daejeon, 34103, Republic of Korea
| | - Hyeonseok Han
- Department of Mechanical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, 34141, Republic of Korea
| | - Ji-Hwan Ha
- Department of Mechanical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, 34141, Republic of Korea
- Department of Nano Manufacturing Technology, Korea Institute of Machinery and Materials (KIMM), Daejeon, 34103, Republic of Korea
| | - Yongrok Jeong
- Department of Mechanical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, 34141, Republic of Korea
- Department of Nano Manufacturing Technology, Korea Institute of Machinery and Materials (KIMM), Daejeon, 34103, Republic of Korea
| | - Young Jung
- Department of Mechanical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, 34141, Republic of Korea
| | - Jungrak Choi
- Department of Mechanical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, 34141, Republic of Korea
| | - Seokjoo Cho
- Department of Mechanical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, 34141, Republic of Korea
| | - Sohee Jeon
- Department of Nano Manufacturing Technology, Korea Institute of Machinery and Materials (KIMM), Daejeon, 34103, Republic of Korea
| | - Jun-Ho Jeong
- Department of Nano Manufacturing Technology, Korea Institute of Machinery and Materials (KIMM), Daejeon, 34103, Republic of Korea
| | - Inkyu Park
- Department of Mechanical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, 34141, Republic of Korea
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Giordano G, Murali Babu SP, Mazzolai B. Soft robotics towards sustainable development goals and climate actions. Front Robot AI 2023; 10:1116005. [PMID: 37008983 PMCID: PMC10064016 DOI: 10.3389/frobt.2023.1116005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2022] [Accepted: 03/06/2023] [Indexed: 03/19/2023] Open
Abstract
Soft robotics technology can aid in achieving United Nations’ Sustainable Development Goals (SDGs) and the Paris Climate Agreement through development of autonomous, environmentally responsible machines powered by renewable energy. By utilizing soft robotics, we can mitigate the detrimental effects of climate change on human society and the natural world through fostering adaptation, restoration, and remediation. Moreover, the implementation of soft robotics can lead to groundbreaking discoveries in material science, biology, control systems, energy efficiency, and sustainable manufacturing processes. However, to achieve these goals, we need further improvements in understanding biological principles at the basis of embodied and physical intelligence, environment-friendly materials, and energy-saving strategies to design and manufacture self-piloting and field-ready soft robots. This paper provides insights on how soft robotics can address the pressing issue of environmental sustainability. Sustainable manufacturing of soft robots at a large scale, exploring the potential of biodegradable and bioinspired materials, and integrating onboard renewable energy sources to promote autonomy and intelligence are some of the urgent challenges of this field that we discuss in this paper. Specifically, we will present field-ready soft robots that address targeted productive applications in urban farming, healthcare, land and ocean preservation, disaster remediation, and clean and affordable energy, thus supporting some of the SDGs. By embracing soft robotics as a solution, we can concretely support economic growth and sustainable industry, drive solutions for environment protection and clean energy, and improve overall health and well-being.
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Affiliation(s)
- Goffredo Giordano
- Bioinspired Soft Robotics, Istituto Italiano di Tecnologia (IIT), Genova, Italy
- Department of Mechanics Mathematics and Management, Politecnico di Barit, Bari, Italy
- *Correspondence: Goffredo Giordano, , ; Saravana Prashanth Murali Babu, , ; Barbara Mazzolai,
| | - Saravana Prashanth Murali Babu
- SDU Soft Robotics, SDU Biorobotics, The Mærsk McKinney Møller Institute, University of Southern Denmark, Odense, Denmark
- *Correspondence: Goffredo Giordano, , ; Saravana Prashanth Murali Babu, , ; Barbara Mazzolai,
| | - Barbara Mazzolai
- Bioinspired Soft Robotics, Istituto Italiano di Tecnologia (IIT), Genova, Italy
- *Correspondence: Goffredo Giordano, , ; Saravana Prashanth Murali Babu, , ; Barbara Mazzolai,
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