The recent trends in Industry 4.0 and Internet of Things have encour-aged many factory managers to improve inspection processes to achieve automa-tion and high detection rates.However,the corresponding cost results of...The recent trends in Industry 4.0 and Internet of Things have encour-aged many factory managers to improve inspection processes to achieve automa-tion and high detection rates.However,the corresponding cost results of sample tests are still used for quality control.A low-cost automated optical inspection system that can be integrated with production lines to fully inspect products with-out adjustments is introduced herein.The corresponding mechanism design enables each product to maintain afixed position and orientation during inspec-tion to accelerate the inspection process.The proposed system combines image recognition and deep learning to measure the dimensions of the thread and iden-tify its defects within 20 s,which is lower than the production-line productivity per 30 s.In addition,the system is designed to be used for monitoring production lines and equipment status.The dimensional tolerance of the proposed system reaches 0.012 mm,and a 100%accuracy is achieved in terms of the defect reso-lution.In addition,an attention-based visualization approach is utilized to verify the rationale for the use of the convolutional neural network model and identify the location of thread defects.展开更多
Electronic devices require the printed circuit board(PCB)to support the whole structure,but the assembly of PCBs suffers from welding problem of the electronic components such as surface mounted devices(SMDs)resistors...Electronic devices require the printed circuit board(PCB)to support the whole structure,but the assembly of PCBs suffers from welding problem of the electronic components such as surface mounted devices(SMDs)resistors.The automated optical inspection(AOI)machine,widely used in industrial production,can take the image of PCBs and examine the welding issue.However,the AOI machine could commit false negative errors and dedicated technicians have to be employed to pick out those misjudged PCBs.This paper proposes a machine learning based method to improve the accuracy of AOI.In particular,we propose an adjacent pixel RGB value based method to pre-process the image from the AOI machine and build a customized deep learning model to classify the image.We present a practical scheme including two machine learning procedures to mitigate AOI errors.We conduct experiments with the real dataset from a production line for three months,the experimental results show that our method can reduce the rate of misjudgment from 0.3%–0.5%to 0.02%–0.03%,which is meaningful for thousands of PCBs each containing thousands of electronic components in practice.展开更多
The growing demand for electronic devices, smart devices, and the Internet of Things constitutes the primary driving force for marching down the path of decreased critical dimension and increased circuit intricacy of ...The growing demand for electronic devices, smart devices, and the Internet of Things constitutes the primary driving force for marching down the path of decreased critical dimension and increased circuit intricacy of integrated circuits. However, as sub-10 nm high-volume manufacturing is becoming the mainstream, there is greater awareness that defects introduced by original equipment manufacturer components impact yield and manufacturing costs. The identification, positioning, and classification of these defects, including random particles and systematic defects, are becoming more and more challenging at the 10 nm node and beyond.Very recently, the combination of conventional optical defect inspection with emerging techniques such as nanophotonics, optical vortices, computational imaging, quantitative phase imaging, and deep learning is giving the field a new possibility. Hence, it is extremely necessary to make a thorough review for disclosing new perspectives and exciting trends, on the foundation of former great reviews in the field of defect inspection methods. In this article, we give a comprehensive review of the emerging topics in the past decade with a focus on three specific areas:(a) the defect detectability evaluation,(b) the diverse optical inspection systems,and(c) the post-processing algorithms. We hope, this work can be of importance to both new entrants in the field and people who are seeking to use it in interdisciplinary work.展开更多
With the rapid development of information technologies such as digital twin, extended reality, and blockchain,the hype around "metaverse" is increasing at astronomical speed. However, much attention has been...With the rapid development of information technologies such as digital twin, extended reality, and blockchain,the hype around "metaverse" is increasing at astronomical speed. However, much attention has been paid to its entertainment and social functions. Considering the openness and interoperability of metaverses, the market of quality inspection promises explosive growth. In this paper, taking advantage of metaverses, we first propose the concept of Automated Quality Inspection(Auto QI), which performs integrated inspection covering the entire manufacturing process, including Quality of Materials, Quality of Manufacturing(Qo M), Quality of Products, Quality of Processes(Qo P), Quality of Systems, and Quality of Services(Qo S). Based on the scenarios engineering theory, we discuss how to perform interactions between metaverses and the physical world for virtual design instruction and physical validation feedback. Then we introduce a bottomup inspection device development workflow with productivity tools offered by metaverses, making development more effective and efficient than ever. As the core of quality inspection,we propose Quality Transformers to complete detection task,while federated learning is integrated to regulate data sharing.In summary, we point out the development directions of quality inspection under metaverse tide.展开更多
High precision manufacturing, e.g. milling and grinding, which have manufacturing tolerances in the range of <10 μm require microscopic measurement techniques for the inspection of the manufactured components. The...High precision manufacturing, e.g. milling and grinding, which have manufacturing tolerances in the range of <10 μm require microscopic measurement techniques for the inspection of the manufactured components. These measurement techniques are very sensitive to cooling liquids and lubricants which are essential for many manufacturing processes. Therefore, the measurement of the components is usually conducted in separate and clean laboratories and not directly in the manufacturing machine. This approach has some major drawbacks, e.g. high time consumption and no possibility for online process monitoring. In this article, a novel concept for the integration of high precision optical topography measurement systems into the manufacturing machine is introduced and compared to other concepts. The introduced concept uses a reservoir with cooling liquid in which the measurement object is immersed during the measurement. Thereby, measurement disturbance by splashing cooling liquids and lubricants can effectively be avoided.展开更多
Flexible electronics such as mechanically compliant displays,sensors and solar cells,have important applications in the fields of energy,national defence and biomedicine,etc.Various types of flexible electronics have ...Flexible electronics such as mechanically compliant displays,sensors and solar cells,have important applications in the fields of energy,national defence and biomedicine,etc.Various types of flexible electronics have been proposed or developed by the improvements in structural designs,material properties and device integrations.However,the manufacturing of flexible electronics receives little attention,which limits its mass production and industrialization.The increasing demands on the size,functionality,resolution ratio and reliability of flexible electronics bring several significant challenges in their manufacturing processes.This work aims to report the state-of-art technologies and applications of flexible electronics manufacturing.Three key technologies including electrohydrodynamic direct-writing,flip chip and automatic optical inspection are highlighted.The mechanism and developments of these technologies are discussed in detail.Based on these technologies,the present work develops three kinds of manufacturing equipment,i.e.,inkjet printing manufacturing equipment,robotized additive manufacturing equipment,and roll-to-roll manufacturing equipment.The advanced manufacturing processes,equipment and systems for flexible electronics pave the way for applications of new displays,smart sensing skins and epidermal electronics,etc.By reviewing the developments of flexible electronics manufacturing technology and equipment,it can be found that the existing advances greatly promote the applications and commercialization of flexible electronics.Since flexible electronics manufacturing contains many multi-disciplinary problems,the current investigations are confronted with great challenges.Therefore,further developments of the reviewed manufacturing technology and equipment are necessary to break the current limitations of manufacturing resolution,efficiency and reliability.展开更多
基金supported partially by the Ministry of Science and Technology,Taiwan,under contracts MOST-110-2634-F-009-024,109-2218-E-150-002,and 109-2218-E-005-015.
文摘The recent trends in Industry 4.0 and Internet of Things have encour-aged many factory managers to improve inspection processes to achieve automa-tion and high detection rates.However,the corresponding cost results of sample tests are still used for quality control.A low-cost automated optical inspection system that can be integrated with production lines to fully inspect products with-out adjustments is introduced herein.The corresponding mechanism design enables each product to maintain afixed position and orientation during inspec-tion to accelerate the inspection process.The proposed system combines image recognition and deep learning to measure the dimensions of the thread and iden-tify its defects within 20 s,which is lower than the production-line productivity per 30 s.In addition,the system is designed to be used for monitoring production lines and equipment status.The dimensional tolerance of the proposed system reaches 0.012 mm,and a 100%accuracy is achieved in terms of the defect reso-lution.In addition,an attention-based visualization approach is utilized to verify the rationale for the use of the convolutional neural network model and identify the location of thread defects.
基金The work was supported by National Key Research and Development Program of China(2020YFB1708700)the National Natural Science Foundation of China(Grant Nos.61922055,61872233,61829201,61532012,61325012,61428205).
文摘Electronic devices require the printed circuit board(PCB)to support the whole structure,but the assembly of PCBs suffers from welding problem of the electronic components such as surface mounted devices(SMDs)resistors.The automated optical inspection(AOI)machine,widely used in industrial production,can take the image of PCBs and examine the welding issue.However,the AOI machine could commit false negative errors and dedicated technicians have to be employed to pick out those misjudged PCBs.This paper proposes a machine learning based method to improve the accuracy of AOI.In particular,we propose an adjacent pixel RGB value based method to pre-process the image from the AOI machine and build a customized deep learning model to classify the image.We present a practical scheme including two machine learning procedures to mitigate AOI errors.We conduct experiments with the real dataset from a production line for three months,the experimental results show that our method can reduce the rate of misjudgment from 0.3%–0.5%to 0.02%–0.03%,which is meaningful for thousands of PCBs each containing thousands of electronic components in practice.
基金funded by the National Natural Science Foundation of China(Grant Nos.52175509 and 52130504)the National Key Research and Development Program of China(2017YFF0204705)+1 种基金the Key Research and Development Plan of Hubei Province(2021BAA013)the National Science and Technology Major Project(2017ZX02101006-004)。
文摘The growing demand for electronic devices, smart devices, and the Internet of Things constitutes the primary driving force for marching down the path of decreased critical dimension and increased circuit intricacy of integrated circuits. However, as sub-10 nm high-volume manufacturing is becoming the mainstream, there is greater awareness that defects introduced by original equipment manufacturer components impact yield and manufacturing costs. The identification, positioning, and classification of these defects, including random particles and systematic defects, are becoming more and more challenging at the 10 nm node and beyond.Very recently, the combination of conventional optical defect inspection with emerging techniques such as nanophotonics, optical vortices, computational imaging, quantitative phase imaging, and deep learning is giving the field a new possibility. Hence, it is extremely necessary to make a thorough review for disclosing new perspectives and exciting trends, on the foundation of former great reviews in the field of defect inspection methods. In this article, we give a comprehensive review of the emerging topics in the past decade with a focus on three specific areas:(a) the defect detectability evaluation,(b) the diverse optical inspection systems,and(c) the post-processing algorithms. We hope, this work can be of importance to both new entrants in the field and people who are seeking to use it in interdisciplinary work.
基金supported by Optima Collaborative Research Project of Defect Detection Algorithm for Automated Optical Inspection±Phase IIthe Key-Area Research and Development Program of Guangdong Province(2020B0909050001,2020B090921003)the Natural Science Foundation of Hebei Province(2021402011)。
文摘With the rapid development of information technologies such as digital twin, extended reality, and blockchain,the hype around "metaverse" is increasing at astronomical speed. However, much attention has been paid to its entertainment and social functions. Considering the openness and interoperability of metaverses, the market of quality inspection promises explosive growth. In this paper, taking advantage of metaverses, we first propose the concept of Automated Quality Inspection(Auto QI), which performs integrated inspection covering the entire manufacturing process, including Quality of Materials, Quality of Manufacturing(Qo M), Quality of Products, Quality of Processes(Qo P), Quality of Systems, and Quality of Services(Qo S). Based on the scenarios engineering theory, we discuss how to perform interactions between metaverses and the physical world for virtual design instruction and physical validation feedback. Then we introduce a bottomup inspection device development workflow with productivity tools offered by metaverses, making development more effective and efficient than ever. As the core of quality inspection,we propose Quality Transformers to complete detection task,while federated learning is integrated to regulate data sharing.In summary, we point out the development directions of quality inspection under metaverse tide.
文摘High precision manufacturing, e.g. milling and grinding, which have manufacturing tolerances in the range of <10 μm require microscopic measurement techniques for the inspection of the manufactured components. These measurement techniques are very sensitive to cooling liquids and lubricants which are essential for many manufacturing processes. Therefore, the measurement of the components is usually conducted in separate and clean laboratories and not directly in the manufacturing machine. This approach has some major drawbacks, e.g. high time consumption and no possibility for online process monitoring. In this article, a novel concept for the integration of high precision optical topography measurement systems into the manufacturing machine is introduced and compared to other concepts. The introduced concept uses a reservoir with cooling liquid in which the measurement object is immersed during the measurement. Thereby, measurement disturbance by splashing cooling liquids and lubricants can effectively be avoided.
基金supported by the National Key Research and Development Program of China(Grant No.2018YFA0703200)the National Natural Science Foundation of China(Grant Nos.51820105008 and 52188102)。
文摘Flexible electronics such as mechanically compliant displays,sensors and solar cells,have important applications in the fields of energy,national defence and biomedicine,etc.Various types of flexible electronics have been proposed or developed by the improvements in structural designs,material properties and device integrations.However,the manufacturing of flexible electronics receives little attention,which limits its mass production and industrialization.The increasing demands on the size,functionality,resolution ratio and reliability of flexible electronics bring several significant challenges in their manufacturing processes.This work aims to report the state-of-art technologies and applications of flexible electronics manufacturing.Three key technologies including electrohydrodynamic direct-writing,flip chip and automatic optical inspection are highlighted.The mechanism and developments of these technologies are discussed in detail.Based on these technologies,the present work develops three kinds of manufacturing equipment,i.e.,inkjet printing manufacturing equipment,robotized additive manufacturing equipment,and roll-to-roll manufacturing equipment.The advanced manufacturing processes,equipment and systems for flexible electronics pave the way for applications of new displays,smart sensing skins and epidermal electronics,etc.By reviewing the developments of flexible electronics manufacturing technology and equipment,it can be found that the existing advances greatly promote the applications and commercialization of flexible electronics.Since flexible electronics manufacturing contains many multi-disciplinary problems,the current investigations are confronted with great challenges.Therefore,further developments of the reviewed manufacturing technology and equipment are necessary to break the current limitations of manufacturing resolution,efficiency and reliability.
