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In today’s rapidly evolving semiconductor industry, ensuring both precision and efficiency in manufacturing has become an increasing challenge, particularly as advanced technologies like MEMS and AI chips push the boundaries of design and production. Inspection methods that were once sufficient are now falling short, making room for cutting-edge solutions powered by artificial intelligence (AI). The introduction of AI-driven 3D X-ray inspection technologies is transforming the landscape, offering manufacturers a sophisticated tool to ensure quality control, while driving sustainable production strategies.SEMI spoke with, Joscha Malin, Product Manager, and Daniel Stickler, R D Expert for X-ray Imaging at Comet AG, Industrial X-Ray System Division, to explore how AI-powered 3D X-ray inspection technologies are shaping manufacturing. They delve into how these technologies address critical challenges during inspections and defect analysis, using tools such as Dragonfly 3D World software for user-friendly, AI-driven insights that facilitate effective decision-making.Further insights into the application of AI-powered 3D X-ray inspection technologies and their role in advancing MEMS manufacturing will be presented by Stickler at the SEMI MEMS Imaging Sensors Summit on November 14, 2024, in Munich, Germany. Registration is now open.SEMI: Thank you both for agreeing to share your insights. To start, can you explain the importance of inspection strategies in the context of MEMS manufacturing?Malin: As MEMS devices become increasingly miniaturized and complex, effective inspection strategies are crucial. These strategies not only accelerate the wrap-up of production processes, but also significantly enhance product yield. With tighter tolerances and various materials involved, ensuring the integrity and functionality of each component is more critical than ever. A robust inspection strategy allows us to catch potential defects early, which can save time and costs associated with rework or scrap.Stickler: The evolution of MEMS technology, particularly in AI chips, demands a higher level of inspection sophistication. Traditional methods may fall short in providing the necessary detail and speed, which is why we’re focusing on advanced solutions like our AI-powered 3D X-ray inspection.SEMI: Could you elaborate on how the 3D X-ray technology differs from conventional inspection methods? Stickler: The 3D X-ray technology we utilize acts as a bridge between traditional optical methods and standard 2D X-ray inspection. It offers high-resolution, three-dimensional images without damaging the samples. 3D X-ray technology emphasizes three main benefits: clarity, efficiency, and actionable insights. This means we can obtain detailed images that help us analyze components more effectively, allowing for real-time decision-making.Malin: Moreover, the clarity and detail provided by the 3D X-ray images are critical when it comes to defect analysis in MEMS devices. They allow us to assess mechanical, electrical, and assembly errors in ways that conventional methods simply cannot. This leads to a more reliable production process.SEMI: What specific MEMS defects can be effectively analyzed using this technology?Stickler: There are several types of defects we can analyze. For instance, we can detect mechanical defects such as stiction or fractures, as well as electrical failures like short circuits. The 3D X-ray inspection allows us to visualize these defects in detail. Additionally, we can monitor assembly errors, which are particularly important in complex MEMS devices where misalignments can lead to significant issues.Malin: I’d like to add that early detection of these defects is paramount. The faster we identify issues, the quicker we can implement corrective actions, thereby improving overall yield and reducing production costs.SEMI: You mentioned yield improvement earlier. Can you explain how your technology contributes to that?Malin: Our approach supports process optimization by providing information on product characteristics and, for example, allows us to identify trends early on that may lead to yield issues later. We also aim to accelerate new product introduction in the early phase by rapid feedback, saving time and cost. This is crucial because many defects may not be apparent until later stages of production. With our technology, we can monitor samples in real-time, allowing us to react promptly to emerging challenges.Stickler: By integrating this feedback loop, we can significantly shorten the time to market for new products. This is particularly beneficial in industries where speed and efficiency are essential.SEMI: Can you tell us about Dragonfly 3D World software and its role in this process?Malin: Dragonfly 3D World is a user-friendly software that leverages AI and, specifically, deep learning for image processing. It enables users to efficiently perform bump metrology and defect identification, for example, without needing extensive expertise in the field. The software makes complex processes manageable, even for operators who may not be specialists in image processing.Stickler: Beside MEMS and advanced packaging in GPU production, this software is indeed an “AI-for-AI” application. By utilizing deep learning, users can train models that adapt to various imaging tasks, making the entire inspection process more efficient. The insights generated from the 3D X-ray images are automated, enhancing usability and streamlining workflows.SEMI: In conclusion, what are the key takeaways you’d like to share?Malin: The key takeaways are that AI-driven 3D X-ray inspection is transformative for the MEMS manufacturing process, enhancing inspection strategies and defect detection significantly. By integrating advanced technologies, we can ensure higher product quality and efficiency.Stickler: Yes, and I would emphasize the importance of powerful monitoring and non-destructive test tools. Our innovative solutions not only improve yield, but also pave the way for sustainable practices in manufacturing, ultimately benefiting the industry. Dr. Daniel SticklerDirector X-ray Technology Components at Comet AG, Industrial X-Ray System Division. Based in Hamburg, Germany, he holds a PhD in Physics from the University of Hamburg and has extensive experience in X-ray imaging, semiconductor X-ray applications and product innovations. Joscha MalinDirector Product Marketing Software Products at Comet AG, Industrial X-Ray System Division. Based in Hamburg, Germany, he holds a degree in Electrical Engineering with specialization in Semiconductors and profound experience in the industry. For over a decade, he has focused on developing X-ray inspection and metrology solutions, especially for the Semiconductor industry. SEMI ContactSitong He / Communications Manager, SEMI EuropeEmail: [email protected]: +49 151 5546 2638
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The SEMI Smart Manufacturing Americas Chapter, a key driver of the Global Smart Manufacturing Initiative, accelerates awareness of digital and data-driven strategies and implementations to help speed adoption of smart manufacturing. In 2021, the Chapter will focus on expanding its work across the industry to include academic and research initiatives. The semiconductor industry saw an unprecedented focus on improving digital monitoring of manufacturing activity in 2020, partially due to COVID-19. The Americas Chapter shared case studies on new tools and techniques for social distancing in fabs, aides for remote maintenance, and tips for remote workers. The Chapter also introduced its three pillars of Sensing, Connecting and Predicting and offered related programs. The Global Smart Manufacturing Conference (GSMC) highlighted the significance of universities and research institutions in the development of smart manufacturing with their focus on joint research for broad dissemination. To help drive smart manufacturing advances, at GSMC several offered non-proprietary tutorials on topic including the following: Integrating sensors for acquisition – CEA-Leti Applying new AI and ML tools and strategies to manufacturing – Binghamton University Digital tools for planning, qualifying and management and scheduling in fabs – MINES Saint-Étienne. Adding AI tools to robot work in a smart factory – KAIST Institutes By continuously highlighting the activities of these and other institutions through presentations, interviews, articles and blog posts, we will draw more attention to what is on the horizon for smart manufacturing in 2021. The SEMI Smart Manufacturing Americas Chapter also plans to elevate activities important to the Outsourced Semiconductor Assembly and Test (OSAT), Surface-Mount Technology (SMT) and Printed Circuit Board Assembly (PCBA) segments of the industry including programs on inspection, traceability and the SEMI SMT-ELS Standard for SMT automation. Thurston Taylor, marketing expert at Tokyo Electron and Vice Chair of the Americas Chapter, notes that “With increasingly more demanding requirements for bump, assembly and test, smart manufacturing and applied data science are necessary to achieve back-end goals now and in the future.” Also, many companies are implementing smart manufacturing applications and assessing various strategies to increase their smart manufacturing capabilities. Members of the Americas Chapter plan to review and develop self-assessment documents and maturity models that apply to front-end wafer fabs all the way through packaging and assembly facilities. “Moving forward it is imperative for all of us to up the intensity on specific ROI vectors such as quality, cost, productivity, sustainability and safety leveraging our smart manufacturing SEMI framework of Sensing, Connecting and Predicting,” said noted Bobby Mitra, worldwide director of Smart Manufacturing at Texas Instruments and Americas Chapter Chair. “By offering special flagship events, invited talks, ROI case-studies and ROI criteria in maturity models, we’ll bring high value to the smart manufacturing industry.” Chapter members also will begin mapping the skills needed to implement and support increasingly digital manufacturing capabilities, including any new skill sets, to help companies develop their hiring, training and management strategies. The mapping effort aims to support companies in building a strong pipeline of employees who can efficiently manage and operate smart manufacturing facilities. For its part, the Americas Chapter’s Go Green Subcommittee will focus on applying smart manufacturing technology to reducing the electronic industry’s carbon footprint by accurately tracking energy waste improving overall fab efficiency. Stay tuned for details on activities planned for our chapters in Europe, China, Japan, Korea, Southeast Asia and Taiwan. To learn more about each chapter and how to get involved, please visit the SEMI Smart Manufacturing Hub and sign up for our newsletter. Ayo Kajopaiye is senior project coordinator, Collaborative Technology Platforms, at SEMI.
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