We will exhibit at the 3rd "Smart Factory EXPO Autumn": showcasing exterior inspection AI, worker analysis AI, and data generation management solutions.

Attention: Improve work efficiency with the automation of image inspection! Easily and high-quality implement good product detection and defective product image generation with AI that provides understandable reasoning.

This is an AI solution designed for the manufacturing industry. It dramatically improves the automation of factory inspection tasks, enhances work efficiency, and increases the accuracy of quality control. It centralizes the generation and management of NG (non-good) data, streamlining the creation and management of AI training data. Additionally, it standardizes the skills required for inspection tasks, achieving skill-less operation. Key Features: - Intuitive operation: No need for AI expertise, easily operable by anyone. - Learning with a small amount of data: Efficient learning enables the quick construction of high-precision models. - Visualization of decision-making rationale: XAI technology clarifies the rationale behind AI decisions, enhancing reliability. - Generation and management of defective product data: Reduces the burden of data collection and optimizes quality control. Target Audience: - Production Management Department: Planning and managing production schedules, improving production efficiency, reducing defective products. - Producers: Optimizing production processes, introducing new technologies, maintaining equipment, utilizing automation technologies. - Quality Control Department: Conducting product quality inspections, detecting and addressing defective products, establishing quality assurance processes, confirming compliance with standards. - DX Promotion Department: Promoting digital transformation, implementing AI, improving operations through data analysis. - Companies that have already introduced image inspection machines and are facing issues with over-detection. *Please contact us for more information.

• Visual Inspection Equipment
• Image Processing Software
• Image analysis software

A must-see for those considering AI implementation! Streamline NG image generation and data management; preprocessing for machine learning has become surprisingly easy!

This is the ideal data management tool for manufacturers considering AI implementation. Preparing AI training data becomes easier, leading to reduced inspection time and lighter workloads. Challenges include: - Complex data management: Organizing image data is difficult, resulting in longer AI training times. - Insufficient NG data: There is a lack of defective product data, which hinders AI accuracy. - Difficult quality control: Data quality is inconsistent, causing variability in inspection results. Implementation is very simple! - Install the tool: Easy setup with cloud provision. - Upload data: Upload existing image data to the tool. - Generate NG samples: Automatically generate the necessary defective product data. - Train AI: Effectively train AI with high-quality data. Also perfect for those who have already implemented visual inspection! - Streamlined data management: Easily integrate and manage current visual inspection data. - Quality improvement: Support for evaluating and enhancing the quality of existing data. - Flexible response: Smooth integration with existing visual inspection AI. - AI validation support: Verify the performance of the AI model after implementation and assist with optimization. For more details, please refer to the 'Related Catalog' and contact us.

• Image analysis software

Understanding the basis and risks of AI's judgments. Capable of learning from a small amount of data. Intuitive operation without the need for AI knowledge. Achieving continuous quality management that does not end with a PoC.

The practical "visual inspection AI" for manufacturing sites allows for high-precision learning and operation from a small amount of data with intuitive operation. It is a user-friendly and effective AI tool for site managers. Target Industries: Manufacturing (semiconductors, foundry, automotive, processed foods) / Chemicals / Pharmaceuticals Target Audience: - Production Management Department: Planning and managing production, improving production efficiency, reducing defective products - Production Technology Department: Optimizing production processes, introducing new technologies, maintaining equipment, utilizing automation technologies - Quality Control Department: Inspecting product quality, detecting and addressing defects, establishing quality assurance processes, confirming compliance with standards - DX Promotion Department: Promoting digital transformation, implementing AI, improving operations through data analysis - Companies that have already introduced image inspection machines and face challenges with over-detection Main Features: - Intuitive operation: No AI knowledge required. Easy from AI model creation to operation and quality management. - Learning from a small amount of data: Domain-specific data augmentation technology generates training data tailored to the on-site environment. - Quality management through visualization: XAI technology visualizes the reasoning behind AI decisions, making model improvement easier. - Quality verification for AI: QAAI enables quality verification of data and models, visualization, and management of change points.

• Visual Inspection Equipment

【FAQ/Glossary】You can understand the overview of the FAQ and terminology related to the introduction of AI for difficult-to-understand visual inspections.

We will organize and provide FAQs and a glossary in an easy-to-understand manner for those considering the introduction of an appearance inspection AI system. This content is essential for companies that have already implemented appearance inspection and those that are considering doing so in the future. The appearance inspection AI system is a powerful tool designed to dramatically improve quality control in manufacturing. Our AI technology utilizes advanced image analysis and machine learning algorithms to detect defective products quickly and accurately. It achieves a highly transparent decision-making process through Explainable AI (XAI) and reliable quality assurance through Quality Assurance AI (QAAI). Furthermore, it can build high-precision models from a small amount of data using data augmentation techniques. It has the flexibility to learn from images taken with various cameras and can adapt to different imaging conditions. It maintains consistent detection accuracy even with images captured in different environments, such as those using rule-based image inspection, significantly improving factory production efficiency.

• Image analysis software

Easy operation even for AI beginners! A next-generation AI platform that realizes factory automation and quality control.

This is an AI platform designed for the manufacturing industry. By using this tool, you can achieve factory automation and labor reduction, while also easily managing quality control. It supports tasks such as visual inspections and analysis of worker behavior with AI, assisting operations on the shop floor. Why it’s good: It offers intuitive operation that can be used without specialized AI knowledge. It can learn from a small amount of data, making implementation easy. Additionally, it incorporates the following advanced technologies: - XAI (Explainable AI): Clarifies the reasoning behind AI decisions, allowing users to understand AI behavior. - QAAI (Quality Assurance AI): Generates data and verifies quality while considering environmental changes and disturbances, providing a stable AI model. Why explainability and robust AI are necessary: In manufacturing environments, it is crucial to understand how AI makes decisions. XAI enhances reliability by making the reasoning behind AI decisions explicit, allowing for safe operation. Furthermore, QAAI provides a robust model capable of responding to disturbances and environmental changes, ensuring stable performance on the shop floor. *For more details, please refer to the "Related Catalog" and contact us.*

• Image analysis software

DX transformation with operator analysis AI: Visualizing work processes and converting "tacit knowledge" into "explicit knowledge." We will streamline and optimize the manufacturing process!

We will clarify the tasks in manufacturing and logistics that are prone to errors and time-consuming, and achieve appropriate personnel placement, training, workload verification, and improvement of work mistakes. To this end, we will promote the digital transformation (DX) of operations, which can enhance productivity and quality. To address issues such as labor shortages and the transmission of skills, we will utilize the "Worker Analysis AI" to smoothly implement the SECI model (Socialization, Externalization, Combination, Internalization), promoting personnel training, efficient work, and knowledge sharing. The "Worker Analysis AI" strengthens corporate competitiveness and supports sustainable growth. **The Necessity of Converting Tacit Knowledge into Explicit Knowledge** In various operations, the experience of skilled workers tends to accumulate as tacit knowledge within individuals. Converting tacit knowledge into explicit knowledge offers the following benefits: - Standardization: Ensures consistency in work procedures and quality. - Efficient Training: Enables rapid training of new employees. - Knowledge Sharing: Shares knowledge across the organization, improving performance. - Risk Mitigation: Reduces risks associated with worker transfers and resignations. - Continuous Improvement: Promotes process improvements, optimizing efficiency and costs. *For more details, please refer to the "Related Catalog" and "Other Materials" and contact us.*

• Image analysis software

Significant efficiency improvements in manual processes with the help of AI! Analyzing work processes from videos of the manufacturing site.

What is Operator Analysis? Operator Analysis AI is an innovative tool that visualizes work on the manufacturing line in real-time and recorded footage, enabling efficient production processes. It can dramatically improve productivity and quality in manufacturing settings through accurate understanding of cycle times, optimization of process flows, improvement of work actions, optimization of personnel allocation, detection of work omissions, and estimation of work loads. Benefits of Work Analysis 1. Remarkable Efficiency - Eliminates waste through detailed analysis of work processes, significantly improving work efficiency. 2. Assurance of Top Quality - Reduces work omissions and errors through consistent procedures, dramatically enhancing product quality. 3. Improved Safety - Monitors work actions in real-time, allowing for early detection and correction of risky behaviors, thereby providing a safe working environment. 4. Cost Reduction - Reduces operational costs by eliminating unnecessary work and duplication, optimizing personnel and resources. Reasons to Choose Our Products We offer AI solutions specialized for the manufacturing industry, with extensive know-how and flexible customization options. We ensure transparency with XAI and QAAI technologies, achieving intuitive operability and rapid implementation. Our pre-validation minimizes risks and guarantees high implementation effectiveness.

• Image analysis software

[For the manufacturing industry] Analyze and compare on-site work using AI video analysis – Identify bottlenecks and dramatically improve work efficiency with IE methods.

The "Operator Analysis AI" visualizes routine work on the manufacturing line using AI, enabling the understanding of cycle times, optimization of process flows, improvement of work actions, optimization of personnel allocation, detection of work omissions, and estimation of work loads. 【Optimal Operations】 - Comparison among operators: Improve consistency and efficiency of work using the ECRS (Eliminate, Combine, Rearrange, Simplify) method. - Creation of manuals: Promote the 3S (Sort, Set in order, Shine) principles. - Continuous operation: Review and optimize the 3M (Muri, Muda, Mura). 【Target Audience】 - Production Technology Department: For those aiming for process improvement and efficiency, promoting TQC (Total Quality Control) methods. - Production Management: For those wanting to accurately grasp cycle times and optimize production flows, supporting KY (Kiken Yochi) activities. - Quality Control: For those aiming to improve quality through the detection of work omissions and estimation of work loads. - DX Promotion Department: For those promoting digital transformation and aiming for work efficiency through IE (Industrial Engineering) methods. - Shipping Management: For those looking to enhance the efficiency and accuracy of the shipping process. You can view actual implementation examples and demos. *For details, please refer to the "Separate Catalog" and contact us.

• Image analysis software

[Free Case Study Available] Discover efficiency improvement points in the assembly processes of the world's six major manufacturers using AI! Results of the comparison between veterans and newcomers included!

Facing significant challenges in the manufacturing industry, Yokogawa Manufacturing Corporation has implemented Copy's work analysis AI, achieving remarkable results. This case study introduces the detailed processes and specific outcomes. 【Challenges Addressed】 1. Personalization of tasks 2. Issues in human resource development and technology transfer 3. Workload of operators 4. Variability in quality 【Some of the Effects of Implementation】 1. Early detection of process anomalies: Using Copy's AI technology, outliers in process cycle times were identified, uncovering process anomalies such as missed preparations for necessary parts. 2. Realization of efficiency: Waiting times for assembly equipment were identified, and efficient cart operations by veteran workers were discovered. The work efficiency of veterans and newcomers was compared, clarifying each group's strengths and areas for improvement. 3. Comparative analysis of workers: The movements of newcomers and veterans were analyzed over approximately 200 cycles, clarifying differences in work efficiency and areas for improvement. Through these initiatives, reductions in work time, improvements in quality consistency, and contributions to human resource development have been achieved, establishing new standards for productivity improvement and quality management across the manufacturing industry. For detailed case studies, specific data, and analysis results, please download and view the "Related Catalog."

• Image analysis software

[Free Case Study Available] Achieving Efficiency and Quality Improvement in Production Sites with AI! Publicizing Asahi Densou's Success Case.

Asahi Denso Co., Ltd. has introduced Confide for Factory to address important challenges faced by the manufacturing industry, achieving remarkable results. This case study presents the detailed process and specific outcomes. 【Challenges Addressed】 - Complexity of paper-based document management - Decrease in data accuracy - Difficulty in grasping real-time progress and quality data - Improvement of operational efficiency 【Some Effects of the Implementation】 - Improved operational efficiency: Reduced data entry effort, resulting in smoother and more accurate work. - Visualization and sharing of information: Real-time information sharing enables effective progress management. - Reduction in working hours: A reduction of work hours equivalent to six people per day. By moving away from paper-based document management and embracing digitalization, transparency in business processes has improved. Employee productivity has significantly increased, and errors and mistakes have decreased. Additionally, communication between departments has become smoother, strengthening the overall cooperation of the team. Confide for Factory is evaluated as an essential tool that supports digital transformation in the manufacturing industry and enhances the overall competitiveness of companies.

• Electronic documents

Sekisui Filler Co., Ltd. will exhibit at the "Automotive Technology Exhibition 2026 YOKOHAMA" held at PACIFICO YOKOHAMA from May 27. (Booth number 285, within the Sekisui Chemical booth) 【Exhibited Products】 Mobility G - Re-sealable gasket HM (EV Seal 500) - Interior materials (Thermonex/Swiftlock) - Battery protection materials (EV Protect 4006SFR, etc.) Electronics / Automotive Electronics - Adhesives for camera modules - Adhesives for displays - Conformal coatings - Optical adhesives We sincerely look forward to your visit.

Dear Sir or Madam, We hope this message finds you well and that your company continues to prosper. FUKUDA will be exhibiting at the 28th INTERPHEX Week Tokyo. At the exhibition, we will be showcasing 100% inspection equipment compliant with Container Closure Integrity Testing (CCIT) standards, as well as sampling inspection machines. We sincerely invite you to visit our booth at this opportunity and would greatly appreciate your attendance despite your busy schedule. Yours sincerely, [Dates] May 20 (Wed) - 22 (Fri), 2026 10:00-17:00 (JST) [Venue] Makuhari Messe, Japan 8 Hall Booth No. 41 - 36

[Instructor] Hiroto Hayashi, Attorney at Law, New York State, Mori Hamada & Matsumoto Law Firm, Foreign Law Joint Enterprise [Key Lecture Content] Recently, batteries are expected to serve as a balancing power source for the realization of renewable energy as a primary power source. Due to changes in the business environment brought about by market development and government support measures, opportunities in the battery business are expanding. For grid-connected batteries, there are multiple options for long-term decarbonization power source auctions, tolling models, and merchant models, and the points of project development vary depending on the offtake method. Additionally, with the spread of the FIP system, the installation of batteries alongside renewable energy generation facilities is also progressing. In this lecture, we will explain the systems related to batteries, as well as key points for contract creation and negotiation, and financing necessary to steadily advance projects. We will also outline the challenges and prospects for project development and project finance formation according to each offtake scheme.

[Lecturer] Hideo Yamada, Ph.D. Honorary Professor, Waseda University Visiting Professor, Business Breakthrough University Graduate School [Key Lecture Content] Companies face various trade-offs (dilemmas) such as quality vs. cost, inventory levels vs. service levels, and standardization vs. differentiation. Traditionally, companies have responded to trade-offs by (1) finding a balance or (2) prioritizing one over the other. However, this does not lead to fundamental solutions. In this lecture, I will propose a third method that is neither balancing nor prioritizing. Using case studies from over 50 Japanese companies, I will explain it in an easy-to-understand manner. If we can turn long-standing trade-offs into trade-ons (coexistence), business opportunities will arise. [Lecture Topics] 1. What is a trade-off? 2. Trade-offs between customers and companies 3. Trade-offs within companies 4. Trade-offs within customers 5. How to turn trade-offs into trade-ons 6. Steps for exploration 7. Q&A / Business card exchange

[Lecturers] Corporate Partner, Nishimura & Asahi Law Office Osaka, Mr. Satoshi Niki Associate, Nishimura & Asahi Law Office - Foreign Law Joint Enterprise, Mr. Shu Numazawa [Key Lecture Content] In recent years, the diversification of defense cooperation and advancements in dual-use technology have significantly changed the management and international sharing of advanced technologies. This lecture will clarify the basic structure of Article 3 of the Japan-U.S. Technology Agreement and the significance of "similar treatment," while explaining the institutional transformation brought about by the introduction of the non-public patent application system under the Economic Security Promotion Act. Furthermore, considering the relationship between this system and the Japan-U.S. Technology Agreement, we will examine how to reposition the patent applications and secrecy management of defense-related technologies within the context of expanding international joint research and multilateral defense cooperation. [Lecture Items] 1. Diversification of defense cooperation and advancements in dual-use technology 2. Basic structure of Article 3 of the Japan-U.S. Technology Agreement 3. Practical application of "similar treatment" 4. Introduction of the non-public patent system (Economic Security Promotion Act) 5. Relationship between the non-public patent system and Article 3 of the Japan-U.S. Technology Agreement 6. Expansion of international joint research and reevaluation of Article 3 7. Q&A / Business card exchange