[Thank You for Attending] Report on the 8th Smart Factory EXPO: Exhibition of Appearance Inspection AI and Worker Analysis AI

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

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

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

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

[Speaker] Yuichi Murakami Director, Automotive Sector, Deloitte Tohmatsu Consulting LLC [Key Lecture Content] In the automotive industry, which is undergoing a once-in-a-century transformation, "SDV: Software Defined Vehicle" will play a central role in this change. However, the term "SDV" encompasses diverse meanings, leading to varying interpretations and resembling a buzzword. In this lecture, we will explore the true digital transformation (DX) in the automotive industry encapsulated by the term "SDV," starting from the changes in the value provided by automobile manufacturers, namely "the car (what is produced)," and including both "changes in how it is made" and "changes in how it is used." We will provide a comprehensive examination of the impact of digital technology on the automotive industry and the points of transformation. [Lecture Topics] 1. Changes in usage - Shifts in user values 2. Changes in what is produced (the car) - Software and digitalization of vehicles 3. Changes in how it is made - Software-based vehicle development 4. Changes in the supply chain 5. Changes in business viability 6. Q&A / Business card exchange

[Lecturers] Masaki Mochimaru, Fellow, National Institute of Advanced Industrial Science and Technology Masato Komiya, CEO, d-strategy, inc. / CEO, Third Ecosystem, inc. Masato Komiya, Specially Appointed Associate Professor, Data Science Research Institute, Tokyo International University [Key Lecture Content] The decrease in the labor population due to declining birth rates and aging society, along with the increasing burden of nursing care and rehabilitation, presents business opportunities. There is growing attention on the approach of "human augmentation," which not only involves complete automation through AI and robots but also enhances human capabilities. In particular, the "interverse" business, where people connect with virtual spaces to transcend time and space constraints and extend value into the real world, is expected to thrive. The lecture will introduce the latest trends through examples of collaboration with companies and national projects. [Lecture Items] 1. Human Augmentation 2. XR 3. Service Transformation in Manufacturing 4. Metaverse 5. Virtual Economy 6. Q&A / Business Card Exchange

[Speaker] Abeam Consulting Co., Ltd. Supply Chain Sustainability Unit Principal Shiro Komatsu Digital Technology Business Unit Artificial Intelligence Leap Sector Senior Expert Miho Yoshida [Key Lecture Content] In response to the rapid changes and complexities in the current business environment, procurement organizations need to break away from their downstream positioning and become a strategic function that leads company-wide reform and corporate value. This seminar will redefine the ideal state that procurement should aim for and the challenges that need to be overcome, introducing the possibilities of business reform utilizing AI agents/solutions along with specific case studies. We will explain the latest AI capabilities such as automated quotation assessment and automated delivery date adjustments, clarifying what your company should do now to strengthen procurement in light of your current situation. [Lecture Items] 1. The ideal state that procurement should aim for and the current situation - Case studies of procurement reform 2. What AI agents/solutions can achieve - Including case study presentations 3. Towards realizing the strategic function of the procurement department 4. Q&A / Business card exchange

[Speaker] Tadakazu Arakawa, Professor Emeritus, The University of Tokyo / Vice President, World Wind Energy Association [Key Lecture Content] After an overview of wind power generation, the latest information on the business trends and technological developments of offshore wind power generation, which has become one of the main power sources, will be explained. Based on the Renewable Energy Sea Area Utilization Act, operators have been determined for offshore wind power projects up to Round 3, and there has been significant progress in expanding into vast Exclusive Economic Zones (EEZ). On the other hand, due to international material shortages and rising prices stemming from issues like the Ukraine crisis, some operators have expressed the possibility of withdrawing from projects. In Japan, where there are no wind turbine manufacturers, discussions will be held on the healthy development and dissemination of offshore wind power towards the carbon neutrality policy by 2050. [Lecture Items] 1. Introduction to Wind Power Generation 2. Current Status of Offshore Wind Power Generation 3. Offshore Wind Power Projects Based on the Renewable Energy Sea Area Utilization Act 4. Technology and Wind Turbines in Offshore Wind Power Generation 5. Project Formation and Regional Promotion of Offshore Wind Power Generation 6. Progress of Japan's Offshore Wind Power Generation Aiming for Carbon Neutrality 7. Q&A / Business Card Exchange

The Management Game (MG) is a practical educational training program developed by Sony in 1976. It has a track record of approximately 5,000 companies and 1 million participants, primarily among large corporations. Through corporate management simulation (experiential learning), it enhances numerical ability and strategic thinking. Each participant takes on the role of a business owner, managing the company from its founding to its operation. They practice a series of management cycles, including decision-making, result analysis (financial statements), and planning. Participants not only create P/L and B/S but also learn strategic accounting (criteria for profit generation), conduct management analysis, and draft the next management plan (strategic plan). The program combines "practical exercises" and "lectures" to achieve high learning effectiveness.