We will be exhibiting at the Kansai Monozukuri World "Monozukuri AI/IoT Exhibition" from October 5 (Wed) to October 7 (Fri).

As an enabler company for our customers, we contribute to society through manufacturing innovation!

At Fields Technology Co., Ltd. is a group of engineers dedicated to developing the necessary manufacturing conditions and systems for new product development and mass production improvement, primarily in the semiconductor manufacturing field. We provide consistent support from proposing improvement measures aimed at problem-solving to implementing and following up on solutions, by directly addressing issues on-site and utilizing statistical methods based on principles and fundamentals. We promise to be a strong partner in improving our customers' management. 【Business Activities】 ■ Infrastructure system construction and application software development ■ Data collection and analysis ■ Development of manufacturing methods in the manufacturing technology field *For more details, please refer to the PDF document or feel free to contact us.

• Other contract services

Attention managers and personnel in the manufacturing and quality control departments! We present case studies on improvements utilizing data.

To realize a smart factory, it is considered necessary to achieve "connectivity" through the collection and integration of production equipment data. However, simply collecting data and "connecting" it will not yield the management value that was envisioned. It is important to gather and utilize data that "connects" to value. This document presents examples of improvements utilizing data, focusing on the methods for collecting and processing the data necessary to achieve management value. [Recommended for] ■ Those who want to work on smart transformation but don't know where to start ■ Those who want to start collecting data from a single piece of equipment ■ Those who are struggling with data collection from old equipment ■ Those who have collected data from production equipment but are not seeing management results ■ Those who want to know about case studies of data collection services [Contents] ■ Purpose of this document ■ Expected challenges ■ Solutions to the challenges ■ Service introduction ■ Case study introduction ■ Company overview *For more details, please refer to the PDF document or feel free to contact us.

• Business Intelligence and Data Analysis

Information useful before system implementation, including common challenges and solutions for realizing predictive maintenance of equipment.

Our company provides consistent technical support from the acquisition to the utilization of various data in manufacturing plants. Furthermore, we are capable of building infrastructure, including data collection tools. This document introduces common challenges and solutions in implementing equipment anomaly monitoring, as well as the features of our analysis and anomaly management system, "＠FieldEye Manager," and examples of its utilization. It is recommended for those who want to start predictive maintenance for equipment or have challenges in collecting and utilizing equipment data. *For more details, please check the download button. Feel free to contact us as well.*

• Business Intelligence and Data Analysis

Implementing the necessary functions for effective utilization of manufacturing data! Seamlessly achieving data analysis to anomaly monitoring.

The "@FieldEye Manager" is an analysis and anomaly management system that seamlessly realizes data analysis and anomaly monitoring through centralized data management and modeling. It implements necessary functions for effective utilization of manufacturing data, including "high-speed processing of large volumes of data and external integration," "high-precision analysis," "anomaly detection," and "modeling." In response to the challenge that "most quality anomalies are discovered in later processes, leading to reactive measures and increased losses," there are cases where we have checked 500 equipment parameters in real-time at 10,000 files per day to prevent the outflow of quality anomaly lots in advance. 【Features】 ■ Big Data Support: High-speed search using NoSQL DB ■ Usability: Trimming, overlaying time series, and statistical value display ■ Modeling and Anomaly Detection: Automatic judgment through modeling of normal waveforms *For more details, please refer to the PDF materials or feel free to contact us.

• Other analyses

About ROAD: The "Roundtable on the Purpose of Autonomous Driving (ROAD)" conference series has evolved into a unique platform for interdis-ciplinary dialogue and international collaboration in the field of autonomous driving and autonomous mobility. Established in 2016, ROAD has brought together researchers, industry leaders, and public sector stakeholders from six countries across three continents. Based on this background, the upcoming ROAD 2026 will focus on "safety” and "driving AI”—the final pieces of the autonomous driving puzzle—to advance discussions on establishing the foundational framework for ensuring safety quality and obtaining regular-tory approval for autonomous driving. We also intend to discuss the international commonalities and differences regarding the social value brought about by ADS vehicles in terms of automation, intelligent driving, and mobility. We have established a total of five compelling themes for the Round Workshops, consisting of two topics related to “The Last Piece” and three topics related to the social value of ADS, as shown below. 1) Round Workshop 1 - Horizons of E2E Driving AI → Can AI Understand the Driving Environment Like Humans? 2) Round Workshop 2 - Beyond the Unknown: Safety Cases for ADS → Can Safety Ever Be Proven? 3) Round Workshop 3 - Envisioning Smart City Mobility → Can Smart City Mobility Bridge the Mobility Divide? 4) Round Workshop 4 - Logistics Enhancement Through Autonomous Tracking → Will Logistics Become Human-Free? 5) Round Workshop 5 - The Evolution of CASE: SDV/AIDV → Will Automakers Become AI Companies? We hope you’ll all join us!

[Speaker] Masashi Sugita, President and CEO of LEX Style Co., Ltd. [Key Lecture Content] The power consumption of AI servers used in data centers has significantly increased, making traditional air cooling insufficient for operation. This lecture will organize the requirements for introducing a liquid cooling system into air-cooled data centers and explain the implementation method using free cooling with specific design details. When handling high-density AI servers, energy efficiency is required, and the widely used energy efficiency indicator, as well as the Ministry of Economy, Trade and Industry's Resource and Energy Agency's PUE regulation of "1.3 or below," will be explained along with practical operational insights. [Lecture Items] 1. Heat dissipation methods for high-density, high-heat AI servers 2. Basics and importance of PUE/pPUE 3. PUE regulation of "1.3 or below" by the Ministry of Economy, Trade and Industry's Resource and Energy Agency 4. AI server implementation and requirements for new data centers 5. Summary and future outlook 6. Q&A / Business card exchange

[Key Lecture Content] 1. Promotion of SAF Introduction Yasushi Yamashita, Director, Carbon Neutral Promotion Office, Aviation Bureau, Ministry of Land, Infrastructure, Transport and Tourism 1. Importance of SAF in the decarbonization of the aviation sector 2. Initiatives to promote the introduction of SAF 3. Q&A / Business card exchange 2. Japan Airlines' Challenge Towards Net Zero CO2 Emissions by 2050 Kazuki Hirotani, Group Leader, GX Planning Group, Sustainability Promotion Department, Japan Airlines Co., Ltd. 1. Introduction of our five initiatives for CO2 emission reduction 2. Initiatives for reducing fuel consumption (introduction of fuel-efficient aircraft, operational improvements) 3. Initiatives for fuel transition (sustainable aviation fuel SAF) 4. Initiatives for reductions outside the value chain (carbon credits, new removal technologies) 5. Initiatives to deepen collaboration with society 6. Q&A / Business card exchange

[Instructor] Yuichiro Kabushiki, Partner Lawyer at TMI Comprehensive Law Office [Key Lecture Content] With the spread of AI, there is growing attention on the civil liability of developers, providers, and users of AI. The Ministry of Economy, Trade and Industry will publish "Guidelines on the Interpretation and Application of Civil Liability in AI Utilization" in April 2026, and the Ministry of Justice will also establish an expert meeting to examine civil liability related to unauthorized use of images and voices generated by AI in the same month. As the full enforcement of the AI Promotion Act and the revision of AI guidelines are underway, it is necessary to design and operate governance based on the potential responsibilities that may arise retrospectively. In this seminar, based on the guidelines from the Ministry of Economy, Trade and Industry and drawing on litigation practice experience as a judge and lawyer, we will organize the basic framework for assessing civil liability and explain fundamental methods for designing and operating governance based on risk analysis. Furthermore, we will examine the framework for civil liability and the design and operation of governance using hypothetical cases that are likely to pose practical issues.

In this seminar, we will welcome Mr. Satoru Hayami from Waseda University, who will explain the latest trends in AI utilization in manufacturing, as well as the evolution of technologies such as agent-based AI and physical AI, and the opportunities and key points for practical application in the manufacturing industry. Furthermore, Mr. Tsubasa Shibata, representative of Next Opt, will introduce processes aimed at practical implementation, incorporating actual case studies from manufacturing sites. We hope you will envision the "potential for AI utilization in your company" and take home hints that will lead to improvements in your operations starting tomorrow. We look forward to your participation.