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  6. Explanation material "Methods for Collecting and Utilizing Equipment Data to Successfully Implement Predictive Maintenance"

Explanation material "Methods for Collecting and Utilizing Equipment Data to Successfully Implement Predictive Maintenance"

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last updated:May 29, 2023

アットフィールズテクノロジー
アットフィールズテクノロジー
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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
予兆保全を成功させる設備データの収集・活用方法.JPG

Explanation material "Methods for Collecting and Utilizing Equipment Data to Successfully Implement Predictive Maintenance"

予兆保全を成功させる設備データの収集・活用方法.JPG
予兆保全を成功させる設備データの収集・活用方法.JPG

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【Analysis and Anomaly Management System "@FieldEye Manager"】 This system seamlessly realizes anomaly monitoring from data analysis. ■ Centralized management of large-capacity data, high-speed processing, and support for external integration ■ Real-time anomaly detection is possible ■ High-precision analysis is achievable through data overlay and trimming ■ Creation of learning models and automatic anomaly judgment using learning models are possible *For more details, please refer to the materials. Feel free to contact us with any inquiries.

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[Explanatory Material] "Methods for Collecting and Utilizing Equipment Data to Successfully Implement Predictive Maintenance"

[Explanatory Material] "Methods for Collecting and Utilizing Equipment Data to Successfully Implement Predictive Maintenance"

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【Exhibition 10/26 (Wed) - 10/28 (Fri)】We will be exhibiting at the Nagoya Smart Factory EXPO "Manufacturing Innovation Exhibition through IoT/AI/FA."

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This exhibition is a must-see for customers who want to visualize everything from individual equipment to the overall operation of the factory! ◆ I want to start collecting equipment data ◆ I want to see abnormalities at the equipment level ◆ I want to work on predictive maintenance for equipment Our services are recommended for customers with such concerns. For those struggling with specific approaches to IoT implementation in factories, we have prepared tools that allow you to experience firsthand the selection of collected data and the construction of an IoT environment, focusing on key points. Please stop by our booth! ■ Our company website is here https://atfields.com/

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

  • Seminar・Event

This exhibition is a must-see for customers who want to visualize everything from individual equipment to the overall operation of the factory! ◆ I want to start collecting equipment data ◆ I want to see abnormalities at the equipment level ◆ I want to work on predictive maintenance for equipment Our services are recommended for customers facing such challenges. For those struggling with specific approaches to IoT implementation in factories, we have prepared tools that allow you to focus on key points and gain hands-on experience, from selecting collected data to building an IoT environment. Please be sure to stop by our booth! ■ Here is the e-invitation (free) https://www.manufacturing-world.jp/kansai/ja-jp/search-ex/2022/domestic/aiotex/directory/directory-details.org-7292d96f-718f-4e43-beb0-971d9c9e1314.html?co=ml_aiotexk-k-40zjcv#/ ■ Here is our company website https://atfields.com/

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We will be exhibiting at the Kyoto Business Exchange Fair 2022 from February 17 (Thursday) to February 18 (Friday).

  • Seminar・Event

We will be exhibiting at the largest BtoB exhibition and business meeting in Kyoto, the "Kyoto Business Exchange Fair 2022." This time, our exhibition focus will be on "Productivity Improvement (Telecommunications and Information) in the Manufacturing Industry." We plan to showcase our efforts to enhance productivity using equipment data with demonstration machines. We look forward to welcoming many visitors! ■ Here is the entrance to the virtual exhibition https://vp.kyoto/Account/Login ■ Here is our company website https://atfields.com/

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【Exhibition May 13 (Fri) - 14 (Sat)】 We will be exhibiting at the 37th Ishikawa Information System Fair "e-messe Kanazawa 2022"!

  • Seminar・Event

We will be exhibiting at "e-messe kanazawa," the largest ICT business show on the Sea of Japan side. At this exhibition, we will provide easy-to-understand case studies on the utilization of equipment data for manufacturing personnel, engineers, and business owners, along with tools for hands-on experience. This is a must-see for anyone considering IoT implementation in factories or looking to further leverage equipment data for added value. We hope you will stop by! We look forward to welcoming many visitors! ■ Exhibition details here https://www.e-messe.jp/exhibitor.php?act=detail&id=616 ■ Our company website here https://atfields.com/

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アットフィールズテクノロジー

アットフィールズテクノロジー

Other manufacturing

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Our company is a group of engineers engaged in establishing manufacturing conditions and developing systems necessary for new product development and mass production improvement, primarily in the field of semiconductor manufacturing. We provide consistent support from proposing improvement measures to addressing and following up on issues, by directly confronting phenomena in the field and utilizing statistical methods based on principles and fundamentals. The name of our company, "At Fields," embodies our commitment to contributing to our customers rooted in the field. We promise to be a strong partner in improving our customers' management.

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