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  6. IT Implementation Subsidy 2024: Promoting DX in Manufacturing and Logistics! Implementation possible within the fiscal year.

IT Implementation Subsidy 2024: Promoting DX in Manufacturing and Logistics! Implementation possible within the fiscal year.

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Confide for Factory

last updated:Jul 30, 2024

コーピー 本社
コーピー 本社
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[To companies struggling with AI implementation] It's not too late! This is your last chance for this fiscal year! Promote DX with the IT Implementation Subsidy 2024!

The IT Implementation Subsidy 2024 is a support program aimed at promoting DX (Digital Transformation) for the manufacturing and logistics industries. Are you facing any of these challenges as production technology, production management, quality control, or DX promotion personnel? - Struggling with the accuracy of visual inspections - Wanting to implement visual inspections but looking to reduce costs - Aiming to optimize line balance - Wanting to check the balance of assembly work - Wanting to detect worker anomalies early Would you like to solve these issues by utilizing the IT Implementation Subsidy? By using the IT Implementation Subsidy 2024, you can introduce the latest IT tools and achieve greater efficiency and quality improvement in your operations. This is especially a significant opportunity for companies considering the introduction of visual inspections or worker analysis, as it is the last major chance this fiscal year! Moreover, the implementation can be completed within the fiscal year. Deadline: - Application deadline: August 23 (Friday) by 17:00 Notes: - Access may become congested just before the deadline, making applications difficult. Early application is recommended.

    Image analysis software
【最終告知】IT導入補助金2024.png

IT Implementation Subsidy 2024: Promoting DX in Manufacturing and Logistics! Implementation possible within the fiscal year.

【最終告知】IT導入補助金2024.png
【最終告知】IT導入補助金2024.png

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1. Improvement of Appearance Inspection Accuracy We will utilize AI-powered appearance inspection tools to achieve early detection of defective products and improve quality. Even minute defects that are often overlooked in traditional visual inspections will be detected with high precision, significantly enhancing production quality. 2. Cost Reduction By utilizing subsidies, we can reduce initial investment and lower the barriers to implementation. For small and medium-sized enterprises, the initial implementation cost can be a significant barrier, but by leveraging IT introduction subsidies, this burden can be greatly alleviated. 3. Optimization of Line Balance and Efficiency of Assembly Work We will check the balance of assembly work in real-time and reduce waste in operations. By introducing tools that visualize work progress, we can monitor the work efficiency of each worker in real-time and implement immediate improvements. 4. Health Management of Workers Using cameras, we will detect abnormalities in workers early and provide a safe working environment. We will monitor workers' movements and postures in real-time, and if any abnormalities are detected, alerts will be issued immediately.

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Applications/Examples of results

【Appearance Inspection / Data Generation/Management】 - Semiconductor Manufacturing: Wafer inspection, chip appearance inspection, packaging defect inspection - Casting Industry: Surface inspection of cast products, internal defect detection, product dimension inspection - Automotive Manufacturing: Body panel scratch and dent inspection, engine parts defect detection, interior parts quality inspection - Food Processing Industry: Packaging defect inspection, foreign object detection in contents, error detection - Chemical Industry: Appearance inspection of chemical products, packaging defect detection, product uniformity confirmation - Pharmaceutical Manufacturing: Tablet chipping and cracking inspection, foreign object detection in packaging, label error detection - NG Image Generation: Artificially generating defective images for machine learning to compensate for data shortages - Quality Verification: Verifying the quality of AI models to ensure stable performance 【Operator Analysis】 - Manufacturing Operations: Work management, optimization of process flows, consideration of personnel allocation - Production Management: Measurement of cycle times, resolution of work variability - Quality Control: Detection of work omissions, estimation of work load - DX Promotion: Introduction of digital tools, data-driven decision making - Shipping Management: Streamlining shipping processes, optimization of inventory management * We also have "Product Materials" and "Case Studies" available, so please contact us.

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[Flyer] Last chance this fiscal year! Achieve DX promotion and AI implementation in the manufacturing and logistics industries with the IT introduction subsidy 2024!

[Flyer] Last chance this fiscal year! Achieve DX promotion and AI implementation in the manufacturing and logistics industries with the IT introduction subsidy 2024!

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[Other Materials] Guide to Utilizing IT Introduction Subsidies for AI Utilization – Includes Free Checklist

[Other Materials] Guide to Utilizing IT Introduction Subsidies for AI Utilization – Includes Free Checklist

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[Company Introduction] Copy Inc. / Company Information

[Company Introduction] Copy Inc. / Company Information

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[Case Study] Confide for Factory Work Analysis AI | Yokogawa Manufacturing Corporation

[Case Study] Confide for Factory Work Analysis AI | Yokogawa Manufacturing Corporation

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Catalog: Confide for Factory: Visual Inspection AI

Catalog: Confide for Factory: Visual Inspection AI

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[Catalog] AI for Manufacturing: XAI/QAAI-Based Platform 'CONFIDE for Factory'

[Catalog] AI for Manufacturing: XAI/QAAI-Based Platform 'CONFIDE for Factory'

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[Catalog] Confide for Factory: Data Generation/Management Solution

[Catalog] Confide for Factory: Data Generation/Management Solution

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Catalog: Confide for Factory: Worker Analysis AI (Workflow Analysis)

Catalog: Confide for Factory: Worker Analysis AI (Workflow Analysis)

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[Other Materials] Utilization of the SECI Model Using Worker Analysis AI

[Other Materials] Utilization of the SECI Model Using Worker Analysis AI

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Company information

コーピー

コーピー 本社

IT/Telecommunications

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Our company is an AI startup founded by researchers from the University of Tokyo and the French research institution Inria, with a mission to "improve quality and efficiency through advanced AI technology" specifically for the manufacturing and logistics industries. Our technology meets the needs of quality control, production technology, and DX promotion departments, enabling optimization of production processes and risk management. The founder, Yamamoto, has conducted AI research at Yahoo Japan and Inria, presenting results at top international conferences such as WWW and RecSys. Over 80% of our team consists of researchers who studied AI and computer science at world-class universities like the University of Tokyo, Cambridge, and Imperial College. With their international perspectives and advanced skills, we provide innovative solutions to quality control challenges. In particular, in mission-critical areas that emphasize the interpretability of AI, our XAI (explainable AI) technology brings transparency to the reasoning behind AI decisions for managers in quality control and production technology departments, supporting safer and more reliable system operations. This leads to improvements in production efficiency and quality, promoting sustainable growth in the manufacturing and logistics industries.

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