Free image diagnosis now available! Araya's image recognition AI development service for the manufacturing industry.

Significantly reduced the selection time! We were able to greatly decrease the number of image points to be checked.

We would like to introduce a case where AI was implemented to extract suitable images that meet the criteria for publication in the media from a large number of images taken during sports events. In the case of our client, they traditionally took a large number of photos during sports events and manually extracted suitable images that met criteria such as "full body is visible" and "sports equipment is included." However, this selection process was time-consuming, and there was a demand for quicker extraction. To solve this issue, we created a system where AI extracts images that meet the criteria from thousands of target images, significantly reducing the number of images that need to be reviewed. For inquiries about the implementation of AI for the efficiency and automation of image and video-related tasks, please feel free to consult with Araya. [Effects After AI Implementation] ■ Significant reduction in selection time ■ Almost no time required for extraction *For more details, please refer to the PDF document or feel free to contact us.

• Other inspection equipment and devices
• Other image-related equipment
• Other information systems

With the introduction of AI, we are moving towards automated inspection with high quality! A case that can handle multiple types of raw materials and foreign substances.

We would like to introduce a case where AI was implemented for quality inspection of raw materials in consumable manufacturing. In the company that requested our services, inspectors previously needed to visually detect fine foreign substances that occasionally mixed in with the raw materials (plants) flowing through the manufacturing line. This visual detection by inspectors was challenging, and existing inspection equipment could not handle it, as conditions varied from factory to factory and line to line. To solve this issue, we installed fixed cameras on the manufacturing line and implemented an AI algorithm to determine good and defective products, achieving high-quality, automated inspection. Additionally, we introduced a total system that allows the customer to implement solutions for multiple factories and lines on their own. For inquiries about the introduction of AI for visual inspection of products and raw materials on manufacturing lines, please feel free to consult with Araya. [Effects After AI Implementation] ■ Automation of foreign substance detection ■ Support for multiple types of raw materials and foreign substances ■ Customers can independently manage different conditions in other factories/lines *For more details, please refer to the PDF document or feel free to contact us.

• Other inspection equipment and devices
• Other image-related equipment
• Other information systems

Utilization of automation for inventory management in logistics warehouses! A case aimed at significantly improving the efficiency of tasks traditionally performed by humans.

Inventory management in logistics warehouses involves a wide range of tasks and also requires working at heights, making it necessary to ensure the safety of workers. The "automated inventory drone" we are developing autonomously flies to trace all boxes, scanning the barcodes and QR codes attached to them, and registering the information in the inventory management system. By utilizing drones that fly autonomously for warehouse inventory tasks, it becomes possible to achieve this in a short time and at a low cost. Additionally, we are seeking partner companies in the logistics industry who are interested in collaborating with us to develop solutions using Alaya's automated inventory drone technology. **Benefits of the automated inventory drone we are developing:** - Drones at an affordable price range - Achievable with built-in cameras and QR codes - No need for additional RFID sensors, reducing implementation costs *For more details, please refer to the PDF document or feel free to contact us.*

• Other industrial robots
• 2D Code Reader
• Other production management systems

Achieving high inspection quality that does not rely on personal judgment! Introducing a case study of implementing AI in the inspection of parts for large transport machinery.

At Araya, we solve various business challenges for our customers using image recognition technology powered by deep learning. Here, we introduce a case study where AI was implemented for inspecting parts of large transport machinery. The company that requested our services had a statutory inspection task for parts of transport machinery. Traditionally, workers used endoscopes to conduct inspections on the fine parts that were subject to inspection, but they faced challenges such as "difficulty in maintaining high inspection quality" and "time-consuming processes." To address these challenges, we were able to reduce the overall burden of the inspection work by having AI automatically determine whether the inspection images indicated "normal" or "potentially abnormal and requiring focused inspection." If you are considering the introduction of AI for the visual inspection of large machinery and structures (such as towers and bridges), please feel free to consult with Araya. [Effects After AI Implementation] ■ Maintenance of high inspection quality ■ Reduction in required time *For more details, please refer to the PDF document or feel free to contact us.

• Visual Inspection Equipment
• Defect Inspection Equipment
• Image Processing Software

The following cameras are supported in the Elua 7.6 series. Product introduction: https://aileunsys.co.jp/b01_aileun.html Compatible camera list: https://aileunsys.co.jp/aileun/compatible_camera.html Newly added: - Manufacturer: DAHUA Model number (1 model): DH-IPC-HFW2449TLN-S-PRO

Dear Valued Customers, Thank you very much for your continued support. We would like to inform you that our company will be closed for summer vacation from Wednesday, August 13, 2025, to Friday, August 15, 2025. We will resume normal operations on Monday, August 18. We appreciate your understanding and cooperation.

Technoa Co., Ltd. (Headquarters: Gifu City, Gifu Prefecture, Representative Director: Koji Yamazaki) will hold a limited-time summer special event, "Monozukuri DX CAMP," from Saturday, August 9, 2025, to Saturday, August 23, 2025. Small and medium-sized manufacturing companies face challenges such as a shortage of specialized personnel and a lack of know-how and information, which act as barriers to promoting DX (digital transformation). This event will provide a step-by-step approach to "realistic DX," based on the know-how accumulated by Technoa while supporting the DX transformation of small and medium-sized manufacturing companies. It will be structured as DAY.1 to DAY.5, offering an opportunity for skill development during the summer break and supporting the learning and growth of small and medium-sized manufacturers. For more details, please refer to the related link.

JOHNAN has updated a webpage summarizing the selection points to solve various challenges in large-scale processing (quality maintenance, short delivery times, costs). This article introduces the challenges faced in large-scale processing based on years of knowledge and experience, as well as the key points for choosing the optimal contractor that balances quality and short delivery times. If you are looking for a reliable contractor, please make use of our "Large-Scale Processing Solutions." ▼For more details "Large-Scale Processing Solutions to Achieve Product Quality and Short Delivery Times" https://www.johnan.com/solution/process/processing-assembly/post_8.html

Thank you very much for your continued support. We sincerely apologize for the inconvenience, but our company will be closed for summer vacation during the following period. 【Closure Period】 From Saturday, August 9, 2025, to Thursday, August 14, 2025. We will resume normal business operations on Friday, August 15. We appreciate your understanding during this time and apologize for any inconvenience caused.