Non-visual inspection: A new inspection process system with AI × image inspection technology.
Are you struggling with 'oversights' and 'human errors' in visual inspections? Achieve high-precision inspection automation with the AI visual inspection system [Phoenix]!
In the production field, quality inspection is an important process, and until now, visual inspection (inspection by human eyes) has been the mainstream method. While visual inspection can achieve high precision, it also faces many issues such as the occurrence of human error, management of inspectors' health, and a decrease in the number of inspectors due to declining birth rates. Additionally, there is a method of image inspection based on rules, but since there are inspections that it excels at and others it struggles with, there is a possibility that the accuracy may not improve even if it is implemented for certain inspections. To address the concerns of companies struggling with such inspection processes, we have developed an AI-powered visual inspection system called 【Phoenix】. By building a system that automatically inspects using AI, it is possible to achieve inspection accuracy that rivals even that of skilled inspectors. For more details, please download the materials. 【Phoenix】 has been implemented in various manufacturing companies, including top industry leaders in Japan, primarily in the automotive and food industries. If you are interested in reviewing your inspection processes or automating inspections using AI, please feel free to contact us. We will provide a thorough explanation, including case studies.
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Do you have any concerns in the inspection process like these? - "There are differences in inspection quality among inspectors." - "The inspection difficulty is high, and it can only be done visually." - "I want to eliminate dependency on individuals and improve productivity and efficiency." - "I want to minimize human errors as much as possible." - "I want to improve the accuracy of existing image inspection machines." Purpose of introducing the AI visual inspection system [Phoenix]: ◆ Automation of the inspection process ◆ Assurance of quality through improved inspection accuracy ◆ Improvement of yield through accurate judgments ◆ Reduction of human resources for visual inspectors ◆ Capability to handle a variety of small lots ◆ Ability to use a combination of AI and rule-based methods or switch between them depending on the inspection items By utilizing AI in visual inspections, why not clear the challenges of visual inspections and aim for improved productivity? Please check the materials for more details. *To give you an idea of how to utilize AI in visual inspections, we are currently conducting free evaluations. If you have any interest, please feel free to contact us.
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I will provide a detailed explanation about AI. Please feel free to contact us.
Detailed information
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Inspection Case 1: Carpet Tear Inspection In conventional visual inspection systems, it was difficult to inspect products with gradations, as shown in the image, leading to numerous false detections. With [Phoenix], by training the latest AI equipped in the system to recognize the characteristics of tears, it can detect only the defective areas without reacting to the patterned parts.
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Inspection Case 2: Bone Residue Inspection of Sausages It is possible to detect foreign objects and bones mixed inside sausages with high precision. At 【Phoenix】, we have achieved high-precision detection of small bones and foreign objects by combining pretreatment technology with the latest AI algorithms.
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Inspection Case 3: Scratch Inspection on Metal Plates In cases where the inspection target has a complex surface, such as metal, traditional visual inspection systems tend to react to variations in the shades of good parts, leading to unstable inspections. With [Phoenix], by training the AI only on the defects we want to detect, we can accurately identify only the defective items even in inspection targets with complex surfaces.
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Our company supports DX (Digital Transformation) in the manufacturing industry. Japanese manufacturing is facing significant challenges such as "intensified international competition" and "labor shortages," making the improvement of productivity through digital utilization increasingly necessary. However, the reality is that digital utilization is still not progressing on the ground. The reasons for this include various uncertainties such as: - "Not knowing when to utilize it" - "Not understanding the value of data utilization" - "Not knowing how to proceed" At VRAIN Solution, we aim to resolve the various uncertainties that companies face and realize their DX through consulting, AI algorithm provision, data analysis, AI application sales, system development, and a wide range of services utilizing the latest technologies. If you have any concerns or questions regarding DX, we would be happy to assist you.