visual inspection system

With the rapid implementation of artificial intelligence technology and the continuous development of the intelligent robot industry, visual inspection machines are unleashing even stronger vitality. The typical structure of visual inspection equipment design mainly consists of five parts, namely: lighting, lens, camera, image acquisition, and computing hardware units.   What is the visual inspection? Visual inspection system refers to the use of machine vision products (i.e. image capture devices, divided into CMOS and CCD) to convert the captured target into an image signal, which is transmitted to a dedicated image processing system and converted into a digital signal based on pixel distribution, brightness, color, and other information; The image system performs various operations on these signals to extract features of the target, and then controls the on-site equipment actions based on the discrimination results.     Customization process of visual system 1. Software Testing The cyclic process of ensuring the correctness of software processes and the correct application logic relationships, discovering vulnerabilities in the system, conducting research and development modifications, and testing verification. 2. Hardware testing Conduct hardware reliability testing on the hardware itself (aging testing, compatibility testing, failure rate testing) and the environment to determine whether the software can run in multiple hardware configuration environments. 3. Joint debugging test Test the software and hardware joint debugging function to verify the correctness of electrical and software signal communication logic, light source, camera and other hardware triggering functions such as photography and scanning, as well as the statistics of detection results. 4. Model testing   Focus on the functional testing, performance testing, evaluation of model indicators, and analysis of indicator results of the model.     How to carry out testing of visual inspection system? Customer Requirements Application type: Accurately and detailedly understand the changes in product testing standards, external dimensions, and other factors that affect testing, and preliminarily evaluate whether they can meet the requirements. Stage requirements: Customers' demands for visual inspection efficiency, quantifying the time required for visual inspection steps. Accuracy requirement: Control the accuracy of product defect detection. Installation space: Confirm if there are any restrictions on the installation of visual equipment in the on-site environment.   Conceptual design Requirement analysis: Organize key customer requirements and analyze their feasibility. Hardware design: Selection of visual system platform, camera, lens, and light source. Software design: Use third-party visual software or develop visual processing software independently. Feasibility verification: Set up software and hardware environments, customize human-computer interaction interfaces, and conduct preliminary testing to determine if they can meet customer needs.   Algorithm Deployment Cloud platform development: Collect product defect sample images, upload and store images, select images, annotate, upload, train, test, optimize, and apply.  

Deploying visual inspection systems has become the first choice for manufacturing enterprises to transform quality inspection and improve product quality. However, enterprises that are not familiar with visual inspection equipment often have certain misunderstandings about the value of visual inspection equipment when choosing. Today, we will summarize several types of problems that enterprises face how to choose visual inspection machines and systems.     Question: If one machine can inspect all products? No, it's not possible. If a company wants to purchase a set of AI visual inspection equipment to test all its products, it is not feasible at this stage.   Although AI visual inspection equipment is compatible, it has a range of requirements for product specifications. Currently, many manufacturing companies have a wide range of products, and products with different materials, shapes, and sizes require different light sources, cameras, and algorithms.     Keye AI image visual detection has a certain degree of compatibility, but the two products differ greatly and it is also difficult to achieve complete compatibility. The visual inspection equipment for bottle caps is compatible with two products with a height difference of no more than one-third and a width difference of no more than half, and there are no irregular caps. Whether the height or width difference is too large, using the same equipment for inspection will affect the final factory quality. Customized solutions based on product characteristics are necessary to ensure the factory quality of the product.     Question: Will setting excessively high testing standards lead to a low yield rate? Yes. Some manufacturing companies, when purchasing vision inspection systems, do not establish inspection requirements based on the actual situation and acceptance standards of the enterprise, but instead use theoretical standards to develop inspection standards. Finally, when debugging and running, it was found that the yield rate was too low, and the visual inspection system was not accurate enough. In fact, this kind of problem belongs to the use of useless ultra-high standards. Enterprises should develop testing standards based on actual situations, increase testing items appropriately to improve testing standards, improve product quality, and maintain market competitiveness.   Question: Is the value of visual inspection systems only reflected in reducing labor costs? No, it's not. A set of AI visual inspection equipment not only saves labor costs, but also reduces the operating costs of enterprises. To improve efficiency, enterprises often choose automated equipment to replace manual labor, which not only improves production capacity and quality, but also reduces operating costs. Keye's AI image visual inspection equipment on a single production line can help enterprises save 3-5 inspection personnel and ensure uniform product quality standards, enhancing customer recognition of the enterprise. In terms of operating costs, Keye's AI image visual detection has played a more significant role. For example, visual inspection of bottles can directly sell qualified products after inspection, and defective products that have been removed can be further processed or reused. The product value can be diversified and maximized.       Question: Can a visual system be used for high production? Suggested to use, but it depends on the business situation of the enterprise. A large output is indeed more suitable for choosing a visual inspection system. From the long-term development strategy of enterprises, manual testing has limited speed, low efficiency, and is more suitable for using automated equipment for testing in large quantities. Although some individual products have low value, using manual visual inspection may result in missed or false inspections. If the products are found in the hands of downstream enterprises and do not meet the standards, they may choose to return them, causing certain losses to the enterprise. Over time, this is not conducive to the long-term development of the enterprise. Therefore, when the production volume of the enterprise's products is large, it is recommended to choose visual inspection equipment. One investment can benefit the enterprise for a lifetime.     Therefore, the choice of AI visual inspection equipment by enterprises is not a direct manifestation of high quality. Only by making reasonable use of AI visual inspection systems to control product quality and effectively eliminate the outflow of defective products can we avoid complaints from end customers and win their trust in the enterprise.