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Amazon lookout for vision uses computer vision models trained by Amazon cloud technology on image and video streams to discover anomalies and defects in products or production processes
Currently, users and partners using lookout for vision include GE Healthcare, Amazon and Balser
Recently, Amazon cloud technology announced that Amazon lookout for vision is officially available. It is a new service that uses computer vision and advanced machine learning ability to analyze images to find defects and anomalies in products or processes in the manufacturing process. Amazon lookout for vision can use as few as 30 benchmark images as customer training models through a machine learning technology called “feed shot learning”. With Amazon lookout for vision, customers can quickly start to detect manufacturing and production defects of products (such as cracks, dents, incorrect colors, irregular shapes, etc.), and prevent these costly defects from entering the operation process or even reaching customers. Combined with Amazon lookout for equipment, Amazon monitron and Amazon panorama, Amazon lookout for vision provides the most comprehensive industrial machine learning service suite from cloud to edge for industrial and manufacturing customers. With Amazon lookout for vision, customers can pay for the actual use of the service on an hourly basis to train the model and detect anomalies or defects, regardless of pre commitment or minimum fees. To get started with Amazon lookout for vision, visit: https://aws.amazon.com/lookout-for-vision/
In today’s manufacturing industry, production line shutdown caused by missing defects or inconsistent quality problems will cause millions of dollars of cost overrun and revenue loss every year. In order to avoid these costly problems, industrial enterprises must make unremitting efforts to ensure quality control. Quality assurance in industrial processes usually relies on manual inspection. Even in the best case, the process is still time-consuming and can not guarantee inconsistency, while in the worst case, it is almost impossible. Computer vision can bring the speed and accuracy needed to continuously identify defects. However, traditional computer vision solutions can be very complex. Building a computer vision model from scratch requires careful labeling of a large number of images for each element in the manufacturing process. The data scientist team then needs to build, train, deploy, monitor and fine tune the computer vision model to analyze each individual stage of the product inspection process. Even small manufacturing process changes (such as replacement of an out of stock part with another equivalent part, updating product specifications or changing lighting) mean the need to retrain and redeploy individual models, or other models downstream of the production process. Obviously, this is lengthy, complex and time-consuming. Because of these obstacles, the visual anomaly system driven by computer vision is still beyond the reach of most companies.
Amazon lookout for vision provides customers with a high-precision, low-cost anomaly detection solution, which uses computer vision to process thousands of images per hour to find defects and anomalies without machine learning experience. Customers send camera images to Amazon lookout for vision in real time to identify anomalies such as product surface damage, component loss and other anomalies on the production line. Using the machine learning technology of “feed shot learning” (machine learning model can classify data based on a very small amount of training data), the service only needs as low as 30 acceptable and abnormal images as a benchmark to start the evaluation of machine parts or finished products. In addition to the ability to detect anomalies without a large amount of training data, this function also enables the service to adapt to the inspection tasks in various industrial environments. After analyzing the data, Amazon lookout for vision reports images that are different from the benchmark through the service dashboard or “detectanomalies” real-time API for appropriate action. Amazon lookout for vision is fine enough to achieve high-precision adjustment of camera angle, pose and lighting in the working environment. Customers can also provide feedback on the results (such as whether the prediction correctly identifies the exception), and lookout for vision will automatically retrain the underlying model to continuously improve the service. This feature allows the technology to fully adapt to changes in the manufacturing process, and even know when to allow or not to allow changes based on customer feedback. This means that customers can be more flexible, according to their own competitive advantage or external factors affecting their operations, timely adjust the process.
“Whether our customers make ingredients for frozen pizzas or precisely calibrated parts for airplanes, we clearly understand that ensuring that the products reaching the end users are of high quality is fundamental to their business. While this may seem obvious, ensuring quality control of industrial processes is actually very challenging. ” Swami sivasubramanian, vice president of machine learning at Amazon cloud technology, said, “we are pleased to offer Amazon lookout for vision to customers of all sizes and industries to help them detect defects quickly and economically on a large scale, save time and money, and ensure the quality that their consumers rely on without machine learning experience.”
Lookout for vision can be obtained directly from the Amazon Web Services console, or by supporting partners to help customers embed computer vision into existing operating systems within their facilities. The service is also compatible with Amazon cloudformation. Lookout for vision has been officially launched in the eastern United States (Northern Virginia), eastern United States (Ohio), western United States (Oregon), Europe (Ireland), Europe (Frankfurt), Asia Pacific region (Tokyo) and Asia Pacific region (Seoul), and other regions will be launched soon.
GE Healthcare is the world’s leading innovator of medical technology and digital solutions. It helps clinicians make faster and more accurate decisions through intelligent devices, data analysis, applications and services. “The early results of Amazon lookout for vision are encouraging, which will help improve the speed, consistency and accuracy of defect detection in our plants.” Kozaburo Fujimoto, operations officer, general manager of manufacturing department and plant manager of GE Healthcare Japan, said, “as one of the most reliable healthcare companies in the world, we have been keeping technological progress and digital innovation for more than a century. We are full of expectations for the benefits that Amazon cloud technology’s industrial machine learning service will bring to our manufacturing environment.”
Amazon’s print on demand (POD) facility, which prints books on order for customers. “Since books are made when customers order them, it is essential to ensure the accuracy of every step of the manufacturing process. With pod, we can quickly deliver the highest quality books to our customers. ” David Symonds, global director of Amazon pod, said, “with Amazon look out for vision, we can automate and extend visual inspection at every step of production, while running at full speed, helping us ensure a good customer experience.”
Basler is a global industrial vision manufacturer and solution provider, providing cameras and machine vision systems for semiconductor detection, robotics, food detection, postal sorting and printed image detection. “Fault reduction is one of the most important KPIs that manufacturing enterprises need to consider. The traditional manual detection is a labor-intensive and difficult to scale detection method. Through the use of computer vision for quality inspection, this process can be automated, thus significantly reducing costs. Basler and Amazon lookout for vision provide a very compact architecture, which can adopt Visual based anomaly detection in any production site. We are happy to combine Basler’s expertise in industrial vision and edge platforms with Amazon’s investment in industrial machine learning to provide our customers with a complete vision solution. ” Gerrit Fischer, marketing director of Basler AG, said.
Dafgards is a household name in Sweden, producing all kinds of food. “We tried Amazon lookout for vision to automate the inspection of our pizza line to see if there was enough cheese and the right ingredients in the pizza, and the results were good.” Fredrik dafg å Rd, head of operations excellence and industrial Internet of things at dafgards, said, “we are pleased to be able to extend lookout for vision to other production lines such as hamburgers and waffles to help us detect any anomalies, including incorrect ingredients. We plan to extend lookout for vision to multiple production lines. Amazon lookout for vision will help dafgards improve consistency and accuracy in detecting defects and anomalies, enabling us to improve overall production quality on a large scale. ” More reading: AWS Technology Summit 2018 Shanghai station set sail. It is estimated that there will be more than 50 technical forums and more than 6000 professionals attending the meeting, which is the highest in China. AWS announced the opening of three Amazon cloudfront sites operated by Western cloud data. AWS announced the launch of new regions in Hong Kong. At present, it has provided 64 services in 21 regions around the world Amazon’s Q4 financial report in 2020: the annual revenue of Amazon’s cloud service (AWS) reaches 45.4 billion US dollars. Shanghai Amazon’s AWS joint innovation center is officially opened to build a new smart city with the government. AWS launches the education technology entrepreneurship acceleration plan in China. AWS edstart Amazon’s focus on Ali’s “cloud platform” war is about to start. AWS joins hands with several APN partners Meeting the global security and compliance needs of Chinese customers Amazon AWS and Nanjing Municipal Government jointly build Nanjing joint innovation center project CNNIC: the next outlet from Amazon public cloud market five forecasts of Amazon’s business development in 2014 Amazon: 4q19 revenue increased by 21% year on year, prime members reached 150 million Amazon: 4q19 financial report teleconference record AWS’s product portfolio is in a leading position in the market. Amazon: 2q19 net sales reached $63.4 billion, a year-on-year increase of 20%. Amazon: during the epidemic period, the demand for e-commerce and entertainment surged, but the increase in the cost of fulfilling orders dragged down profits
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