When will the hottest made in China 2025ai plant b

2022-07-24
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Made in China 2025: when will the AI factory be realized

Abstract: outside the field of science and technology, AI technology is still mostly experimental. Only a few exceptions - especially in the automotive field - have been adopted by few factories. The implemented AI technology is applied in a small range, mainly in areas such as inventory management and inspection

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outside the scientific and technological field, AI technology is still mostly experimental, with only a few exceptions - especially in the automotive field - few factories have started to adopt it. The AI technology that has been implemented to achieve customer satisfaction in an all-round way is applied in a small range, mainly in areas such as inventory management, inspection and so on

Dayton Horvath, a researcher at lux research, a market research institution, said: "AI can support the operation of applications such as finite element analysis (FEA) to establish simulation models. In addition, it can also deal with more difficult problems, such as those with greater degrees of freedom or incomplete data sets." For example, topology optimization can use AI to create lighter parts with the same or higher strength, and can build more efficient heat exchanger models

a system often mentioned in the factory AI application is robot. The AI robot technology neocortex of the American operator universal logic is derived from the Robonaut research and development project of the space station robot sponsored by NASA. This technology enables the automatic system to handle deformable objects, high item variability and parts replacement, and does not require fixed facilities

made in China 2025: when will the AI factory be realized

hob wubbena, vice president of universal logic/universal robotics, said that neoportex is the AI machine learning module of the company's spatial vision 3D software platform, which can work with various actuating machines, not just robots; The platform can sense the surrounding environment of the robot used for handling, grasping and other tasks, so that the robot can interact and react with the environment in real time and at high speed. The capabilities given to the robot include the ability to properly recognize and respond to objects mixed with various shapes and textures, such as bottles, bags and boxes, with a reliability of 99%

for cooperative robots, the intensive training of "human in the loop" is the key to making robots smarter with the help of machine learning; Erik Nieves, founder and executive officer of plusone robotics, said: "intensive learning will provide the best service for the factory production line and distribution center Both bring impact; In the future, the distribution center will be under each large factory. Even those who run the factory have never thought about this. As the factory imported 346700 batches, 48544700 tons and US $32.056 billion of the above four types of waste raw materials in 2013, these will continue to progress. "

examples of the combination of AI and industrial robot equipment

recently, there have been two cooperation projects in the industry to develop AI technology for industrial (including manufacturing) process robots. One is "cognitive industrial machines" that can help human operators improve quality control, improve speed and yield, and reduce down time, This is a cross industry digital solution that combines ABB ability's cloud to edge devices and IBM's Watson IOT platform

the above commercialized system is called cognitive vision inspection system. Combined with the AI of Watson supercomputer and the real-time image of the production line captured through ABB system, defects can be found and relevant data can be sent to the cloud for analysis on the Watson IOT platform for manufacturing industry; BRET Greenstein, vice president of IBM Watson IOT department, said that Watson is implemented in the cloud, and its subset can be implemented on the server: "we can execute on edge devices and off, usually x86 systems using Linux or embedded operating systems; in this regard, we are cooperating with CISC dual digital display test equipment which has become the mainstream equipment o and other manufacturers."

in addition to supporting machine vision inspection, IBM uses Watson's perception to interact with operators in a manual free environment, or provides augmented reality tools to assist in diagnosing and maintaining equipment. Greenstein said: "we are seeing the adoption of such technologies around the world, including the United States and other markets; AI brings more competitive advantages, including improving quality, safety and productivity, as well as achieving the manufacturing of more sophisticated and complex products."

at the same time, NVIDIA and Japanese manufacturer FANUC are also cooperating to add AI function to FANUC's industrial control system field (FANUC intelligent edge link and drive), so that robots in automated factories can operate faster and more efficiently; This technology will apply a series of NVIDIA graphics processors (GPUs) and deep learning software to enable AI to execute in the cloud, data center, and even embedded in edge devices

field system is linked with CNC equipment, robots, peripheral devices and sensors to optimize manufacturing production with the help of analysis; Murali gopalakrishnafanuc, head of NVIDIA's intelligent machine product management department, said that FANUC recently demonstrated three basic applications of AI robots, including grasping and placing objects, predictive maintenance at the edge, and automated optical detection with a seven fold increase in detection rate

nvidia's Volta claims to be the first GPU architecture built specifically for AI applications, that is, training that can support machine learning; Tesla V100 GPU of Volta architecture is equipped with 640 tensor processor cores, which can provide 120tflops performance, equivalent to 100 deep learning CPUs (source: NVIDIA)

General Electric, a large American manufacturer, is also developing technologies suitable for its own manufacturing needs and other American vertical integration manufacturers; John lizzi, head of Robotics Department of GE Global Research, revealed that in addition to the software and hardware platforms, GE has also invested in Clearpath robotics, which is good at automatic mobile robots, and OC robotics, which is famous for its "snake arm" robots

for some application cases, Ge builds robots from scratch, such as devices that can go deep into the jet engine for detection; In addition, the company also makes and purchases sensors by itself. Through machine learning, AI has become very important in the robot field, and this technology has also become the key to improve robots in the future from three aspects, namely perception, advanced reasoning and dexterity. Lizzi also pointed out that collaborative robots are also a major trend. GE's vision is to develop mobile and self-sufficient systems. Humans only need to intervene when dealing with exceptions. In addition, there are smart robots that can cooperate with human teams

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