How to move from artificial intelligence to indust

  • Detail

How to move from "artificial intelligence" to "industrial intelligence"

speaking of artificial intelligence, industrial control first came into contact with Marvel's first film iron man in 2008. As a new star in the future industrial field, the "Jarvis" in the film is the most intuitive interpretation of the artificial intelligence system. By combining advanced AR technology and artificial intelligence voice and other artificial intelligence systems, it carries out data visual analysis, predictive maintenance, and self diagnosis in the process of fighting before the iron man goes to war

since the birth of the "thinking machine" in the 1950s, AI has failed to achieve a breakthrough. Until the past 10 years, with the rapid development of science and technology, the fictional "Jarvis" originally only in the film has quietly entered people's lives. There is no doubt that AI is setting off a new wave of digital revolution in both industrial and civil fields

what can AI do

Nowadays, artificial intelligence technology is developing rapidly in various fields. When it comes to artificial intelligence in the field of industry, everyone will be embodied as industrial robots; In the civil field, the Siri artificial intelligence voice function of iPhone has brought earth shaking changes to human life

industrial control focuses on the application of artificial intelligence in the industrial field, which can be divided into the following three categories:

the first category is the visual analysis of relatively simple application data: in addition to collecting various data of equipment operation (such as temperature, speed, energy consumption, productivity, etc.), artificial intelligence can store data for secondary analysis, optimize the energy saving of the production line, and detect whether the equipment operation is abnormal in advance, At the same time, measures to reduce energy consumption are provided

the second kind is to let the machine realize self diagnosis. For example, when a production line suddenly sends out a fault alarm, the machine can diagnose itself, find out where the problem is and what the reason is. At the same time, it can also tell us how to solve the fault according to the historical maintenance records or maintenance standards, and even let the machine solve the problem and recover itself

of course, we don't want to have failures, so the third kind of application, predictive maintenance, can be realized through artificial intelligence technology. You should know that if there is a sudden problem in the industrial production line or equipment, the loss will be very huge. So we use artificial intelligence technology to make the machine perceive or analyze the possible problems before they occur. For example, the NC machine tool in the factory needs to be replaced after running for a period of time. By analyzing the historical operation data, the machine can know in advance the time when the tool will be damaged, so as to prepare the replaced parts in advance and arrange to replace the tool at the latest maintenance

AI has already quietly settled in the industrial field

in 2017, Alibaba et industrial brain was the first AI to go down to the workshop in bat and AMG. As the first manufacturer to adopt cloud computing byk-c 8003 service provided by Alibaba, GCL, a photovoltaic material manufacturer, has increased its yield by 1% and saved hundreds of millions of costs every year. The cooperation between GCL poly and Alibaba cloud is an innovation demonstration in China's industrial manufacturing field. The first thing Alibaba cloud does in the manufacturer's workshop is to put the data of all ports on the production line on the cloud, then mobilize the computing power of thousands of servers, and find 60 variables that affect the yield in a short time from thousands of variables. Next, AI monitors and controls these variables in real time, and the production line only needs to "follow orders"

in fact, enterprises that quietly deploy AI in the industrial field have long appeared. As the pioneer leading the development of the automation industry, visionary bosses saw the advantages of digital transformation and began to deploy AI platforms in the industrial field

Siemens - Siemens Central Research Institute recently demonstrated a part of the dual arm robot in Munich. With the help of the high automation of artificial intelligence, the robot can work independently and cooperate without programming for product manufacturing. Siemens accelerates the pace of research and development, promotes the market of universal laboratory machines, and vigorously develops the Central Research Institute. Dr. kaiwurm said, "we just need to tell the robot to install a part on the guide rail, and it will perform this operation." As a simplified example, this task describes the connotation of "one-piece customized production". It involves processing or assembling diversified products with different parts. The robot obtains the relevant information of manufacturing products from the associated software model. Traditional robots cannot understand this cad/cam (computer aided design and manufacturing) model, but new robot prototypes can do it. In a sense, it's like a robot can understand different languages, so it doesn't have to program its motion and process. The ball screw is level E5

ge - recently, GE announced that it had reached multi-year agreements with many electric companies and reached extensive agreements with the New York Power Authority (NyPa), aiming to become the world's first fully digital power company. Today, the integrated intelligent operation center of Ge predictive analysis software has been opened, which is a cutting-edge asset monitoring and diagnosis center. Among them, GE and Enel will deploy and optimize GE's asset performance management (APM) software, which runs on predix, GE's industrial IOT platform, to monitor, predict and improve the reliability of 13 gas-fired power plants and 1 coal-fired power plant, all of which use general electric gas or Alstom turbines and generators. Russell Stokes, CEO of General Electric, said, "in the future, Ge will significantly improve operational efficiency for enterprise factories through digital transformation, so as to create more revenue."

Rockwell Automation not long ago, Rockwell Automation also showed its ambition to occupy a place in the field of industrial artificial intelligence. On November 3, 2017, Rockwell Automation announced to invest in a silicon valley innovation fund and co Creation Studio called thehive, which is committed to applying artificial intelligence (AI) to the field of industrial automation by leveraging the ecological environment composed of innovation groups and high-tech start-ups. Elikfooks, senior vice president of Rockwell Automation enterprise development, said, "we continue to establish partnerships with leading innovation groups. For example, we cooperate with thehive to further promote the realization of the vision of interconnected enterprises, that is, to push industrial productivity to an unprecedented new level through the integration of factory and enterprise operations." The purpose of Rockwell Automation's move includes helping manufacturing customers eliminate the barrier between the factory's grass-roots and higher-level information systems through co creation to solve customer problems, accelerate innovation and explore emerging technologies, so as to improve business performance

from "artificial intelligence" to "industrial intelligence"

intelligent technology from the computer and Internet industry is sweeping all fields around the world with an irresistible momentum. The combination of intelligence and industry has attracted global attention. From industrial 4.0 in Germany to industrial interconnection in the United States, and from predix in Ge to PMQ in IBM, we can see that the combination of industry and intelligent technology will also be the next outlet

the core of intelligence lies in decision-making and execution, while the core of decision-making lies in perception and judgment. In industrial systems, the continuous development of IOT technology, sensor technology, data transmission, data management and so on provides a reliable sensing foundation for the implementation of intelligent technology. However, most of the current industry focuses on human decision-making and feedback, which leads to a large part of the value of the system has not been released. The more complex the system is, the slower the learning curve of people will be. When the learning curve of people is slower than the speed of technological progress, people will become the bottleneck restricting technological progress and application. The first revolutionary change that AI brings to industry is to get rid of the limitations of human cognition and knowledge boundaries and provide quantifiable basis for decision support and collaborative optimization

industrial control: artificial intelligence will become one of the key words attracting attention in 2018. The future of artificial intelligence has been revealed to us in many science fiction films and television. But so far, the application of artificial intelligence in the industrial field is not as mature as Internet, and it needs to be further cultivated in the future. By fully realizing the intellectualization of factory operation through artificial intelligence, operators can minimize manpower and continuously improve manufacturing quality

I wonder what is your view on the development of artificial intelligence in the industrial field? Welcome to brainstorm with industrial control below the comments

Copyright © 2011 JIN SHI