Nowadays, artificial intelligence technology is developing rapidly in various fields, and it is setting off a new wave of digital revolution. Its appearance has brought too many changes. Now the combination of intelligence and industry has attracted worldwide attention. Artificial intelligence has long been Quietly settled in the industrial field, how to move from "artificial intelligence" to "industrial intelligence", we will work harder.
Speaking of artificial intelligence, when we first came into contact, it was the first film "Iron Man" in Marvel in 2008. As a new star in the future industrial field, "Jarvis" in the film is the most intuitive interpretation of the artificial intelligence system. It combines advanced AR technology and artificial intelligence voice and other artificial intelligence systems to visualize data before the Iron Man battle. Analysis, predictive maintenance, and self-diagnosis during the battle.
Since the birth of "thoughtful machines" in the 1950s, artificial intelligence has not been able to achieve breakthroughs. Until the past 10 years, with the rapid development of science and technology, "Jarvis", which was originally only fictionalized in the movie, has quietly entered people's lives. There is no doubt that artificial intelligence is setting off a wave of new digital revolutions, both in the industrial and civilian sectors.
What can artificial intelligence do?Nowadays, artificial intelligence technology is developing rapidly in various fields. When it comes to artificial intelligence in the industrial field, everyone will behave like an industrial robot; while in the civilian field, it is the SIRI artificial intelligence voice function of Iphone, and its appearance has brought about earth-shaking changes in human life.
We focus on the application of artificial intelligence in the industrial field, which can be divided into the following three categories:
The first category is a relatively simple visual analysis of application data: in addition to the ability to collect data on equipment operations (such as temperature, speed, energy consumption, productivity, etc.), and store data for secondary analysis, the production line Energy-saving optimization, detecting whether the equipment is operating abnormally in advance, and providing measures to reduce energy consumption.
The second type is to let the machine achieve self-diagnosis. For example, if a production line suddenly issues a fault alarm, the machine can diagnose it by itself, find out where the problem has occurred, what is the reason, and also tell us how to solve the problem according to historical maintenance records or maintenance standards, and even let the machine solve the problem and self. restore.
Of course, we do not want to have a failure, so we can achieve the third type of application and predictive maintenance through artificial intelligence technology. To know if the industrial production line or equipment suddenly has problems, the damage caused is very huge. So we use artificial intelligence technology to let the machine perceive or analyze possible problems before they occur. For example, the CNC machine tool in the factory needs to be replaced after running for a period of time. By analyzing historical operational data, the machine can know the time when the tool will be damaged in advance, so that the replacement parts are prepared in advance and arranged for the most recent maintenance. Replace the tool.
Artificial intelligence has quietly settled in the industrial fieldIn 2017, in BAT and AMG, Ali ET Industrial Brain was the first artificial intelligence to go down to the workshop. As the first manufacturer to adopt cloud computing services provided by Ali, photovoltaic material manufacturer GCL has increased its yield by 1% and saved hundreds of millions of dollars annually. The cooperation between GCL-Poly and Alibaba Cloud is an innovative demonstration in China's industrial manufacturing industry. The first thing Alibaba Cloud does in the manufacturer's workshop is to put the data of all ports on the production line into the cloud and then mobilize thousands of servers. Calculate the power, and find 60 of the thousands of variables that affect the yield rate in a short time. Next, artificial intelligence is used to monitor and control these variables in real time, and the production line can be “as orderedâ€.
In fact, companies that quietly deploy artificial intelligence in the industrial field have already emerged. As a pioneer in the development of the automation industry, the foresighted giants have seen the advantages of digital transformation and have begun to lay out artificial intelligence platforms in the industrial field.
Siemens - Siemens Central Research Institute recently demonstrated a part of a two-armed robot in Munich. With the high degree of automation of artificial intelligence, the robot can work independently for product manufacturing without programming. Dr. KaiWurm of Siemens Academia Sinica said, “We just need to tell the robot to install a part on the rail and it will do it.†As a simplified example, this task describes “single piece custom productionâ€. Connotation. This involves processing or assembling a diverse range of products with different components. The robot obtains information about the manufactured product 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 as if the robot can understand different languages ​​so that it doesn't have to program its motion and craft.
GE - Recently, General Electric announced a multi-year agreement with a number of electrical companies and reached a broad agreement with the New York Power Authority (NYPA) to become the world's first fully digital power company. Today, GE's comprehensive intelligence operations center for predictive analytics software is open, a state-of-the-art asset monitoring and diagnostic center. Among them, GE and Enel will deploy and optimize GE's Asset Performance Management (APM) software, which runs on GE's Industrial Internet of Things (IIoT) platform, Predix, to monitor, predict and improve 13 gas-fired power plants and 1 coal-fired plant. Power plant reliability, these 14 power plants use GE or Alstom turbines and generators. General Electric CEO Russell Stokes said, "In the future, GE will transform its operations to achieve greater operational efficiency and create more revenue for its factories through digital transformation."
Rockwell Automation - Not long ago, Rockwell Automation also revealed its ambition to occupy a place in the field of industrial artificial intelligence. On November 3, 2017, it announced the investment of a Silicon Valley Innovation Fund and co-creation studio called TheHive. With an ecological environment consisting of innovative groups and high-tech start-ups, we are committed to applying artificial intelligence (AI) to industrial automation. ElikFooks, senior vice president of enterprise development at Rockwell Automation, said, “We continue to build partnerships with leading innovation groups, such as our partnership with TheHive to further drive the vision of connected companies, through plant and business operations. Industrialization pushes industry productivity to unprecedented heights.†Rockwell Automation’s efforts include helping manufacturing customers eliminate plant-level and higher-level information systems by creating customer solutions, accelerating innovation and discovering emerging technologies. The barriers that improve business performance.
From "artificial intelligence" to "industrial intelligence"Intelligent technologies from the computer and Internet industries are sweeping across the world in an unstoppable momentum. The combination of intelligence and industry has attracted worldwide attention. From German Industry 4.0 to the US Industrial Internet, from GE's Predix to IBM's PMQ, it can be seen that the combination of industrial and intelligent technology is bound to be the next cusp.
The core of intelligence lies in decision making and execution, and the core of decision making lies in perception and judgment. In industrial systems, IoT technology, as well as sensor technology, data transmission, data management, etc., continue to develop, providing a reliable basis for the realization of intelligent technology. However, most of the current industry is centered on people's 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, the slower the learning curve of people, and when the learning curve of people is slower than the progress of technology, people will become the bottleneck restricting technological progress and application. The first revolutionary change that artificial intelligence 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.
Artificial intelligence will become one of the most popular keywords in 2018. For the future of artificial intelligence, it has been revealed to us in many science fiction movies. But so far, the application of artificial intelligence in the industrial field is not as mature as the Internet, and it needs to be deeper in the future. With artificial intelligence to fully realize the intelligent operation of the plant, operators can minimize the manpower and continuously improve the manufacturing quality.
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