Rewriting the Technological Scenario

On September 10, the state officially introduced "3 years of development recommendations of industrial upgrading", it is recommended that industrial upgrading needs more detailed, and it is necessary to focus on some technologies that have achieved initial results.

On the same day, the Great Breeze Group invited the domestic included car and electronic consumer goods to participate in a meeting on Yunzhi Lianlian + manufacturing.

The meeting was personally served by Meng Qian.

"Many old friends in these two days are called me. Suddenly, what is the purpose of such a meeting, after all, the Great Wind Global Developer General Assembly is less than 3 months.

In fact, because in the past two months of the Fourth Global Developer Congress, we communicate with more than half of the world's 500 companies in China, and make a complete summary and analysis for the details of all aspects.

In this process, we noticed that the world now knows that the next key development direction of our wind group is Yun Zhilian + manufacturing.

But now users have more understanding of this thing, such as smart home appliances, smart cars, but today you have come clear that Yun Zhilian + manufacturing is not simple to take out a smart product, give traditional products Smart systems and networked functions are as simple as.

Yun Zhipian + The fundamental purpose of manufacturing is to upgrade in the industry, so today, through the market situation of "recommended", we decided to invite everyone to come over and talk about this. "

Meng Qian said that this opened PPT, everyone's attention was also concentrated. "In the process of contact with traditional manufacturing companies at home and abroad, we have noticed some status quo.

The foundation of the traditional manufacturing industry originated from the large-scale standardized production of the industrial era, the management model is based on the pyramid, multi-level, subdivided, poorly flexible, and it is difficult to adapt to the manufacturing task of rapid changes and customer needs.

At the same time, there are too many fields in the manufacturing segment, and each subdivided industry standard is not the same. When Yun Zhilian enters the manufacturing industry, it will not talk about what standard.

For example, if we are most common, corporate workshops often have a large number of different manufacturers of digital machines and industrial automation products, design a variety of industrial Ethernet and fieldbus standards, manufacturers hardware and software are difficult to compatibility, traditional manufacturing This lack of relevant standards and complex production lines are hindering Yunzhi Union + manufacturing development.

So in order to adapt to Yunzhi Dian + manufacturing, almost all traditional manufacturing companies need to carry out a subversion.

However, this is a huge investment, which will involve a large number of equipment, software, and hardware updates and even modifications, long investment cycles, and short-term hard work.

We can see a meaningful data, from the beginning of this year, the company I negotiating Yun Zhilian + manufactured by the company has been more than 10,000, but so far, we will start the large-scale construction of Yunzhi Lianlian + manufactured enterprises Less than 200.

I don't know what I don't know when I see this data? "

Meng Qian deliberately stopped waiting for everyone to respond, only I don't know who said, I said that I have a long way, Meng Qian will continue, "Yes, it is really a long way, so when I first saw this I didn't sleep almost a night during the report.

Because we have contacted a global manufacturing company, we collect the global manufacturing information. We have drawn a global manufacturing conclusion, that is, this hesitation is not only the exclusive issue of our Chinese manufacturing industry, but the world. The common attitude of the manufacturing industry. "

Meng Qian said that this, many people's eyes began to change, "I want to think about it. Isn't this our chance? When others are alleged, it is not the opportunity to come.

Of course, the premise is that the technology is worth convinced, so I will show three successful applications from practice itself today, which is the application of Yun Zhilian's success and mature application in manufacturing.

The first is intelligent detection.

In this exchange of international automobile giants, our intelligent detection became the focus of concern in the whole industry, and the manufacturing process of the industry is extremely complex, and the online test task is abnormal.

But everyone has always been manually detected, and the results are obvious, and the accuracy of manual identification is very limited. It does not see the error, and the detection speed is also slow.

Coupled with the detection of workers' fluidity, experience is difficult to accumulate, major cars must invest a lot of funds every year.

However, our strong wind group has achieved a very significant effect in BYD and Geely Factory. We record the production process through industrial camera, and give video to artificial intelligence for machine detection.

At first, our artificial intelligence needs to double inspections with workers to achieve double insurance purposes, and as artificial intelligence continues to accumulate inspection experience, deep learning begins to play a clear role.

As of now, the artificial intelligence we used in BYD has replaced 50% of workers, and the detection rate of non-penetration products is as high as 86%, and this data is continuously optimized as the accumulation of experience is continuously optimized. "

Meng Qian said that this start video display intelligent detection in BYD's application, give you a more intuitive feelings.

"Second, mature technology applications are intelligent maintenance, and there are factories that have the importance of equipment maintenance, but all of the traditional factory is basically passive maintenance, and other equipment have issued problems.

Now that we create artificial intelligent intelligent maintenance can use machine learning to achieve equipment maintenance warning, we also have a case here. In the process of cooperation with Gree Plants, the number of apparatus has decreased by 51%, system diagnosis and maintenance The response time is less than 1 hour.

Not only shortening the equipment maintenance cycle, but also improves equipment utilization. "

Next, it is naturally a video display. "Finally, let's talk about the third intelligent application to see the results, that is, the intelligent supply chain.

In the process of globalization in China, we not only recognize the importance of the vertical industry chain, but also feel the importance of the supply chain.

This neon thing believes that many companies have brought a positive impact, and many people are in the curious wind group, why didn't seem to have affected in this event.

Today, I also responded to this problem in my first time. In addition to our high deflation rate on the industrial chain, the key to this incident can be such a seemingly relaxed response is because we create the intelligent supply chain internally system.

Traditional supply chain management, traditional supply chain management, has shown very obvious defects in our globalization, low efficiency, high circulation cost, no prediction of demand, insufficient supply response, dealing with supply chain fluctuations, Vendor's inventory management cost is high.

When we let the machine learning into the supply chain management, artificial intelligence can effectively establish a real-time supply chain matching relationship through analysis of demand, plan, and inventory, we have established multi-level stocks, plan production inventory dynamics Semi-automaticization of even procurement and replenishment.

Through the video, we look at the video. In this neon incident, our intelligent supply chain system gives us the first time to propose materials procurement programs, global factory production programs, and adjustments to market supply planning and future in the world. Supply and demand forecast.

We passed this system feedback in the first time to clarify different cities in different countries to supply and sell the sales target, timely dispatch, and maximize the impact of neon incidents on our company. "

Meng Qian's intelligent supply chain system showed these manufacturing companies that they were in both eyes.

"Everyone see this, is it more interested in cloud smart + manufacturing?" Meng Qian asked with a smile.

Nice to everyone's consciousness.

"Then let's get our core technology of Yunzhi Dian + manufacturing, which is semiconductor chip, core equipment components, core software, and core algorithms.

Now, we have confidence that we can fight with the core algorithm and software, and the overall industrial semiconductor is still behind, while the biggest gap is now on the core industrial equipment.

Is everyone confirmed that we judge? "

Everyone nodded again, Meng Qian nodded, "Obviously, Yun Zhilian + manufacturing is inseparable from these four cores, so after three successful application cases, we come from these four cores. The status quo of this technology. "

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