AI Boosts Intelligent Manufacturing into a New Stage

Science Popularization Times reporter Chen JieWith the deep integration of new generation information network technology and manufacturing, advanced sensing technology, digital design and manufacturing, robots, and intelligent control systems are increasingly widely used, promoting the intelligent development trend of various links in the manufacturing industry. Traditional manufacturing enterprises want to solve the development problems of low Gross margin, low added value and high labor cost

Science Popularization Times reporter Chen Jie

With the deep integration of new generation information network technology and manufacturing, advanced sensing technology, digital design and manufacturing, robots, and intelligent control systems are increasingly widely used, promoting the intelligent development trend of various links in the manufacturing industry. Traditional manufacturing enterprises want to solve the development problems of low Gross margin, low added value and high labor cost. Only by opening up production and manufacturing links and expanding operation services downward through digitalization, can the intelligent transformation of the whole factory be realized, so as to further improve the added value of the manufacturing industry.

At present, the digitalization level of China's manufacturing industry is not high. Although there are also some intelligent transformations, the exploration of data value is not deep. The main reason is that the transformation of manufacturing enterprises is a systematic project, and coupled with the lack of talent and technology, the transformation is more difficult. Wang Chao, a researcher at Wenyuan Think Tank, told reporters that the widespread involvement of AI technology will be a variable, It can provide all-round support for Digital transformation of manufacturing enterprises, help enterprises improve production efficiency, optimize supply chain management, improve product quality, innovate business models, and respond to market competition.

The Pain of Transformation for Manufacturing Enterprises

In the face of the digital flood, a considerable number of manufacturing enterprises actually do not want to transform, but they do not know how to, or even dare not.

Wang Chao said that manufacturing enterprises themselves are good at production and manufacturing and master advanced commodity production processes, but they do not understand new technologies such as artificial intelligence, Big data, cloud computing, and it is difficult to use data to feed back production and operation; The manufacturing industry has to do a lot of "dirty and tiring work", and the gap in labor remuneration compared to the internet and technology companies is very obvious, which makes skilled talents unwilling to engage in the manufacturing industry, and the manufacturing industry is facing a talent shortage; In addition, due to the lack of "genes" and talents in digital technology, manufacturing enterprises face numerous obstacles in promoting digital transformation, making it difficult to form internal synergy. "With the blessing of multiple factors, many enterprises want to turn but do not know how to turn when facing the tide of Digital transformation."

But in the irreversible tide, many manufacturing companies can only force themselves to follow the trend.

The Digital transformation process of manufacturing enterprises is complex, and the quality inspection of enterprises' products is often the first production link to be deconstructed digitally. According to relevant data statistics, quality inspection costs account for 20% to 25% of sales, and the overall market size in China is about 140 billion yuan per year. However, the market size that has already adopted intelligent industrial quality inspection machines is about 10 billion yuan per year, with a market share of only 7%.

In the past, quality inspection relied heavily on manpower and heavily on the vision and experience of quality inspectors. With the widespread intervention of digital technologies such as artificial intelligence, AI quality inspection has become the current mainstream. However, the general AI quality inspection plan needs to first undergo production line transformation, then accumulate data, train models, tune, and finally apply it to the production line. The overall deployment cost is extremely high, the training cycle is long, and the flexibility is poor, making it difficult to meet the flexible production needs of manufacturing enterprises.

At present, there are already many AI quality inspection solutions in the market, but most of them are limited to a single technology and cannot truly meet the needs of application points by integrating cross domain technologies. "AI technology fully enables Digital transformation of manufacturing industry, obviously there are still many problems to be solved." Wang Chao said frankly.

The Last Kilometer of Flexible Production

It may take time for AI technology to fully empower manufacturing enterprises to make Digital transformation, but intelligent manufacturing under its empowerment has gradually evolved from upgrading based on local intelligence capabilities to system engineering oriented to global intelligence, and the needs of enterprises have gradually transformed from product requirements to the needs of overall solutions.

Recently, Weiyi Intelligent Manufacturing has launched a full stack solution of "eyes, hands, brains, and clouds" with the main line of "industrial artificial intelligence+machine vision", which has attracted widespread attention in the industry.

The Last Kilometer of Flexible Production

The industry generally believes that the solutions based on visual AI have the characteristics of flexible deployment, low cost and high efficiency, which obviously meet the Digital transformation needs of manufacturing enterprises.

Ma Yuanwei said that how to use technology to apply data, optimize processes, improve efficiency and even generate new value points is the key to Digital transformation of manufacturing enterprises. Based on AI technology, solutions that can be quickly implemented can fully empower manufacturing enterprises with unified engineering from front-end to back-end, basic hardware to algorithm platforms, and promote the intelligent development of the entire process of the enterprise

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