Digitalization Of Textile Brain In Textile Technology

? From the more than 80 thousand varieties of fabric "needle"? This five hundred strong enterprise has created a "textile brain" by AI.

The fabric industry itself is a pattern based industry, which makes artificial intelligence based image recognition technology promising in this field.

How to find a needle from more than 80 thousand varieties of fabric materials? How to find tiny defects in the fabric of ten thousand counting units? From June 30th to July 1st, to 2018 snow wave conference, we have more topics on manufacturing field, and want to brainstorm with you!

From the perspective of resources, data is a new means of production for the sun, and its ultimate value is to maximize the value of other means of production. This is a view expressed by Dr. Wang Jian, the chairman of the technical committee of Alibaba group and the honorary mayor of Xuelang Town, when he visited Jiangsu sunshine group.

The so-called "other means of production" for the current sunshine group, the most typical is cloth. In the sunshine group party secretary and chairman Chen Lifen view, data barrier is a major obstacle to the spanformation of digital sunshine. If the data between clothing and fabrics, departments and departments, and between domestic and export markets get through, then the role of sunshine group and even the entire textile industry will be immeasurable.

It is worth mentioning that the term "immeasurable" has been stressed three times by Chen Lifen. It can be seen that data have a new meaning for sunshine.

At present, most of the textile enterprises in China belong to small and medium-sized enterprises. Most of these enterprises lack full application of information technology and Internet talents. Data island phenomenon is serious. The linkage efficiency of each link in the industrial chain is low, resulting in overstock and delay in delivery. With the rapid development of new technology, a small number of enterprises have created industry myths through the unique big data system and corresponding process changes. There are also large scale customized production processes, making the value of the data enlarged. It is becoming more urgent to optimize the industrial chain and forecast the market demand and reasonable pricing of textile products in the future.

The sun is also groping ahead in the flood of data revolution. At the research site, Chen Lifen presented Dr. Wang Jian (and Xuelang number) three points of pain that the sun needs to solve at present. In fact, it also represents the common problems of most textile and garment enterprises: how to reduce or even eliminate sample proofing? Two, how to reduce inventory? Three, how to achieve customized production in the garment industry?

Digital spanformation from fabric to hand

　　 Fabric The industry itself is a pattern based industry, which makes artificial intelligence based image recognition technology promising in this area.

When it was first established in 1986, the sun group is still a nameless town run wool mill (formerly known as Jiangyin fine wool mill). Now the sunshine of the year has long been a famous wool textile production enterprise and high-end garment production base in the world. Its products are 50% domestic market and 50% overseas market. But with the rising cost of raw materials and the disappearance of demographic dividend, technological spanformation has become the only choice for these enterprises to break through innovation.

The digital spanformation of sunshine group can be said to start with fabrics.

In the textile industry, after ordering, it is necessary to first sample, first design the process of the sample, then collect the raw materials, and then produce the products according to the technological process, usually after dyeing, re combing, spinning, weaving, repairing, dyeing and finishing, and finished product inspection. So proofing is actually a process of "setting standards". Once the sample is confirmed, the whole process and every process will be solidified.

According to Chen Lifen, the average cost of a proofing is about two thousand yuan. The problem is that proofing is not done once, and customers sometimes need to confirm it again and again. From wool dyeing to finishing, one proofing takes about a month, and two times is two months. In this year, about 6000 proofing is done, and the cost is about 12 million. In addition to direct costs, proofing is also a "hidden cost" that disrupts the efficiency of the entire assembly line process.

"If you can" figure out a map ", you can find the basic data and file data of the cloth before, and even if it is similar data, it can be called directly, so that the delivery time can be shortened for at least one month.

Chen Lifen referred to the "map to find the map", in fact, is to take the sample pictures given by the user, through the artificial intelligence image recognition function to find flowers, flowers and materials with the highest similarity in the warehouse.

Such seemingly simple behavior, without technical support, will be too heavy to imagine. Because in the information warehouse of sunshine group, there are about more than 80 thousand species of fabric materials lying on the floor. Finding similar cloth from it is like looking for a needle in a haystack.

"So customers are constantly coming to the market, and the company needs to keep sampling. Two times, three samples are wasted. But in fact, there are ready-made in the warehouse, sometimes the guest wants 300 meters of cloth, the storehouse has 300 meters, does not need to do at all.

Chen Lifen also talked about an incident that had just touched her a few days ago. A brand dealer needs a special fabric. Chen Lifen remembers that there are many in the warehouse. But when she got to the warehouse, she was dumbfounded. Everyone said that the material was indeed available, but it was impossible to find it, because the system did not get through. The fabric warehouse and the clothing warehouse system did not get through, and the domestic sales warehouse did not get through with the export warehouse, and the code was not shared, which made it very difficult to find.

"Although there are two dimensional codes on each package, only after scanning is it known. And clothing production involves many links. Sometimes cloth stores sometimes exist in clothing stores, sometimes in fabric stores, or in some intermediate links in the workshop. This should be a common pain point in the industry. " Chen Lifen said helplessly.

Although it was discovered by memory later, it also made Chen Lifen determined to dredge up the sunshine data and build a big data processing system similar to the ET industrial brain. In this system, there are not only basic data and archival data of cloth, but also information about production process data, recipes, raw material specifications and so on. At the same time, integrating upstream and downstream enterprises, such as clothing companies, materials companies, etc., has become a shared service platform for an industry.

For these more than 80 thousand varieties of fabric, Chen Lifen intends to put FRID chip labels on them in the future. In this way, when you look for a picture again, you just need to compare the photos on the computer, and through the image recognition technology of artificial intelligence, the background will show where and where the fabric is produced. "100% of the best similarity, or 90%, 80%, even if sixty or seventy of the similarity, can also" crack "from the system to tune away, direct use.

The immediate effect is to clear up the stock. According to Chen Lifen estimates, more than 80 thousand varieties of fabric inventory is less than 3 million meters, if the price of 100 yuan per meter to calculate, that is 300 million yuan!

"If the system is applied to other enterprises, and even the whole industry, the benefits will be immeasurable." Dr. Wang Jian said.

Another typical application scenario of AI image recognition technology is finding flaws.

In the domestic textile industry, the original grey fabric and the final product defect detection are still in the manual detection stage. Manual detection often has many shortcomings, such as slow speed, high detection rate and poor continuity. Therefore, replacing people with machines to find defects becomes the common demand of the industry.

In the sunlight, the work of finding defects requires 2 people to complete. One is responsible for finding, another is responsible for marking, recording data. There are three ways to detect defects: billet inspection, intermediate inspection and final inspection. After the inspection, a supplementary repair is necessary. Among them, the defect of billet inspection is the largest, almost half of it can be filtered.

Chen Lifen estimates that according to the current tens of thousands of kilometers of fabric production in the sunshine, there will be nearly 1 million defects. To accomplish so many quality inspections, the current use of sunlight is almost 7 or 80 manpower.

"If a machine is used to replace a person, and the image recognition technology of artificial intelligence is used to find defects, two people save at least one person, leaving a person marking. That is to say, save 50% of manpower.

Under the big cargo scenario, how to achieve small batch customized production?

Before the titanium media visited the manufacturing enterprise, it was found that the highly personalized products of the product are generally encountered with a common problem: what is the product with many orders and small batch production, and what are the good solutions? This is also a problem encountered by the sun group.

In the sun, the customized production of big goods has always been a barrier to the past.

The so-called big goods, that is, the relatively large volume of products, these customers are relatively stable, the contract is signed for 35 years, but the characteristics are lots of order batches and short delivery time, which has caused great distress to the original production process, and on the other hand, it also caused the asymmetry of R & D information.

Sunshine customers include HNA, China Eastern, Air China, Xiamen Airlines and other airlines. These airlines will make their orders almost once a week. Take East China Airlines, orders for many times a month, a set of orders less than 3-5 sets, more than a dozen sets, and airlines because of the large flow of personnel, flight attendants training for up to two months on the job, which means that 2 months must be delivered, which led to the pipeline on the East China Airlines is a list, and later is HNA's list, the entire production scheduling, scheduling, scheduling and so on, we need to constantly adjust, not only inefficient, delay in delivery is also common.

But there is also one advantage of these big goods, that is, the styles remain unchanged for a long time, and basically remain in the three regular numbers of S, M and L. Chen Lifen said that if the data can be used to analyze the quantity and frequency of orders per year, the number of garments with different specifications, and the most frequently used styles, sunlight can be prepared in advance. In the case of stable data, sometimes even one year's inventory can be prepared.

"This order can be reduced to once a month or even once a year, and the efficiency of production lines will also increase significantly. Of course, if the data shows that the number of shipments is decreasing and the order batch is decreasing, we will pay attention to whether the other person wants to change the payment. For example, Hainan Airlines, historical data show that three years to replace it, then we can go to third years to automatically reduce the stock.

Another point of pain in customized production is professional wear. Professional wear is also the main product of sunshine. Since 2000, the sun has launched a series of brands such as Venetian's tailored clothing and Pompeii professional wear, among which the annual sales of Pompeii are over 1 million 500 thousand.

Compared with ordinary clothing, the biggest feature of professional wear is that the size of each person is quite different from body size. This makes the requirements of volume, board and tailoring extremely harsh. In particular, the size of the volume, the details of the control is very strict, from the pocket width, to the precision of the neckline sewing, data has accumulated hundreds of thousands of pieces.

Such fine volume data means that cutting must also be very precise. In the sunlight, the cutting is done in two times -- wool scissors and fine scissors. For example, now the production of 10 thousand sets of clothing, age from 18 to 60 years old, then only men's clothing needs 60 models, women's clothing is also, there are many other special features. The men's dress adds up to almost more than 120 samples. When cutting, the similar specifications need to be filed, and each file will be completed through two tailoring. For hair scissors, keep 1 centimeters of -0.5 centimeters with the template, and then fine cut. Such a set will probably cut off 5 centimeters of cloth.

"If the annual output of 2 million 500 thousand sets is calculated, savings of one centimeter is 25000 meters cloth, and the cost of 1 yuan is 100 yuan, which is 2 million 500 thousand. 5 centimeters down is 12 million 500 thousand loss. " Chen Lifen said.

In addition to fabric loss, manpower loss can not be ignored. There are three main points in this respect: one is skilled manual labor, the other is slow speed. clothing The fit rate will be greatly reduced.

Chen Lifen said that the current volume of data in the sun has not been well analyzed and processed, the future hopes that through these data integration and mining, the formation of standardized typesetting specifications, and then with automatic cutting technology to achieve one-step precise tailoring, will greatly reduce. Fabric Loss, save manpower cost.

"So this is the typical problem of using data resources to exchange other resources." Dr. Wang Jian said. From the point of view of resources, if data link can not reflect the efficiency of resource utilization of the entire enterprise, digitization becomes a matter of informatization for informatization.

Chen Lifen hopes that the digital innovation of sunlight can precipitate data and technology to form a textile brain, which can provide services for the whole industry and enhance the competitiveness of the whole industry.