What Potential Value Will Industrial Data Classification And Classification Release

Recently, the Ministry of industry and information technology issued a notice and a list of pilot enterprises to carry out the pilot application of industrial data classification and classification. Among them, there are nine textile and garment companies, including black peony Textile Co., Ltd., Anhui Huamao Group Co., Ltd., Shandong Huaxing Textile Group Co., Ltd., Jiangsu Dasheng Group Co., Ltd., Jiangsu Hongdou industrial Internet Co., Ltd., Shaoxing English printing and dyeing Co., Ltd., Wuxi Yimian Textile Group Co., Ltd., anlifang (China) Garment Co., Ltd., Lutai Textile Co., Ltd Enterprises have become pilot enterprises of industrial data classification and classification application.

In order to realize intelligent production, textile enterprises need the effective combination of machinery, textile, automation, computer information and other disciplines and technologies, complete the interconnection of different types and functions of intelligent single equipment, and form a new flexible production mode. That is to form a complete mode integrating intelligent management, intelligent workshop, intelligent logistics transportation, product management and after-sales tracking, and forms an intelligent management system through intelligent planning, intelligent production scheduling, intelligent monitoring, real-time cost analysis, market analysis and intelligent decision-making. All of these need data collection and management as support.

It is understood that the Ministry of industry and information technology issued the industrial data classification and classification guide (Trial) in March this year to guide enterprises to improve their industrial data management capabilities, promote the use, flow and sharing of industrial data, release the potential value of data, and enable the high-quality development of the manufacturing industry.

Data driven improves efficiency significantly

The enterprises selected in the industrial data classification and classification application pilot list of the Ministry of industry and information technology are all enterprises with good integration of industrialization and industrialization in the industry, and have actively explored the construction of intelligent management system.

Shaoxing Yingli printing and dyeing Co., Ltd., located in Keqiao District, Shaoxing City, Zhejiang Province, has a small production scale, but the enterprise has been actively exploring the road of intelligent printing and dyeing.

In August last year, the "Textile Industry Internet platform" developed by Beijing Digital Technology Co., Ltd. was fully launched in English printing and dyeing. This "industrial Internet platform" called textile brain makes the whole production process of English printing and dyeing truly digital. Just click the mouse and select a dyeing machine cylinder, and all the real-time working condition data of the cylinder will be displayed in a table or bar chart. The manager can also quickly judge what is wrong with a certain cylinder through the deviation range of production curve and specific parameters on the screen.

Wang Wenjun, general manager of English printing and dyeing Co., Ltd., introduced that after the "intelligent printing and dyeing" system of digital technology was put on line, the number of washing cylinder was reduced by more than 45%, and the equipment utilization rate was also significantly improved. "In the past, we used to do single production scheduling manually, which often took an hour. Now it only takes a few minutes to complete it quickly. In particular, in case of special circumstances such as inserting orders, the high-quality and efficient production scheduling adjustment can be completed within 5 minutes, and the cost of energy consumption, cylinder washing switch and labor force can be significantly reduced, and the cost can be directly reduced by at least 1 million yuan / year. "

Compared with the traditional manual operation mode, the cost of manual operation of the terminal is obviously reduced by 80%. The current basic data is consistent with our actual business situation. Today, the production schedule is real-time and transparent, and the risk can be early-warning in time, and the efficiency of the whole plant work is significantly improved under the drive of data. "

It is reported that the most important solution to solve the problem is to combine the technology of intelligent manufacturing and digital printing and dyeing, such as the four major technology providers, such as intelligent manufacturing and ERP, focusing on the overall cost of the textile industry "Can monitor" and "smart energy" and other new generation of technology products, to truly achieve the digital goal of reducing costs and increasing efficiency.

According to Huang Fuxin, vice president of Beijing Digital System Technology Co., Ltd., an enterprise with an annual output value of 200-500 million yuan, such as English printing and dyeing company, can directly increase the benefit of 5-8 million yuan per year through intelligent management system to improve efficiency and reduce costs.

The realization of intelligence needs to play a greater role of data

Shandong Huaxing Textile Group, also listed in the list of industrial data classification and classification application pilot list of Ministry of industry and information technology, cooperated with Samsung Group SDS company and Zhengzhou Tianqi automation system company to develop the first domestic intelligent textile system.

This system uses big data, cloud computing, Internet and other technologies to realize the visual monitoring of each process and operation point. Customers can know the progress and quality of orders through the Internet in real time. At the same time, the system can transfer and analyze real-time data, and guide production management in reverse by data analysis. It realizes a management platform integrating remote monitoring of production status, automatic generation of production report, real-time monitoring of quality data, real-time tracking of orders, seamless integration of ERP (Enterprise Resource Planning System) and other functions, so as to realize the networking and integration of the whole production process High production efficiency and management refinement level.

After the implementation of Shandong Huaxing intelligent spinning system, remarkable results have been achieved: it can effectively improve the production efficiency by 20%, shorten the product production cycle by 30%, accelerate the turnover of work in process inventory funds, and achieve indirect economic benefits of 10%; the enterprise employs 15 people per 10000 spindles, reducing labor costs by 80%; increasing the energy utilization rate by 12%; the application of intelligent cotton blending can reduce cotton blending grade by 0.5 on average, The cost of cotton consumption is greatly reduced, and the comprehensive operation cost of enterprises is reduced by 20%. In addition, after the implementation of the project, it can effectively reduce the occupation of inventory funds and WIP materials, reduce the inventory fund occupation by 10%, and effectively save the financial cost. Comprehensive analysis shows that the implementation of the project can improve the profitability of the enterprise in many aspects, and the labor productivity of the whole staff can be greatly improved, and the average profit of the enterprise can be increased by about 30%.

In the opinion of Hu Guangmin, chairman of Shandong Huaxing Group, the most important thing in the application of intelligent textile system is to change the original management mode and thinking of the enterprise, so that people, equipment and software systems are integrated and interconnected.

He believes that the core of intelligence should be the integration of intelligence and ability. Today's intelligence has achieved "intelligence", that is, using technology and other means to collect a lot of data. However, data is only a means, and repeated use of data is intelligent.

Guangmin also encountered many problems in its implementation. For example, hundreds of different types of production host and auxiliary equipment are automatically controlled by a variety of controllers. And many equipment manufacturers encrypt the device data port or the communication protocol of each device is different, which makes the data of various devices unable to be obtained or the information transmission between devices is blocked. "In order to achieve real intelligent spinning, we must know what features our equipment has, whether the front and rear processes can match, whether the data can be opened, whether the open data can meet the requirements of the intelligent spinning project, and how the protocol of the communication interface is. The data required to be obtained is the original data, not the processed data. These are the requirements of intelligent spinning project, otherwise it is difficult to realize the meaning of intelligent spinning Hu Guangmin said.

It is understood that due to the low degree of automation and intelligence in China's textile industry, there will be some difficulties in the implementation of intelligent system: first, it is difficult to integrate specialization and informatization. It is difficult for textile enterprises not to understand the technology of it and the automation of textile industry. Second, there is no complete set of intelligent system for all enterprises. Each textile enterprise has its own characteristics, it is difficult to have a complete set of ready-made intelligent system can be used directly, otherwise there are incompatible and incompatible problems. Therefore, textile enterprises need to build intelligent system according to the construction ideas and their own characteristics.

Data classification and classification promotion and deep integration of manufacturing industry

According to the guide to classification and classification of industrial data (Trial), the goal of industrial data classification and classification is to improve the ability of enterprise data management, adhere to the combination of problem orientation, goal orientation and result orientation, the combination of enterprise subject, industry guidance and territorial supervision, and the combination of classification identification, classification grading and hierarchical management.

Enterprises combine production and manufacturing mode, platform enterprises with service operation mode, analyze and sort out business processes and system equipment, consider the actual situation such as industry requirements, business scale, data complexity, etc., classify and identify industrial data, and form a classified list of enterprise industrial data. According to the potential impact on industrial production and economic benefits after different types of industrial data are tampered with, damaged, leaked or illegally used, the industrial data are divided into three levels: Level 1, level 2 and level 3. Enterprises are encouraged to share primary and secondary data properly on the premise of data management, so as to fully release the potential value of industrial data. Secondary data is only available to authorized institutions and relevant personnel who really need to obtain such data. In principle, the three-level data shall not be shared. If it is necessary to share, the scope of knowledge shall be strictly controlled.

It is of great significance to carry out industrial data classification and classification, which is reflected in the following aspects: first, it helps to strengthen the enterprise's awareness of data application, guide enterprises to carry out data management and enhance data application awareness by carrying out data classification and classification, which is conducive to enterprises to comprehensively sort out their own industrial data types, promote full use of data, global flow and orderly sharing, and comprehensively improve the number of enterprises According to management ability and understanding of the importance of industrial data. Second, it is conducive to improving the level of industrial data management and application. It is necessary to speed up the integration of data acquisition and data sharing, and to promote the development of data mining and data sharing Height. Third, it is conducive to promoting the implementation of industrial data classification and classification from the operational level. The guide provides strong policy guidance and theoretical basis for enterprises to effectively excavate data value and accelerate the transformation of production mode in the industrial field. It also clarifies the main responsibilities and relevant requirements of enterprise classification and classification, as well as the responsibilities of local industrial and information competent departments, so as to facilitate the deficiencies in data management of benchmarking tables, improve the ability of enterprise data management, and effectively mine data value and realize Enterprise production mode transformation.