Automation and intelligent transformation are just the right time, and the manufacturing industry is moving forward with "number"

The application of intelligent manufacturing network big data in manufacturing industry includes many small scenarios. From all aspects of the product life cycle, including design, manufacturing, service, marketing and reuse, there will be big data in every link. The data collected in the "complete" life cycle is diverse and complex. With big data technology, manufacturing can increase the number.

supply chain

With the continuous development of modern supply chain, it has become more and more complicated. Big data analysis solutions can provide supply chain visibility, and instantly know all kinds of information of key supply chains, such as which suppliers are performing well, the type, cycle and quality of their products, and how strong their ability to deliver orders on time.

With the support of big data technology, manufacturing enterprises can put a unique radio frequency identification code on each product, and record the production, packaging and other data of the product in the whole production process through this radio frequency identification code. Once defective products appear, engineers can use these data to check the whole production process, quickly find the defects in the production line and improve them, thus greatly reducing the defective rate.

Electronic identification technology of products such as RFID, Internet of Things sensing technology and terminal cloud sharing technology can help manufacturing enterprises to obtain complete product supply chain big data. By analyzing these data, factory managers can actively change the manufacturing and circulation mode of products, thus promoting the efficiency of warehousing, distribution and sales and reducing costs.

Demand chain

Big data is a good sales analysis tool. Through the multi-dimensional combination of historical data, we can see the proportion and change of regional demand, the market popularity of product categories, the combination form of product marketing recognition and the change of consumer demand, so as to adjust product strategy and distribution strategy.

In the demand chain, big data analysis not only brings more value to enterprises, but also puts forward higher requirements for skilled talents of enterprises. Because big data analysis is non-traditional data analysis, traditional data analysis may rely on tables for analysis, while big data analysis is a professional analysis of messy, massive, messy and diverse data, which requires professionals to integrate, analyze and call the data, so as to give full play to the value of all kinds of data.

With the support of big data technology, enterprises can also use sensing technology and automation technology to improve the intelligence and networking of product production, integrate traditional manufacturing and high-end service industries, and further improve the competitiveness of enterprise products. Big data can provide multi-faceted and refined services for the manufacturing industry. From product design to manufacturing, from use to maintenance, from online promotion to offline display, diversified forward data and reverse data will be fully applied in manufacturing supply chain and demand chain scenarios, and applications such as intelligent factories, intelligent robots and intelligent warehousing will not be far off.

Summary:

Big data technology can collect, count, analyze and process massive data information, providing important reference for people's information feedback, urban construction, business activities and public decision-making, and can be widely used in the fields of finance, commerce, education, medical care, management, electronics and so on.

However, in the face of serious data islands, backward data collection methods, lack of a unified data resource management mechanism, and lack of application standards in the big data industry, all parties should pay attention to it, especially stepping up legislation and norms on data privacy and data security.

Applications and services centered on data mining and data analysis can undoubtedly lay a solid data foundation for social and economic growth. Looking ahead, big data will not only change people's thinking patterns at different levels, but also change many people's original lifestyles and business service formats.