Data management has become the core competitiveness of enterprises, directly affect the company's financial performance when the "Data assets are the company's core assets" concept deeply rooted in the hearts of people, business data management have a more clearly defined, data management as the core competitiveness of enterprises, sustainable development, strategic planning and the use of data assets become the core of enterprise data management. Data asset management efficiency and main business revenue growth, sales growth was significantly positive correlation; In addition, for enterprises with Internet thinking, competitive data assets accounting for 36.8%, asset management performance data will directly affect the financial performance of the enterprise.
Smart era requires deep integration of information technology and manufacturing, driven by big data technology, the manufacturing industry will usher in a comprehensive transformation and upgrading, to intelligent manufacturing industry. So, how big data will promote the transformation and upgrading and development of intelligent manufacturing industry? According to the data analysis, the development prospects of intelligent manufacturing can be summarized as the following two aspects.
1. The supply side: digital process monitoring, protection of product quality
In the era of large-scale manufacturing, quality control production lines are usually arranged at the end of the link, in order to guarantee the quality of removing defective. However, due to the lack of effective, digital production process monitoring, engineers need to look far to find out the causes of defects, coupled with the causes of the last products vary, so the traditional manufacturing enterprises in order to reduce the defect rate it is very difficult.
With the support of big data technology, manufacturing companies can mark a proprietary radio frequency identification code of each product, and the product identification code recording data throughout the production process by the radio frequency. Once defects occur, engineers can troubleshoot these data for the entire production chain, identify defects and to improve the production line, thereby significantly reducing the defect rate.
Moreover, mass storage and cloud storage technology enables the production data retention for years or even decades, until the end of the product life cycle. After the product is sold, after-sales department of manufacturing enterprises can dynamically monitor problems of user satisfaction and use of the product with the product and recorded. These after-sales data can help manufacturing enterprises to further optimize the product design, provide the market with better, more durable, more intimate products.
2. Demand side: pinpoint market demand, mass customization
From the 1920s to the 1970s, "Fordism" and large-scale manufacturing was all the rage. Large-scale manufacturing can create enormous economies of scale, lower production costs and increase profits of large manufacturing companies. However, large-scale manufacturing but also the loss of individuality and diversity of products, "cookie-cutter" Although the product can meet the market demand in terms of quantity, but can not meet the needs of individual consumers. Especially after abundant material wealth, large-scale manufacture gradually declined.
From the 1970s to the early 21st century, Toyota Motor Corporation as the representative of "Toyota" system advocated precise positioning market demand, flexible arrangements and adjust the product line, to achieve "zero inventory", "low-volume" personalized manufacturing. However, the small scale manufacturing of personalized and can lead to instability in corporate profits, is not conducive to long-term development of manufacturing enterprises.
So far from the beginning of the 21st century, the US Apple as the representative of a new manufacturing methods "mass customization" gradually forming. "Mass Customization" by mining user data generated in the process of consumption, found that several of its most popular personalized product design, and then mass production based on these designs, and improvements based on user feedback timely.
Mass customization is the "mass production" and "personalized" custom combination of new products, is an internationally recognized manufacturing development direction, Big Data technologies can fully collect market data via the Internet and artificial intelligence algorithms, and thus the manufacturing sector enterprises to achieve mass customization, provides powerful data support and technical support.