How does industrial big data change manufacturing?

How does industrial big data change manufacturing?

Industrial big data is the product of the combination of Internet, big data and industrial industry, and it is the foothold of national strategies such as Made in China 2025, Industrial Internet and Industry 4.0 in enterprises. For the manufacturing industry, it is of great practical significance to understand the background of industry big data, summarize the classification and characteristics of industry big data, and view and recreate the industry value process from the perspective of data flow promoting its own value creation.

How does industrial big data change manufacturing? 1, manufacturing with higher precision and high success rate is the core competitiveness of manufacturers. Before the emergence of big data, the best way is to invest in better equipment or better train employees, but neither can greatly reduce the additional losses caused by failure rate. However, with big data, manufacturers can use computer programs to optimize processes and analyze errors more skillfully, thus preventing these errors. 2, higher output Most manufacturers buy raw materials and manufacture finished products, and their sales price is higher than the manufacturing cost. In this system, manufacturers can get higher profits (the less raw materials are used for each finished product), and the operation of enterprises will be more profitable. New big data applications enable manufacturers to better understand their overall output and have the opportunity to improve their operation methods and get more profits from their products. 3. Better forecasting Manufacturers can predict how many products they need to produce in advance according to various situations, reduce production in the off-season, and stock or ship them in the warehouse. Big data helps manufacturers to better grasp this change in supply and demand, so as to produce under the most valuable production conditions. 4. Predict and judge the advantages and disadvantages of suppliers' products. Manufacturers can also use big data to track the advantages and disadvantages of suppliers. For example, if suppliers provide a high proportion of inferior products and prove these things through big data calculation, it can be determined whether it is more cost-effective to choose new suppliers. 5. Higher traceability Big data also makes manufacturers' processes more transparent and traceable. How much is the loss of raw materials of the manufacturer in the production process and production stage? What is the output of a given batch and where is it currently stored? How long does it take to deliver the goods? Where is the product once it needs to be delivered? Big data can help manufacturers track all stages of production and delivery, and gain insight and analysis into areas that may be inefficient. 6. The big data of advanced customization shows that advanced customization can be created by obtaining data from previous efforts and creating ways to make better use of raw materials. It can also help manufacturers reverse engineer and propose new solutions to common problems. 7. Return on investment and operational efficiency Big data enables manufacturers to have a deeper understanding of the real efficiency of their operations and the return on investment (ROI) generated when upgrading, such as new equipment or new advertising strategies. What does this mean for manufacturers? The traditional manufacturing industry with higher profitability is limited by factors such as raw material cost and output limitation. With the emergence of big data, each production link can get more benefits and greatly reduce costs. Business owners can take advantage of these opportunities to earn more income. Greater competitive pressure As manufacturers adopt big data strategies, competitors feel pressure to adopt similar or even better methods. More and more competition forces more and more traditional manufacturers to upgrade their internal systems, so the future technological development will be more and more active. Demand for new roles Lean data application is very challenging for outsiders or people who are not familiar with data analysis. New technologies are impressive, but they need people with enough knowledge and experience to implement and manage them. So manufacturers need professional people or companies to help them complete these changes. At present, more and more traditional manufacturing industries are constantly upgrading with the popularity of big data. In the new era of fierce competition, will the changes brought by big data trigger a new industrial revolution? I believe all readers have their own answers.