New trends in manufacturing development in 2023

   In recent years, the global COVID-19 pandemic has made the manufacturing industry suffer from serious development obstacles. Fortunately, the data of the UN Industrial Development Organization in 2022 shows that the global manufacturing industry is entering a stage of strong recovery, with its growth rate reaching 18.2%. A survey of more than 200 top decision makers in global manufacturing companies found that 68% of them listed improving "flexibility" and "agility" as the top business priorities in the next few years. Here, I would like to share with you the key trends affecting the future development of the manufacturing industry.

  The concept of "smart factory" has a long history, but in recent years, people's interest in it has surged. In the past decade, the number of online searches for "Smart Factory" has increased by 93%

  Just as the first and second industrial revolutions were related to the rise of steam-driven mechanization and assembly lines, the Internet of Things, big data, machine learning, artificial intelligence and advanced analysis technologies adopted by "Industry 4.0" have witnessed the application of computers in the manufacturing industry, and "intelligent factory" is the key operating part of "Industry 4.0", which is changing Europe Production environment and workshop operation mode of manufacturing industry in North America and China. Taking the automobile industry as an example, according to the prediction of automobile manufacturers, by the beginning of 2023, about one quarter of the world's factories will become "smart factories", and by 2025, this number will rise sharply to 50%, and "smart factories" will create a value of 160 billion dollars for the automobile industry in 2023.

  Use "Predictive Maintenance" and Digital Twin Technology to reduce production errors.

In the manufacturing industry, the cost of equipment failure is often extremely high. For example, the compressor failure in an oil plant may cause a loss of 1 million to 2 million dollars per day, and unplanned downtime may cause a loss of 50 billion dollars per year to manufacturers. The combination of the Internet of Things and big data analysis can predict such failures very accurately. The data shows that "predictive maintenance" can reduce downtime by 30% - 50%, increase machine life by 20% - 40%, and reduce production costs by more than 30%. At present, 35% of the large manufacturers in the United States have adopted the "predictive maintenance" technology, and Airbus is one of the early users. In 2022, Airbus and GE cooperated to deploy complex predictive maintenance software based on artificial intelligence and machine learning to predict aircraft.

Another important sub-trend of "smart factory" is digital twinning technology, which can influence and make decisions for manufacturing objects by implementing the simulation behavior of data-driven virtual objects. "Digital Twin" can be a single component (such as automobile tires) or a product (such as the entire vehicle and all its subsystems, including software and thousands of components), or a complete manufacturing process (such as a factory containing many assembly lines and parts stores). The application scope of "Digital Twin" is to predict the life of products based on design (such as the life prediction of aircraft jet engines), To manage the whole plant and analyze and optimize production operation through simulation and assumptions.