After three decades of Bentley Microstation fast expansion, China's industrial sector has achieved tremendous successes, but there are still a number of obstacles ahead. Countries all around the world have started new developments and transformations in industrial intelligence and digitalization at the same time. Deloitte predicts that three key trends will dominate China's manufacturing sector over the next ten years: rising business growth, international development, and digital smart manufacturing. One of them, digital smart manufacturing, has the potential to launch a new industrial revolution and change the global economy. In China, it will assist the country's manufacturing sector in reaching a turning point. In order to achieve this, the Chinese government has released "Made in China 2025," which aims to take advantage of the wave of Industry 4.0 to encourage the thorough fusion of information technology and industrial technology and to realize the transformation from the first manufacturing power to the world's manufacturing powerhouse.
To make up for the shortfall in industrial automation and CDE Solution provider informationization, as well as the status quo reasonable growth of intelligent manufacturing fit for their own firms, Chinese enterprises must, however, accelerate this process.
Currently, a new generation of CDE solution information network technology and manufacturing industry in-depth integration, advanced sensing technology, digital design and manufacturing, robotics, and intelligent control systems are used more and more frequently to promote manufacturing research and development, design, production process, enterprise management, and even user relations are showing intelligent trend, mass customization, and personalized customization is becoming more and more popular.
First, the growth of digital technology into the manufacturing sector. With the rapid development of mobile payment, e-commerce, online shopping, live video broadcasting, smart logistics, and other new forms and modes of business, the digital transformation of China's consumer sector has recently become more active. This has encouraged the matching of supply and demand in time and space, reduced transaction costs, and unleashed enormous consumer potential. Future-oriented digital and intelligent technologies, such as 5G, the Internet of Things, big data, and artificial intelligence, have facilitated a deep integration of digital technology and manufacturing, created the intelligent manufacturing mode of human-machine integration, and fostered the growth of new integration and development paradigms, including digital design, intelligent production, networked coordination, and service extension.
Second, the building is being accelerated by the industrial ecosystem based on the industrial Internet. If the last time saw China's rapid consumer Internet expansion and the emergence of several major international network platform enterprises, the next period will see the rise of the industrial Internet wave. Industrial Internet is playing a bigger and bigger part in enabling manufacturing firms, and it's gaining center stage as a brand-new method of production.
Thirdly, digital technology enables the manufacturing sector's transition to a low-carbon, environmentally friendly economy. The application of artificial intelligence, big data, cloud computing, and other technologies, along with the real-time collection of operational data, strengthened data analysis, and value mining, to achieve precise demand forecasting, remote monitoring of equipment and energy management, and fine management of industrial enterprises' processes, manufacturing, logistics, and other links, can successfully reduce energy consumption and carbon emissions. Digital technology can lower carbon emissions by more than 20%, according to certain research.
The following are the primary areas of pain for the manufacturing industry when it comes to data management and data applications:
"Difficult to deal with" are historical issues.
The construction of many of the Group's historical systems is not standardized due to historical factors; there is no single standard to serve as a guide, upgrading and transformation are difficult, and there are numerous barriers to overcome when building a standard system, which greatly increases the difficulty of putting the standard specification landing into practice.
Identifying problems with quality can be challenging.
Manufacturing firms lack data personnel, making it more harder to rapidly and precisely detect and address data quality concerns. Group data problems of complicated sorts, low data quality, and manual judgment are all challenges.
"Synergy is difficult" across areas
Data control and governance require a lot of work across many departments, and the Group lacks the necessary processes, which makes coordination and communication difficult and expensive. At the same time, on a technical level, the Group lacks metadata, data standards, data quality, and other areas where it is difficult to achieve an effective flow of data between the Group's various departments, as well as efficient linkage and synergy.
Decision-making in the service sector is "difficult to apply"
There is a need to establish a set of comprehensive, efficient, unified data analysis and display systems in order to meet the various requirements of the Group. The Group's existing reports can only display a limited amount of information in a single way, while the regional information is displayed independently, not to form a holistic, comprehensive reports for the Group level analysis, reference.
An AEC project's common data environment (CDE) is a central cloud repository for tracking and managing data. It ensures that all project participants and the team have access to the most recent information, enhancing teamwork and minimizing mistakes and inconsistencies.