Industrial 4.0 era of manufacturing upgrade nine technology trends

Since the beginning of the Industrial Revolution, every technological advance has brought about a substantial increase in industrial productivity. In the early 19th century, the steam engine promoted the establishment of a modern factory. By the 20th century, electrification had led to large-scale industrial production and automation in the 1970s. However, in the ensuing decades, industrial technological progress was only an increase in quantity, with little breakthrough compared with information technology, mobile communications and e-commerce.

We are now in the wave of the fourth wave of industry: the emerging digital technology industry is called Industry 4.0, specifically referring to the transition to nine foundational technology-driven developments (Figure 1). In these shifts, sensors, machines, artifacts and IT systems will be linked to each other beyond the single enterprise to the value chain. These linking systems can interact with other systems based on Internet protocols, analyze data, make predictions, and automatically configure to accommodate changes. Industry 4.0 enables data collection and analysis across devices to produce more affordable, high-quality products more flexibly and efficiently. This, in turn, will also increase productivity, transform economic development patterns, promote industrial growth and ultimately enhance the competitiveness of enterprises and regions.

The Boston Consulting Group released a report outlining the nine technology trends in the Industry 4.0 era and explored its potential technical and economic benefits to provide information to manufacturers and manufacturing equipment suppliers. These nine technological advances have been applied to the manufacturing industry, and with the advent of Industry 4.0, they will change the mode of production: independent and optimized units will be fully integrated into the automated production process, changing the gap between suppliers, manufacturers and customers Traditional relationships also change the relationship between people and machines. (figure 2)


A large <br> <br> data and analysis based on the analysis of large data mode only recently appeared in large numbers in global manufacturing, it has the advantage to optimize product quality, save energy, improve equipment service. In the context of Industry 4.0, a comprehensive, integrated assessment of data from disparate sources such as development systems, production systems, business and customer management systems will make it a standard that supports real-time decision making. For example, the German semiconductor manufacturer Infineon has adopted a single-chip approach to help detect defective chips to improve production quality.

Second, the autonomous robot <br> <br> many industry manufacturers long-term use robots to handle complex jobs, but the robot was in constant evolution, and even can be used in a larger utility. They have become more autonomous, flexible and cooperative. Ultimately, they will work side by side with humans, and humans will learn from them as well. These robots will cost less and will be more widely available than robots used before manufacturing.

In many industries, robots have long been used to handle complex tasks and are still evolving. They are becoming more autonomous and flexible, eventually learning to interact with people, working safely with humans and learning from humans. These robots will be cheaper and more useful, can assume a more complex role.

For example, Gu Family House has used machinery and equipment from European manufacturers. These robots are interconnected so that they can work together and automatically adjust their actions to match the next unfinished product line. High-end sensors and control units ensure close cooperation with humans. Similarly, industrial robotic supplier ABB introduced a two-arm robot called "Corn," designed specifically to be used with humans to assemble products such as consumer electronics. The application of computer vision technology to ensure the safety interaction and the realization of part identification.

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