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  Fan Shukai, Beijing University of Science and Technology: AI is to liberate the domain knowledge of engineers (Domain Knowledge)   In the face of fierce competition in the global market, how should Taiwan's manufacturing industry use technology to help companies ride the wind? Fan Shukai, the convener of the Department of Industrial Engineering and Management of the Ministry of Science and Technology and a professor of the Department of Industrial Engineering and Management of National Taipei University of Science and Technology, put it bluntly: "AI is to liberate the domain knowledge of professional engineers!" The relationship between AI and smart manufacturing   Fan Shukai has long invested in engineering optimization, advanced process control, and big data analysis, and has in-depth observations of Taiwan's industry and academia. He analyzed industrial development from a macro perspective, "From Industry 2.0, which hopes that people can be as regular as machines; to the current Industry 4.0, it is hoped that machines can be as smart as humans." Because machines will not be tired, and Will not complain, and can even do better than humans. Fan Shukai said: "It's like a car must run faster than a human, why do you have to race with a car? Computer calculations are better than humans, why do you have to compare speed with a computer?" Many people worry that artificial intelligence will replace existing human jobs, but there are still many things that only humans can do, such as soothing social work, creative design and other high-level work. Therefore, work is not replaced by AI, but with the development and application of new technologies, it dances with it to create more valuable and unique work items. Returning to the field of smart manufacturing, Fan Shukai pointed out that Taiwan is best at engineering technology development. As customers' requirements for production quality and efficiency increase year by year, the demand for diversified products increases, and various stringent requirements such as light weight products, many engineers spend their entire lives pursuing technology development that meets customer needs, and are also burdened. A lot of inexplicable pressure. However, as the amount of engineering data is increasing day by day, traditional analysis methods are difficult to apply, and existing engineering knowledge cannot deconstruct the problem. At this time, deep learning, machine learning and other technologies are used to help engineers initially understand complex products or engineering procedures. After a series of repeated training, hyperparameter adjustment, model construction, and successful deployment from process transformation (Process Transformation) to artificial intelligence transformation (AI Transformation) process, so that professional engineers can continue to delve into advanced engineering knowledge and continuously improve the added value of products and services. "It is impossible for the team to win the championship only by the main attack!" Fan Shukai took the Chinese women's volleyball champion in the 2016 Rio Olympics as an example. , first pass, and second pass work together to give full play to the synergy of the team.” Zhu Ting, the main attacker, is like the domain knowledge of a company. Liberation means letting the team cover each other or give her the ball at the right time. It's not about focusing on one person.  

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