Germany, which leads Industry 4.0, points out that advanced manufacturing, digitization and resources are the three main challenges of European manufacturing, and Europe must be overcome with a comprehensive integration strategy. Artificial intelligence (AI) and machine learning have a wide range of applications in manufacturing technology, and are also key technologies for digital manufacturing and automation applications and expansion. Therefore, the European Society of Machine Tools (CECIMO) actively advocates the EU's public and private sector to establish an integrated AI strategy.
According to reports, CECIMO, the world's largest machine tool organization in Brussels, Belgium, consists of 1,500 companies in the European Union. The total output of machine tools accounts for 97% of the 28 member states of the European Union, and will increase production in 2018. Machine manufacturing leads Germany with 46.4%, Italy with 21% and Switzerland with 11%.
CECIMO estimates that the size of the EU machine tool market in 2017 will grow from 5.63 billion euros in 2016 to 5.69 billion euros. CECIMO members accounted for more than 35% of the global total of the machine tool industry in the past three years. CECIMO forecasts that the value of production in 2017 will grow by 1.9% from 2016 to reach 24.4 billion euros.
CECIMO has always advocated the importance of strategic coordination on technical issues, including the need to emphasize the need for the public and private sectors in the EU to develop and support competitive industrial strategies, including financial incentives; and to seek public support for trainers with new manufacturing technologies. Skills; support accelerating the commercialization of emerging technologies such as AddiTIve Manufacturing. While AI and machine learning create endless opportunities for automation, improve engineering efficiency, and reduce costs, CECIMO called on all delegates to assist in the development and implementation of plans to expand adoption of AI and machine learning at the recent annual conference.
In addition, CECIMO also endorses the process-driven (Process OpTImizaTIon) data-driven solution, including removing barriers to data sharing and data mobility (Mobility) and establishing data portability self-constraint (Self-regulaTIng) The Code of Conduct emphasizes the need to develop a voluntary European certification and identification program to build a framework that enhances data security in the Internet of Things era.
AI enables computer systems to perform programs that typically require human involvement, such as decision making, language translation, speech recognition, machine vision, and the like. Machine learning is the use of AI guidance system, from the work of (Task) and decision (Decision) synthesis results (Result), the cumulative results become experience, so that the machine can automatically learn and improve from experience, do not need to directly achieve results Programming, that is, let the machine or system automatically access and use data learning.
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