Comparative Analysis on Development and Policy in Intelligent Manufacturing Industry Among China, the United States, Japan and Germany
- DOI
- 10.2991/978-94-6463-036-7_112How to use a DOI?
- Keywords
- Intelligent Manufacturing; Industrial Policy; International Comparison
- ABSTRACT
With the rapid evolution of digitalization, intellectualization and networking, intelligent manufacturing has become an important direction of global manufacturing reform. Countries around the world have continuously issued a number of policies to provide strategic support and cultivate their own international competitive advantages. Compared with the United States, Japan and Germany, China's manufacturing industry shows the characteristics of “premature and rapid” decline, uneven development level of intelligence in various industries, and China is still lacking in core technology in smart manufacturing industry. In the future, China should learn from the experiences of advanced countries in the development of intelligent manufacturing, accelerate the technological research and development of local intelligent manufacturing industry, and improve the industrial policy support system.
- Copyright
- © 2022 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Lina Wang AU - Hengyuan Zhao PY - 2022 DA - 2022/12/31 TI - Comparative Analysis on Development and Policy in Intelligent Manufacturing Industry Among China, the United States, Japan and Germany BT - Proceedings of the 2022 2nd International Conference on Economic Development and Business Culture (ICEDBC 2022) PB - Atlantis Press SP - 760 EP - 765 SN - 2352-5428 UR - https://doi.org/10.2991/978-94-6463-036-7_112 DO - 10.2991/978-94-6463-036-7_112 ID - Wang2022 ER -