Research and Application of Key Technologies of Intelligent Manufacturing Based on 5G Vehicle
Lecture Notes in Electrical Engineering, ISSN: 1876-1119, Vol: 996 LNEE, Page: 920-928
2023
- 17Captures
Metric Options: CountsSelecting the 1-year or 3-year option will change the metrics count to percentiles, illustrating how an article or review compares to other articles or reviews within the selected time period in the same journal. Selecting the 1-year option compares the metrics against other articles/reviews that were also published in the same calendar year. Selecting the 3-year option compares the metrics against other articles/reviews that were also published in the same calendar year plus the two years prior.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Captures17
- Readers17
- 17
Conference Paper Description
With the commercialization of 5G, the industrial intelligent manufacturing based on 5G will make the traditional automobile manufacturing realize the evolution from manual operation to digital operation. It will transform the productivity of manufacturers around the world. Under the background of 5G industrial intelligent manufacturing, intelligent manufacturing is an intelligent production mode integrating sensors and controllers. Automobile enterprises are exploring intelligent manufacturing methods such as machine learning/artificial intelligence, Internet of Things and digital twins to improve production competitiveness.This paper introduces intelligent manufacturing methods and extends the research on how manufacturing plants can apply their intelligent methods to realize the transformation from discrete manufacturing to intelligent manufacturing. The case study shows that Chongqing Changan Automobile Enterprise has started the intelligent manufacturing factory mode, thus transforming the overall production into the intelligent manufacturing industry and realizing the broad path of the implementation of intelligent manufacturing in the automotive industry. In the process of choosing these modes of operation, manufacturing plants continue to realize product mechanization, management informatization and operation digitalization.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85149947441&origin=inward; http://dx.doi.org/10.1007/978-981-19-9968-0_111; https://link.springer.com/10.1007/978-981-19-9968-0_111; https://dx.doi.org/10.1007/978-981-19-9968-0_111; https://link.springer.com/chapter/10.1007/978-981-19-9968-0_111
Springer Science and Business Media LLC
Provide Feedback
Have ideas for a new metric? Would you like to see something else here?Let us know