INDUSTRY 4.0 TRENDS IN INTELLIGENT MANUFACTURING AUTOMATION EXPLORING MACHINE LEARNING

被引:0
|
作者
Hoover, William [1 ]
Guerra-Zubiaga, David A. [1 ]
Banta, Jeremy [1 ]
Wandene, Kevin [1 ]
Key, Kaleb [1 ]
Gonzalez-Badillo, Germanico [2 ]
机构
[1] Kennesaw State Univ, Dept Robot & Mechatron Engn, Marietta, GA 30144 USA
[2] Univ Autonoma San Luis Potosi, San Luis Potosi, Mexico
来源
PROCEEDINGS OF ASME 2022 INTERNATIONAL MECHANICAL ENGINEERING CONGRESS AND EXPOSITION, IMECE2022, VOL 2B | 2022年
关键词
Digital Manufacturing; Machine Learning; Digital Twin; Data Analytics; Industry; 4.0; DIGITAL TWIN; CHALLENGES;
D O I
暂无
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Current trends indicate that the manufacturing industry is moving toward implementing Industry 4.0 concepts in search of improved adaptability, efficiency, sustainability, and advanced technological implementation. Some of these new technologies include virtual process simulation, automation, machine learning technologies, and the use of IIoT to innovate solutions. Researchers are focusing on ways to improve the rate and economy of implementing Industry 4.0 concepts in current manufacturing processes. This paper focuses on the implementation of a combination of specific industry 4.0 concepts in a lab environment. There will also be a case study where this research will be applied, and the results discussed. Digital Twins is also a proposed component of the research case study that is implemented using Siemens PLM Tecnomatix tool. Future work is to improve the efficiency of the manufacturing, pick-and-place operation using Deep Reinforcement learning.
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收藏
页数:9
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