Application of Computer Vision in Intelligent Manufacturing under the Background of 5G Wireless Communication and Industry 4.0

With the development of 5G wireless communications and the arrival of Industry 4.0, computer vision has further penetrated the manufacturing sector. This paper makes a comprehensive study on the field of intelligent manufacturing. By constructing a model analysis method, the current situation of computer vision intelligent manufacturing under the background of 5G wireless communication and industry 4.0 is comprehensively analyzed. It is found that today 's computer vision technology is developing rapidly, while the Industry 4.0 stage and 5G communication technology have helped the field of intelligent manufacturing. At the same time, the author deeply analyzes the characteristics of intelligent manufacturing enterprises supported by computer vision and finds that it has the problem of unbalanced distribution of enterprises. After that, the author demonstrates the application of computer vision re-intelligent manufacturing from multiple dimensions. The application of computational optimization methods provides more diverse and comprehensive algorithms for labor saving and resource utilization improvement. Computer vision technology drives and promotes the development of intelligent applications and promotes a more comprehensive development of intelligent manufacturing.

[1]  Usama Awan,et al.  Enabling Progress in Developing Economies: A Novel Hybrid Decision-Making Model for Green Technology Planning , 2021, Sustainability.

[2]  Usama Awan,et al.  Does green transformational leadership lead to green innovation? The role of green thinking and creative process engagement , 2021, Business Strategy and the Environment.

[3]  M.V.A. Raju Bahubalendruni,et al.  Challenges and opportunities in human robot collaboration context of Industry 4.0 - a state of the art review , 2021, Ind. Robot.

[4]  Usama Awan Impact of social supply chain practices on social sustainability performance in manufacturing firms , 2019, International Journal of Innovation and Sustainable Development.

[5]  Bibhuti Bhusan Biswal,et al.  An intelligent approach towards optimal assembly sequence generation , 2018 .

[6]  A. Kraslawski,et al.  Buyer-supplier relationship on social sustainability: Moderation analysis of cultural intelligence , 2018 .

[7]  A. Al-Ahmari,et al.  Automated Disassembly Sequence Prediction for Industry 4.0 Using Enhanced Genetic Algorithm , 2021, Computers, Materials & Continua.

[8]  Data Processing Techniques and Applications for Cyber-Physical Systems, DPTA 2019, Shanghai, China, November 15-16, 2019 , 2020, DPTA.

[9]  Usama Awan Effects of buyer-supplier relationship on social performance improvement and innovation performance improvement , 2019, International Journal of Applied Management Science.

[10]  Shan Ren,et al.  New Pattern of Lifecycle Big-Data-Driven Smart Manufacturing Service for Complex Product , 2018 .

[11]  Chen Dan,et al.  The Development and Application of Computer Vision Technology , 2008 .