Manufacturing Smart Industry Perspective an Overview
Ayyaswamy Kathirvel1, V M Gopinath2, Kathirvel Naren3, Damotharan Nithyanand4 & K Nirmaladevi1 Show affiliations
- Department of Computer Science and Engineering, Panimalar Engineering College, Chennai, India
- Department of Mechanical Engineering, Rajalakshmi Institute of Technology, Chennai, India
- Department of Artificial Intelligence Data and Science and Institute of Higher Technology, Chennai, India
- Department of Mechanical Engineering, Panimalar Engineering College, Chennai, India
American Journal of Engineering and Applied Sciences, Volume 17, Issue 1, pp. 33–39 · doi.org/10.3844/ajeassp.2024.33.39
Abstract
Within the past few decades, the increasing use of advanced technology in the manufacturing industry has drawn extensive study attention from all around the world. Smart technology is technology that gives previously thought-to-be-inanimate objects cognitive awareness through the application of artificial intelligence, machine learning and big data analysis. Smart Technology (ST) involves many emerging technologies like the internet of things, Industrial Internet of Things (IoT), cyber-physical production system artificial intelligence, blockchain and systematic data analysis. We provide an overview of different smart technologies to control the intensive features of computer and sensor technologies to diminish the gap between humans and machines. This research paper shows the complete literature review of ST to increase the production and maintenance of machinery equipment and future threats faced by ST. This study also includes the survey report of the rate of adoption today as compared to the past five years, to obtain real-time results, cost-effective techniques and the use of different sensors to reduce human workload in the manufacturing sector.
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Kathirvel, A., Gopinath, V. M., Naren, K., Nithyanand, D. & Nirmaladevi, K. (2024). Manufacturing Smart Industry Perspective an Overview. American Journal of Engineering and Applied Sciences, 17(1), 33–39. https://doi.org/10.3844/ajeassp.2024.33.39
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