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  • 标题:Analysing and Improving Efficiency of Production in Manufacturing Industries Using Artificial Intelligence Methodology with Real Time Implementatio
  • 本地全文:下载
  • 作者:JANANI R ; JANANI S ; PUSHPALATHA S
  • 期刊名称:International Journal of Innovative Research in Computer and Communication Engineering
  • 印刷版ISSN:2320-9798
  • 电子版ISSN:2320-9801
  • 出版年度:2021
  • 卷号:9
  • 期号:7
  • 页码:8619-8624
  • DOI:10.15680/IJIRCCE.2021.0907134
  • 语种:English
  • 出版社:S&S Publications
  • 摘要:India has been in a race for the past two and a half centuries but unfortunately it has been a race to the bottom. Most people think that the manufacturing industry is like the services or the Agri-industry; each industry having its own relative advantages and features. What is not clear to most is that the manufacturing-led economies are unique in being more egalitarian in their distribution of wealth. Secondly, manufacturing led economies are also much more resilient than economies that are led by other industries. Finally, the more importantly relevant for India, the manufacturing industry in India creates more employment opportunities with its growth than any other sector. Insight our research shows us is that manufacturing led economies are much more resilient and robust. And one of the major criteria to consider is the manufacturing the goods and delivering it at proper lead time. To achieve the tracking of goods production and it’s on time delivery is required to be taken care. For that technology needs to be integrated with the manufacturing leading to its tremendous improvement. In this project we propose a system to automatically track and trace each step of manufacturing and the time taken incompletion of each step. If the threshold time limit exceeds for any step in the process then an automatic mail will be sent to the manufacturer to automatically take steps for the process to complete on time. This is achieved by implementing object tracking methodology in industries.
  • 关键词:Mobile single shot detection algorithm;Regional Convolution Neural Network;SMTP protocol
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