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  • 标题:TEACHING NETWORK TECHNOLOGIES THAT SUPPORT INDUSTRY 4.0
  • 本地全文:下载
  • 作者:Ishwar Singh ; Nafia Al-Mutawaly ; Tom Wanyama
  • 期刊名称:Proceedings of the Canadian Engineering Education Association
  • 出版年度:2015
  • 语种:English
  • 出版社:The Canadian Engineering Education Association (CEEA)
  • 摘要:Industry 4.0 is a combination of many elements, including distributed intelligence, network security, massive data, cloud computing, and analytics, among other things. Such elements are critical to the “Digital Factory”, a term that has been recently introduced by many companies indicating a comprehensive portfolio of seamlessly integrated hardware, software and technology-based services, with the aim to enhance manufacturing productivity and improving efficiency. Typically, industrial networks enable the gathering of extensive data from production lines and plants, which are increasingly becoming distributed. The gathered data is transmitted to analysis centers where it is transformed into information and used to make better informed decisions. In addition, modern industrial networks allow plant data to be automatically filtered and transmitted to various production controllers. Ultimately, industrial networks enable Industry 4.0 to have the following benefits: improved safety, increase uptime, lower energy costs, and improved maintenance; all of which lead to manufacturing competitiveness in cyber-physical production systems supported by Smart Grid implementations. This paper presents the extent to which industrial networks are taught at the School of Engineering Technology at McMaster University. Further, the paper covers teaching methods of industrial networks and their related applications within manufacturing plants and electrical grid.
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