In recent years, the development of emerging technologies has brought about a new era of industrial reform. The current industrial revolution will deeply integrate the new generation of information technology with modern manufacturing industry and production servicing businesses to promote transformation and upgrading. As it is the foundation of the manufacturing industry, intelligent equipment plays an important role in the reform. In this paper, we propose an innovative design method to help design intelligent equipment. Firstly, referring to the architecture of the Cognitive Internet of Things (CIoT) and industrial big data, we proposed the architecture of the method and defined the different layers to process the data. Then, for the acquired external data, we put forward an algorithm which was combined with the technology of CIoT and industrial big data, to help designers analyze and make decisions. Finally, we verified the validity and feasibility of this method through a case study. The results showed that this method could effectively mine the deep information of intelligent equipment and provide more valuable information about design-assisting designers in designing better intelligent equipment.

Intelligent equipment design assisted by Cognitive Internet of Things and industrial big data

Celesti, Antonio
;
2018-01-01

Abstract

In recent years, the development of emerging technologies has brought about a new era of industrial reform. The current industrial revolution will deeply integrate the new generation of information technology with modern manufacturing industry and production servicing businesses to promote transformation and upgrading. As it is the foundation of the manufacturing industry, intelligent equipment plays an important role in the reform. In this paper, we propose an innovative design method to help design intelligent equipment. Firstly, referring to the architecture of the Cognitive Internet of Things (CIoT) and industrial big data, we proposed the architecture of the method and defined the different layers to process the data. Then, for the acquired external data, we put forward an algorithm which was combined with the technology of CIoT and industrial big data, to help designers analyze and make decisions. Finally, we verified the validity and feasibility of this method through a case study. The results showed that this method could effectively mine the deep information of intelligent equipment and provide more valuable information about design-assisting designers in designing better intelligent equipment.
2018
File in questo prodotto:
Non ci sono file associati a questo prodotto.
Pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11570/3129419
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 36
  • ???jsp.display-item.citation.isi??? ND
social impact