Libraries at University of Nebraska-Lincoln

 

Comments

We are submitting the improved version of our work.

Abstract

Nowadays, data is considered as a new life force for operations of physical systems in various domains such as manufacturing, healthcare, transportations, etc. However, the hugely generated data, which mirrors the working essence of the product life cycle, is still underutilised. Digital Twin (DT), a collective representation of active and passive captured data, is a virtual counterpart of the physical resources that could help prevent effective preventive maintenance in any applied domain. Currently, lots of research is going on about the applicability of digital twin in smart IOT based manufacturing industry 4.0 environment. Still, it lacks a formal study, which can provide a bird's eye view about the research efforts and directions. In this paper, the authors represent a bibliometric survey of the digital twin concept based on the Scopus database to present a global view about scholars' contributions in the manufacturing area. The study was conducted by retrieving 844 Scopus research papers published from 2015-2020 and analysed to find out critical insights such as publication volume, co-authorship networks, citation analysis, and demographic research distribution. The study revealed that significant contribution is made via concept propositions in conferences and some papers published in the journal. However, there is a scope of lots of research work in the direction of actual and secure digital twin implementation.

Share

COinS
 
 

To view the content in your browser, please download Adobe Reader or, alternately,
you may Download the file to your hard drive.

NOTE: The latest versions of Adobe Reader do not support viewing PDF files within Firefox on Mac OS and if you are using a modern (Intel) Mac, there is no official plugin for viewing PDF files within the browser window.