An Aggregated Digital Twin Solution for Human-Robot Collaboration in Industry 4.0 Environments

Author(s):  
A. J. Joseph ◽  
K. Kruger ◽  
A. H. Basson
2020 ◽  
Vol 10 (1) ◽  
pp. 377-385 ◽  
Author(s):  
Antti Liljaniemi ◽  
Heikki Paavilainen

AbstractDigital Twin (DT) technology is an essential technology related to the Industry 4.0. In engineering education, it is important that the curricula are kept up-to-date. By adopting new digital technologies, such as DT, we can provide new knowledge for students, teachers, and companies. The main aim of this research was to create a course concept to research benefits and barriers of DT technology in engineering education. The research confirmed earlier findings concerning digitalization in engineering education. DT technology can increase motivation for studying and improve learning when applied correctly.


2020 ◽  
Vol 53 (2) ◽  
pp. 10867-10872
Author(s):  
Luige Vlădăreanu ◽  
Alexandru I. Gal ◽  
Octavian D. Melinte ◽  
Victor Vlădăreanu ◽  
Mihaiela Iliescu ◽  
...  
Keyword(s):  

Author(s):  
Maria G. Juarez ◽  
Vicente J. Botti ◽  
Adriana S. Giret

Abstract With the arises of Industry 4.0, numerous concepts have emerged; one of the main concepts is the digital twin (DT). DT is being widely used nowadays, however, as there are several uses in the existing literature; the understanding of the concept and its functioning can be diffuse. The main goal of this paper is to provide a review of the existing literature to clarify the concept, operation, and main characteristics of DT, to introduce the most current operating, communication, and usage trends related to this technology, and to present the performance of the synergy between DT and multi-agent system (MAS) technologies through a computer science approach.


2022 ◽  
Vol 73 ◽  
pp. 102258
Author(s):  
Sung Ho Choi ◽  
Kyeong-Beom Park ◽  
Dong Hyeon Roh ◽  
Jae Yeol Lee ◽  
Mustafa Mohammed ◽  
...  

2021 ◽  
Vol 25 (1) ◽  
pp. 35-39
Author(s):  
Łukasz Glodek ◽  
Szymon Bysko ◽  
Witold Nocoń

This paper proposes a model quality assessment method based on Support Vector Machine, which can be used to develop a digital twin. This work is strongly connected with Industry 4.0, in which the main idea is to integrate machines, devices, systems, and IT. One of the goals of Industry 4.0 is to introduce flexible assortment changes. Virtual commissioning can be used to create a simulation model of a plant or conduct training for maintenance engineers. On a branch of virtual commissioning is a digital twin. The digital twin is a virtual representation of a plant or a device. Thanks to the digital twin, different scenarios can be analyzed to make the testing process less complicated and less time-consuming. The goal of this work is to propose a coefficient that will take into account expert knowledge and methods used for model quality assessment (such as Normalized Root Mean Square Error – NRMSE, Maximum Error – ME). NRMSE and ME methods are commonly used for this purpose, but they have not been used simultaneously so far. Each of them takes into consideration another aspect of a model. The coefficient allows deciding whether the model can be used for digital twin appliances. Such an attitude introduces the ability to test models automatically or in a semi-automatic way.


Author(s):  
Himanshu Singh ◽  
Utkarsh Mishra ◽  
Prateek Saxena ◽  
Ganesh Shetiya ◽  
Y. M. Puri

2022 ◽  
pp. 109-136
Author(s):  
Adolfo Crespo del Castillo ◽  
Marco Macchi ◽  
Laura Cattaneo

The world is witnessing an all-level digitalization that guides the industry and business to a restructuration in order to adapt to the new requirements of the surrounding environment. That change also concerns the labour of the technical professionals and their formation. As a consequence of this deep consciousness-raising, this chapter will investigate and develop simulation models based on the current digitalization. The aim of this chapter is the exposition of a real case development of “digital twin” models framed as part of the condition-based maintenance paradigm to improve real-time assets operation and maintenance. This model contributes by providing real-time results that could turn into a basis for the industrial management decisions and place them in the Industry 4.0 paradigm environment.


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