| Title |
Evaluation of Production of Digital Twins Based on Blockchain Technology |
| ID_Doc |
68943 |
| Authors |
Nabeeh, NA; Abdel-Basset, M; Gamal, A; Chang, V |
| Title |
Evaluation of Production of Digital Twins Based on Blockchain Technology |
| Year |
2022 |
| Published |
Electronics, 11, 8 |
| DOI |
10.3390/electronics11081268 |
| Abstract |
A blockchain, as a form of distributed ledger technology, represents the unanimity of replication, synchronization, and sharing of data among various geographical sites. Blockchains have demonstrated impressive and effective applications throughout many aspects of the business. Blockchain technology can lead to the advent of the construction of Digital Twins (DTs). DTs involve the real representation of physical devices digitally as a virtual representation of both elements and dynamics prior to the building and deployment of actual devices. DT products can be built using blockchain-based technology in order to achieve sustainability. The technology of DT is one of the emerging novel technologies of Industry 4.0, along with artificial intelligence (AI) and the Internet of Things (IoT). Therefore, the present study adopts intelligent decision-making techniques to conduct a biased analysis of the drivers, barriers, and risks involved in applying blockchain technologies to the sustainable production of DTs. The proposed model illustrates the use of neutrosophic theory to handle the uncertain conditions of real-life situations and the indeterminate cases evolved in decision-makers' judgments and perspectives. In addition, the model applies the analysis of Multi-criteria Decision Making (MCDM) methods through the use of ordered weighted averaging (OWA) and the Technique of Order Preference Similarity to the Ideal Solution (TOPSIS) to achieve optimal rankings for DT production providers based on consistent weighted decision-maker's judgments in order to maintain and to assure sustainability. An empirical study is applied to the uncertain environment to aid decision-makers in achieving ideal decisions for DT providers with respect to various DT challenges, promoting sustainability and determining the best service providers. The Monte Carlo simulation method is used to illustrate, predict, and forecast the importance of the weights of decision-makers' judgments as well as the direct impact on the sustainability of DT production. |
| Author Keywords |
digital twin; blockchain technologies; sustainability; IoT; AI; industry 4.0; neutrosophic theory; OWA; TOPSIS |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI) |
| EID |
WOS:000786056100001 |
| WoS Category |
Computer Science, Information Systems; Engineering, Electrical & Electronic; Physics, Applied |
| Research Area |
Computer Science; Engineering; Physics |
| PDF |
https://www.mdpi.com/2079-9292/11/8/1268/pdf?version=1650532093
|