Modelling for Digital Twins—Potential Role of Surrogate Models
| Autor: | János Abonyi, Tibor Chován, Sándor Németh, Ágnes Bárkányi |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Underline
Computer science 0211 other engineering and technologies Bioengineering 02 engineering and technology Machine learning computer.software_genre lcsh:Chemical technology lcsh:Chemistry model maintenance Surrogate model 020401 chemical engineering digital twin Chemical Engineering (miscellaneous) lcsh:TP1-1185 021108 energy 0204 chemical engineering surrogate model Discrete manufacturing business.industry Process Chemistry and Technology model life cycle lcsh:QD1-999 Artificial intelligence White box business computer |
| Zdroj: | Processes, Vol 9, Iss 476, p 476 (2021) |
| ISSN: | 2227-9717 |
| Popis: | The application of white box models in digital twins is often hindered by missing knowledge, uncertain information and computational difficulties. Our aim was to overview the difficulties and challenges regarding the modelling aspects of digital twin applications and to explore the fields where surrogate models can be utilised advantageously. In this sense, the paper discusses what types of surrogate models are suitable for different practical problems as well as introduces the appropriate techniques for building and using these models. A number of examples of digital twin applications from both continuous processes and discrete manufacturing are presented to underline the potentials of utilising surrogate models. The surrogate models and model-building methods are categorised according to the area of applications. The importance of keeping these models up to date through their whole model life cycle is also highlighted. An industrial case study is also presented to demonstrate the applicability of the concept. |
| Databáze: | OpenAIRE |
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