Name
Abstract | ||
|---|---|---|
Symbiotic simulation is one of Industry 4.0 technologies that enables interaction between a physical system and the simulation model that represents it as its digital twin. Symbiotic simulation is designed to support decision making at the operational levels by making use of real- or near real- time data that is generated by the physical system, which is used as an input to the simulation model. From the modeling perspective, a symbiotic simulation system comprises a hybrid systems model that combines simulation, optimization and machine learning models as well as a data acquisition module and an actuator. The actuator is needed when the symbiotic simulation system is designed to directly control the physical system without human intervention. This paper reviews the components of a symbiotic simulation system from the perspective of hybrid systems modeling and highlights research questions needed to advance symbiotic simulation study. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/WSC.2018.8632407 | WSC |
Keywords | Field | DocType |
Symbiosis,Data models,Analytical models,Predictive models,Adaptation models,Mathematical model,Data acquisition | Data modeling,Time data,Systems engineering,Simulation system,Computer science,Physical system,Data acquisition,Big data,Hybrid system,Actuator | Conference |
ISSN | ISBN | Citations |
0891-7736 | 978-1-5386-6572-5 | 1 |
PageRank | References | Authors |
0.36 | 0 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| B S S Onggo | 1 | 82 | 14.17 |
| Navonil Mustafee | 2 | 378 | 44.76 |
| Andi Smart | 3 | 4 | 1.42 |
| Angel A. Juan | 4 | 596 | 69.73 |
| Owen Molloy | 5 | 61 | 10.96 |