Name
Title | ||
|---|---|---|
An approach to automatically assign mechatronic components to an existing or identified classification. |
Abstract | ||
|---|---|---|
The increasing use of Virtual Validation Methods during the whole lifecycle of automated manufacturing plants combined with the increasing request towards better quality of plant behaviour simulations lead to the need of improved virtual plants with more effortless and faster set-ups. Existing approaches often focus on simulation quality and highest possible accuracy. Effortless and fast simulation set-ups as well as the ability of simulation models to be equivalent to the real plant not only at one specific moment in time but during its whole life-cycle have often been unattended. To be aware of these challenges, the different simulation sub models need knowledge about themselves, their functionality and what they represent be able to know their own capabilities and therefore be able to interact with each other automatically in a proper way. This work aims at providing a foundation for behaviour models of mechatronic components of automated manufacturing plants to do so. Therefore, the behaviour models are classified using clustering methods. After that, algorithms which enable models to integrate themselves into that classification are developed. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/COASE.2018.8560598 | CASE |
Field | DocType | Citations |
Validation methods,Computer science,Simulation modeling,Artificial intelligence,Cluster analysis,Mechatronics,Machine learning | Conference | 0 |
PageRank | References | Authors |
0.34 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sebastian Süß | 1 | 0 | 0.34 |
| Christian Diedrich | 2 | 76 | 17.15 |
| Felix Auris | 3 | 0 | 0.34 |