Through the lens of Generative AI: The expressiveness of research on validation techniques for material flow simulation
Research output: Contribution to journal › Conference article › Contributed › peer-review
Contributors
Abstract
In the light of the ongoing development of Generative AI (GenAI), we encourage the reflection on scientific publishing to increasingly leverage current and future information processing capabilities. Here, we propose a commonly recognizable framework for the description of validation techniques applicable to the material flow simulation of manufacturing systems. By utilizing this framework not only the explanation of such techniques can be structured appropriately but also a form of guidance for GenAI-driven information processing can be provided. Illustrated by the use case of a high-volume automotive production line, we demonstrate the feasibility of the framework as we streamline the description of two different validation techniques. In doing so, the application of the framework to support the information processing capabilities of GenAI-driven services is discussed.
Details
| Original language | English |
|---|---|
| Pages (from-to) | 451-456 |
| Number of pages | 6 |
| Journal | Procedia CIRP |
| Volume | 146 |
| Publication status | Published - Sept 2026 |
| Peer-reviewed | Yes |
| Externally published | Yes |
Conference
| Title | 59th CIRP Conference on Manufacturing Systems |
|---|---|
| Subtitle | Driving the Future of Manufacturing Systems with AI and Sustainability |
| Abbreviated title | CIRP CMS 2026 |
| Conference number | 59 |
| Duration | 19 - 21 May 2026 |
| Website | |
| Location | AT&T Conference Center |
| City | Austin |
| Country | United States of America |
Keywords
ASJC Scopus subject areas
Keywords
- Digital manufacturing system, Digital Twin, Generative AI (GenAI), Optimization, Simulation