Details
| Original language | English |
|---|---|
| Pages (from-to) | 3592-3601 |
| Number of pages | 10 |
| Journal | Procedia Computer Science |
| Volume | 225 |
| Early online date | 8 Dec 2023 |
| Publication status | E-pub ahead of print - 8 Dec 2023 |
| Event | 27th International Conference on Knowledge Based and Intelligent Information and Engineering Sytems, KES 2023 - Athens, Greece Duration: 6 Sept 2023 → 8 Sept 2023 |
Abstract
The increasing complexity in product development and the lack of knowledge exchange, for example, between development and manufacturing lead to unnecessary iteration loops and high costs. To overcome this situation, an option is the execution of a design review using multi-agent systems to provide designers with a digital assistance system for checking their CAD (computer-aided design) models regarding manufacturability using a milling process. This paper explores how to increase the scalability and robustness of multi-agent systems (MAS) for manufacturability assessment by using runtime-generated BDI (belief-desire-intention) agents and graph-based feature recognition. The applicability and validation of the presented approach is carried out by evaluating different milled part designs.
Keywords
- computer-aided design, digital design review, graph-based feature recognition, multi-agent systems
ASJC Scopus subject areas
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In: Procedia Computer Science, Vol. 225, 08.12.2023, p. 3592-3601.
Research output: Contribution to journal › Conference article › Research › peer review
}
TY - JOUR
T1 - Scalable BDI-based Multi-Agent System for Digital Design Reviews
AU - Plappert, Stefan
AU - Becker, Christian
AU - Gembarski, Paul Christoph
AU - Lachmayer, Roland
PY - 2023/12/8
Y1 - 2023/12/8
N2 - The increasing complexity in product development and the lack of knowledge exchange, for example, between development and manufacturing lead to unnecessary iteration loops and high costs. To overcome this situation, an option is the execution of a design review using multi-agent systems to provide designers with a digital assistance system for checking their CAD (computer-aided design) models regarding manufacturability using a milling process. This paper explores how to increase the scalability and robustness of multi-agent systems (MAS) for manufacturability assessment by using runtime-generated BDI (belief-desire-intention) agents and graph-based feature recognition. The applicability and validation of the presented approach is carried out by evaluating different milled part designs.
AB - The increasing complexity in product development and the lack of knowledge exchange, for example, between development and manufacturing lead to unnecessary iteration loops and high costs. To overcome this situation, an option is the execution of a design review using multi-agent systems to provide designers with a digital assistance system for checking their CAD (computer-aided design) models regarding manufacturability using a milling process. This paper explores how to increase the scalability and robustness of multi-agent systems (MAS) for manufacturability assessment by using runtime-generated BDI (belief-desire-intention) agents and graph-based feature recognition. The applicability and validation of the presented approach is carried out by evaluating different milled part designs.
KW - computer-aided design
KW - digital design review
KW - graph-based feature recognition
KW - multi-agent systems
UR - http://www.scopus.com/inward/record.url?scp=85183562347&partnerID=8YFLogxK
U2 - 10.1016/j.procs.2023.10.354
DO - 10.1016/j.procs.2023.10.354
M3 - Conference article
AN - SCOPUS:85183562347
VL - 225
SP - 3592
EP - 3601
JO - Procedia Computer Science
JF - Procedia Computer Science
T2 - 27th International Conference on Knowledge Based and Intelligent Information and Engineering Sytems, KES 2023
Y2 - 6 September 2023 through 8 September 2023
ER -