Abstract
The design of components suitable for manufacturing requires the application of knowledge about the manufacturing process chain with which the component is to be manufactured. This article presents an assistance system for decision support in the context of design for manufacturing. The assistance system includes explicit manufacturing process chain knowledge and has an inference engine that can automatically evaluate the manufacturability of a component design based on a given manufacturing process chain and resolve emerging manufacturing conflicts by making adjustments on the component or resource side. A link with a CAD system additionally enables the three-dimensional representation of derived manufacturing stages and manufacturing resources. Within the assistance system, a manufacturing process chain is understood as a configurable design object and is implemented via a constraint satisfaction problem. Furthermore, the required abstraction of manufacturing processes within finite domains can be reduced to the extent that necessary modeling resolution is achieved by incorporating empirical or simulative surrogate models into the CSP. The assistance system was conceptually validated on a tailored forming process chain for the production of a multimaterial shaft and provides added value, as valuable manufacturing information for component designs is automatically derived and made available in explicit form during the component development.
| Original language | English |
|---|---|
| Article number | 247 |
| Journal | Algorithms |
| Volume | 16 |
| Issue number | 5 |
| DOIs | |
| Publication status | Published - 10 May 2023 |
Keywords
- constraint satisfaction problem
- design for manufacturing
- knowledge based engineering
- process chain
- product development
- tailored forming
ASJC Scopus subject areas
- Theoretical Computer Science
- Numerical Analysis
- Computational Theory and Mathematics
- Computational Mathematics
Projects
- 1 Finished
-
Collaborative Research Centre 1153/2: Process Chain for Manufacturing Hybrid High Performance Components by Tailored Forming
Behrens, B.-A. (Principal Investigator)
1 Jul 2019 → 30 Jun 2023
Project: Research
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