Assembly time modelling through connective complexity metrics
| Autor: | Joshua D. Summers, James L. Mathieson, Bradley A. Wallace |
|---|---|
| Rok vydání: | 2013 |
| Předmět: |
Computer science
business.industry Mechanical Engineering Physical system Design for assembly Aerospace Engineering Sample (statistics) Variation (game tree) Machine learning computer.software_genre Average path length Standard deviation Computer Science Applications Set (abstract data type) Path length Artificial intelligence Data mining Electrical and Electronic Engineering business computer |
| Zdroj: | International Journal of Computer Integrated Manufacturing. 26:955-967 |
| ISSN: | 1362-3052 0951-192X |
| Popis: | This paper presents an approach for the development of surrogate models predicting the assembly time of a system based on complexity metrics of the physical system architecture when detailed geometric information is unavailable. A convention for modelling physical architecture is presented, followed by a sample of 10 analysed systems used for training and three systems used for validation. These systems are evaluated on complexity metrics developed from graph theoretic measures. An example model is developed based on a series of regressions of trends observed within the sample data. This is validated against the systems that are not used to develop the model. The model developed uses average path length, part count and path length density to approximate assembly time within the standard deviation of the subjective variation possible in Boothroyd and Dewhurst design for assembly DFA analysis. While the specific example model developed is generalisable only to systems similar to those in the sample set, the capability to develop mappings between physical architecture and assembly time in early-stage design is demonstrated. |
| Databáze: | OpenAIRE |
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