Name
Abstract | ||
|---|---|---|
This article describes a model-based approach for defining and refining process parameters in dynamically changing, smart manufacturing environments. This approach uses equation-based models to predict how part quality will respond to changes in that environment. The results from these models provide the major inputs into a process-parameter-optimization technique, which is used to set the values for various process parameters. In developing these models, we integrated various concepts from process improvement frameworks, such as Define-Measure-Analyze-Improve-Control and Monitor-Analyze-Plan-Execute-Knowledge, with techniques from model-based engineering. After describing the approach, we demonstrate its use in an additive manufacturing process example. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1177/1063293X15591038 | CONCURRENT ENGINEERING-RESEARCH AND APPLICATIONS |
Keywords | DocType | Volume |
model-based approach,smart manufacturing,process parameters,additive manufacturing,predictive models,optimization | Journal | 23.0 |
Issue | ISSN | Citations |
SP4.0 | 1063-293X | 1 |
PageRank | References | Authors |
0.39 | 4 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Duck Bong Kim | 1 | 11 | 3.84 |
| Peter Denno | 2 | 26 | 7.47 |
| Albert Jones | 3 | 153 | 20.85 |