Abstract
The recent trends in manufacturing toward modularity and flexibility result in complex multistage manufacturing processes that consist of many interrelated workstations. In such processes, it is highly desirable to differentiate between local and propagated variations, and implement process variability monitoring and reduction. In this paper, attention is focused on the properties of a widely used regression-adjustment-based method in the monitoring of variation propagation in multistage manufacturing processes. Particularly, the impacts of measurement errors and regressor selection on the monitoring scheme are investigated, and conclusions which can help guide the use of this method are summarized. Numerical examples are also presented to validate the analysis.
| Original language | English |
|---|---|
| Pages (from-to) | 109-121 |
| Journal | IIE Transactions (Institute of Industrial Engineers) |
| Volume | 40 |
| Issue number | 2 |
| DOIs | |
| Publication status | Published - Feb 2008 |
| Externally published | Yes |
Bibliographical note
Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 9 Industry, Innovation, and Infrastructure
Research Keywords
- Measurement errors
- Multistage processes
- Regression adjustment
- Regressor selection
- Variation propagation
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