Name
Abstract | ||
|---|---|---|
Semiconductor manufacturing is highly complex and expensive, hence the early detection of problems is necessary to minimize the number of scraps and improve the overall yield. This paper presents an industrial application of dynamic sampling based on an aggregated risk indicator at process tool level. The objective is to identify the lots that should be measured to minimize the overall risk level of the fabrication plant (fab). Results show significant improvements compared with the previous strategy: Sampling decisions are better adapted to the current production state and to the workload in the inspection area. Several parameters and algorithms are proposed and compared using industrial data. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/CoASE.2014.6899414 | Automation Science and Engineering |
Keywords | Field | DocType |
inspection,machine tools,semiconductor industry,dynamic sampling,fab plant,fabrication plant,inspection,risk reduction,sampling decisions,semiconductor manufacturing,smart dynamic sampling,wafer | Risk level,Early detection,Wafer,Workload,Semiconductor device fabrication,Greedy algorithm,Manufacturing engineering,Risk management,Sampling (statistics),Engineering,Reliability engineering | Conference |
Citations | PageRank | References |
0 | 0.34 | 2 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sylvain Housseman | 1 | 9 | 1.81 |
| Stéphane Dauzère-Pérès | 2 | 740 | 65.50 |
| Gloria Rodríguez-Verján | 3 | 6 | 1.55 |
| Jacques Pinaton | 4 | 19 | 12.98 |
| Dauzere-Peres, S. | 5 | 5 | 1.22 |
| Rodriguez-Verjan, G. | 6 | 0 | 0.34 |