| Project/Area Number |
21710161
|
|---|
| Research Category |
Grant-in-Aid for Young Scientists (B)
|
| Allocation Type | Single-year Grants |
|---|
| Research Field |
Social systems engineering/Safety system
|
|---|
| Research Institution | Tokyo University of Science |
|---|
Principal Investigator |
YASUI Seiichi 東京理科大学, 理工学部, 助教 (90434026)
|
|---|
| Project Period (FY) |
2009 – 2011
|
| Project Status |
Completed (Fiscal Year 2011)
|
| Budget Amount *help |
¥4,420,000 (Direct Cost: ¥3,400,000、Indirect Cost: ¥1,020,000)
Fiscal Year 2011: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2010: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2009: ¥2,600,000 (Direct Cost: ¥2,000,000、Indirect Cost: ¥600,000)
|
|---|
| Keywords | 品質管理 / 統計的工程管理 / 多品種少量生産 / 変化点検出 / 品質管理システム / 統計数学 / プロファイルデータ / 多変量解析 |
|---|
| Research Abstract |
A flexible manufacturing system(FMS) enabled the production of multi-item and small-sized. By an automatic measurement system, we can take a large amount of observations at short time. However, the observations are not utilized for statistical process control, effectively. The observations from FMS include some variation patterns and outliers, therefore it is difficult to implement conventional statistical process control. In this study, it is developed that the data analysis technique which extracts effective information for improving and controlling a FMS process. For practical quality data expressed as profile or functional data, conventional approach is applied. As a result, a certain kind of profile data induces serious trouble. The causes are investigated through theoretical approach.
|
