Name
Title | ||
|---|---|---|
Monitoring The Quality Of A Chemical Production Process Using The Joint Estimation Method |
Abstract | ||
|---|---|---|
The standard approach to monitoring a chemical production process is the control chart. Such a chart assumes that the data values are independent and identically distributed. It has been shown that such is not so for many production processes especially those of chemical interest. However a more realistic approach to the problem can be developed using time series modeling. A recent development in time series methodology, the joint estimation procedure, allows for the detection and identification of four types of outliers. This study draws the correspondence between these outlier types and out-of-control situations (that is, adverse process changes) in chemical process control. The correspondence is illustrated in this study using a dye Liquor data set. Results show that the joint estimation procedure is appropriate for use in process control and provides advantages for dealing with out-of-control problems in production processes. |
Year | DOI | Venue |
|---|---|---|
1995 | 10.1021/ci00023a008 | JOURNAL OF CHEMICAL INFORMATION AND COMPUTER SCIENCES |
Keywords | Field | DocType |
production process | Process engineering,Combinatorics,Scheduling (production processes),Mathematics | Journal |
Volume | Issue | ISSN |
35 | 1 | 0095-2338 |
Citations | PageRank | References |
2 | 0.44 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sameer Prasad | 1 | 27 | 3.98 |
| David E. Booth | 2 | 109 | 21.34 |
| Michael Y. Hu | 3 | 426 | 55.74 |