ISSN:
0001-1541
Keywords:
Chemistry
;
Chemical Engineering
Source:
Wiley InterScience Backfile Collection 1832-2000
Topics:
Chemistry and Pharmacology
,
Process Engineering, Biotechnology, Nutrition Technology
Notes:
A new approach to gross error detection provides unbiased estimates and 100(1-α)% simultaneous confidence intervals of process variables when biased process measurements and process leaks exist. Presented in this article are estimation equations for process variables, as well as equations that help identify biased measurements and process leaks. These equations include the power function for a global test, and two types of α-level component tests and their power functions. Important strengths and weaknesses of this approach are compared to those of the serial compensation strategy, in particular, by varying the significance level (α), the variance-covariance matrix (Σ), the size of measurement bias (δ), the number of biased variables, and the sample size (N). Accuracy of δ estimation and performance in detecting the presence of process leaks (γ) are also evaluated and compared. The proposed approach has unique features that can provide a basis for improving the reconciliation of variables in process operations.
Additional Material:
1 Ill.
Type of Medium:
Electronic Resource
URL:
http://dx.doi.org/10.1002/aic.690380410
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