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Title: Automated statistical modeling of analytical measurement systems

Technical Report ·
DOI:https://doi.org/10.2172/10164281· OSTI ID:10164281

The statistical modeling of analytical measurement systems at the Idaho Chemical Processing Plant (ICPP) has been completely automated through computer software. The statistical modeling of analytical measurement systems is one part of a complete quality control program used by the Remote Analytical Laboratory (RAL) at the ICPP. The quality control program is an integration of automated data input, measurement system calibration, database management, and statistical process control. The quality control program and statistical modeling program meet the guidelines set forth by the American Society for Testing Materials and American National Standards Institute. A statistical model is a set of mathematical equations describing any systematic bias inherent in a measurement system and the precision of a measurement system. A statistical model is developed from data generated from the analysis of control standards. Control standards are samples which are made up at precise known levels by an independent laboratory and submitted to the RAL. The RAL analysts who process control standards do not know the values of those control standards. The object behind statistical modeling is to describe real process samples in terms of their bias and precision and, to verify that a measurement system is operating satisfactorily. The processing of control standards gives us this ability.

Research Organization:
Westinghouse Idaho Nuclear Co., Inc., Idaho Falls, ID (United States)
Sponsoring Organization:
USDOE, Washington, DC (United States)
DOE Contract Number:
AC07-84ID12435
OSTI ID:
10164281
Report Number(s):
WINCO-11826; CONF-9206215-1; ON: DE92017271
Resource Relation:
Other Information: PBD: [1992]
Country of Publication:
United States
Language:
English