Improving Sample Analysis Throughput and Quality with a .NET™-based, Real-Time QC Decision Support System

Abstract

This report describes an integrated, software-based quality control system designed to significantly improve the sample analysis throughput and quality of beryllium analysis laboratories throughout the U.S. Department of Energy complex. Originally, this system was developed to minimize the downtimes of expensive instrumentation (here: Perkin Elmer® 4300™ DV Inductively Coupled Plasma Optical Emission Spectrometers) and to automate the sample analysis quality control process. This automated software system was also expected to eliminate time-consuming and error-prone result data interpretation, which previously was done manually. To achieve these goals, Los Alamos National Laboratory recently implemented a rule-based decision support system in the C#.NET™ that continuously extracts and analyzes data from the instrument's result database as the data is being generated. Using a customer-specific expert rule base, the system is capable of detecting abnormal operating situations fully autonomously in real time. This also enables the system to perform on-the-fly quality control and automatic, electronic event notification of lab personnel via e-mail and pager. (JALA 2003;8:107–12)