A Multivariate Approach to Monitor the Quality of Chromatograms from Gas Chromatography Mass Spectrometry

Abstract

Multivariate control charts were generated to accurately track and monitor data produced from large batches of samples in continuous runs. The Shewhart and cumulative sum (CUSUM) charts were evaluated for their ability to determine the quality and stability of chromatograms produced from control sample runs on GC-MS. The data generated from continuous run processes were statistically analyzed in order to evaluate the quality of measurements obtained. A sample of a GC-MS continuous data run is presented to illustrate the effectiveness of these multivariate control charts to monitor quality of data output. Moreover, the statistical analysis of variance (ANOVA) technique was able to identify the specific factors that significantly contribute to GC/ MS instrument data output quality. In conclusion, this chart-based approach to quality control, when applied to ongoing GC-MS processes, will enhance the overall data output quality and improve the detection effectiveness.