Abstract

Abstract To produce reliable analytical data in a laboratory, all steps of the analytical chain have to be properly understood and controlled. Sampling, sample pretreatment, storage, subsampling, dissolution and/or mineralization, choice of analytical method, calibration of the measuring instruments, and metrological evaluation of data should all be subject to QC (quality control) and QAS (quality assessment) measures. QC includes measures for minimizing errors and keeping them within the required limits. QAS measures are monitoring the quality of the produced data. Some aspects of QC and QAS are described and examples are given of the practical difficulties which may occur in an analytical laboratory.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.