Abstract
【Objective】To ensure that each analysis step is in the monitoring state. The quality control chart is used to control the process of soil organic carbon content determination, and the reasons for drifting or exceeding the allowable value of the result data can be found out in time.【Method】The content of soil organic carbon in quality control samples was determined by instrumental analysis, and the quality control chart was drawn based on the determination data in Excel 2007, which was used for the quality control of the soil organic carbon content determination process.【Result】The control line of the mean control chart was 41.94% ~ 40.51%, and the warning limit was 41. 70% ~ 41. 74%. The control line range of the range control chart is 0.00% ~ 2.75%, and the warning limit is 0.00% ~ 2. 12%.【Conclusion】The quality control chart method is simple to operate,easy to master, and can timely find the abnormal points or abnormal trends of data, which has high application value in test analysis, and can ensure the accuracy of laboratory test results.
Highlights
It is necessary to take a series of quality control and quality assurance measures of internal and external to ensure the precision and accuracy of test data, such as laboratory blank tests, parallel blank tests, plain code and security code parallel sample tests, quality control sample tests, sampling recovery rate tests, laboratory capability verification, and methods comparison etc., so as to assess whether the entire analysis process is in a “statistical control condition”
In terms of probability theory and mathematical statistics, there is a 99% chance that the measurement result should be in the range of X ± 3S; 95% should be in the range of X ± 2S; 68% should be in the range of X ± S
According to the “Conventional Quality Control Chart” (GB/T4091-2001)(for example, [13]) issued by the National Quality and Technical Supervision Bureau, the first step is to map the test results of the quality control samples in the order of testing to ensure that all points fall in the upper and lower control line
Summary
It is necessary to take a series of quality control and quality assurance measures of internal and external to ensure the precision and accuracy of test data, such as laboratory blank tests, parallel blank tests, plain code and security code parallel sample tests, quality control sample tests, sampling recovery rate tests, laboratory capability verification, and methods comparison etc., so as to assess whether the entire analysis process is in a “statistical control condition”. The purpose for drawing the quality control chart is that: under the monitoring conditions, the analysis and test result should have the precision and accuracy in a certain range, and be a normal distribution (for example, [1]). Walter Shewhart first proposed the quality control chart in 1928, he believed that, due to the influence of time and environment in sample analysis, no matter which method is used, there will be a certain degree of drift in the testing data, even under ideal conditions, random error will occur, and he proposed a statistical graph that can distinguish normal and abnormal fluctuations.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
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 callDisclaimer: 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.
