Metrology Practices

Committee Charter (as of Sep 2015)
Collect, develop and disseminate analytical information on measuring and test equipment, measuring standards and processes to promote improvements in measurement quality assurance (MQA) and measurement quality metrics (MQMs). This includes the identification and description of mathematical, scientific and administrative parameters and the development of guidelines for statistical or Bayesian methods related to measurement models, measurement reliability, calibration intervals, process control, measurement uncertainty, uncertainty growth, measurement decision risk, and economic metrology decision support.
 
2016-2018 Goals
  1. Assist the 144 Laboratory Operations Committee with the reissue of RP-5, “Measuring and Test Equipment Specifications”.
  2. Set up an NCSLI MPC community web page for committee & membership interaction, surveys, analysis examples & validation data, and other resources.
  3. Develop and publish uncertainty and risk analysis examples to complement RP-12 and RP-18.
    Publish RP-19, “End-to-End Measurement Quality Assurance”
  4. Continue interval analysis methodology effectiveness research and develop interval analysis validation data.
  5. Update RP-1, “Establishment and Adjustment of Calibration Intervals”.
  6. Review the case for an RP on statistical process control for metrology.
  7. Develop short presentations on the MPC RPs for NCSLI Region or Section meetings.
  8. Investigate instrument models for propagating measurement quality metrics (MQMs) from calibration points to the entire instrument usage space.
     

Further Information:

   1.  Our latest charter and admin guideline
 173 Metrology Practices AG 20150921

 
   2.  Committee Meeting:
 Wednesday, August 16, 
5:30 PM,
 Gaylord National Convention Center
 National Harbor, Maryland, Magnolia 3

 
   3.  Subcommittees  
       a. 173.1 Calibration Intervals  
       b. 173.2 Measurement Decision Risk  
       c. 173.3 Statistical Process Control   
       d. 173.4 Measurement Decision Support  
       e. 173.5 Measurement Uncertainty Analysis