MSA

    A Measurement System Analysis, abbreviated MSA, is a specially designed experiment that seeks to identify the components of variation in the measurement.

    Just as processes that produce a product may vary, the process of obtaining measurements and data may have variation and produce defects.

    A Measurement Systems Analysis evaluates the test method, measuring instruments, and the entire process of obtaining measurements to ensure the integrity of data used for analysis (usually quality analysis) and to understand the implications of measurement error for decisions made about a product or process. MSA is an important element of Six Sigma methodology and of other quality management systems.

    MSA analyzes the collection of equipment, operations, procedures, software and personnel that affects the assignment of a number to a measurement characteristic.

    A Measurement Systems Analysis considers the following:
  • Selecting the correct measurement and approach
  • Assessing the measuring device
  • Assessing procedures & operators
  • Assessing any measurement interactions
  • Calculating the measurement uncertainty of individual measurement devices and/or measurement systems

    Common tools and techniques of Measurement Systems Analysis include: calibration studies, fixed effect ANOVA, components of variance, Attribute Gage Study, Gage R&R, ANOVA Gage R&R, Destructive Testing Analysis and others. The tool selected is usually determined by characteristics of the measurement system itself.
    Factors affecting measurement systems

    Factors might include:
  • Equipment: measuring instrument, calibration, fixturing, etc
  • People: operators, training, education, skill, care
  • Process: test method, specification
  • Samples: materials, items to be tested (sometimes called "parts"), sampling plan, sample preparation, etc
  • Environment: temperature, humidity, conditioning, pre-conditioning,
  • Management: training programs, metrology system, support of people, support of quality management system, etc

    These can be plotted in a "fishbone" Ishikawa diagram to help identify potential sources of measurment variation.