Measurement system analysis

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A measurement system analysis (MSA) is a thorough assessment of a measurement process, and typically includes a specially designed experiment that seeks to identify the components of variation in that measurement process. Just as processes that produce a product may vary, the process of obtaining measurements and data may also have variation and produce incorrect results. 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. Proper measurement system analysis is critical for producing a consistent product in manufacturing and when left uncontrolled can result in a drift of key parameters and unusable final products. MSA is also 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.

Contents

A measurement system analysis considers the following:

Common tools and techniques of measurement system analysis include: calibration studies, fixed effect ANOVA, components of variance, attribute gage study, gage R&R, [1] ANOVA gage R&R, and destructive testing analysis. The tool selected is usually determined by characteristics of the measurement system itself. An introduction to MSA can be found in chapter 8 of Doug Montgomery's Quality Control book. [2] These tools and techniques are also described in the books by Donald Wheeler [3] and Kim Niles. [4] Advanced procedures for designing MSA studies can be found in Burdick et al. [5]

Equipment: measuring instrument, calibration, fixturing.

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

Goals

The goals of a MSA are:

  1. Quantification of measurement uncertainty, including the accuracy, precision including repeatability and reproducibility, the stability and linearity of these quantities over time and across the intended range of use of the measurement process.
  2. Development of improvement plans, when needed.
  3. Decision about whether a measurement process is adequate for a specific engineering/manufacturing application.

ASTM Procedures

The ASTM has several procedures for evaluating measurement systems and test methods, including:

ASME Procedures

The American Society of Mechanical Engineers (ASME) has several procedures and reports targeted at task-specific uncertainty budgeting and methods for utilizing those uncertainty estimates when evaluating the measurand for compliance to specification. They are:

AIAG Procedures

The Automotive Industry Action Group (AIAG), a non-profit association of automotive companies, has documented a recommended measurement system analysis procedure in their MSA manual. [6] This book is part of a series of inter-related manuals the AIAG controls and publishes, including:

Note that the AIAG's website has a list of "errata sheets" for its publications.

See also

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References

  1. Measurement System in Manufacturing. Lean Six sigma. (n.d.). Retrieved from https://theengineeringarchive.com/sigma/page-measurment-systems.html.
  2. Montgomery, Douglas C. (2013). Introduction to Statistical Quality Control (7th ed.). John Wiley and Sons. ISBN   978-1-118-14681-1.
  3. Wheeler, Donald (2006). EMP III: Evaluating the Measurement Process & Using Imperfect Data. SPC Press. ISBN   978-0-945320-67-8.
  4. Niles, Kim (2002). Characterizing the Measurement Process in iSixSigma Insights Newsletter, Vol. 3, #42. ISSN   1530-7603.
  5. Burdick, Richard K.; Borror, Connie M.; Montgomery, Douglas C. (2005). Design and Analysis of Gauge R&R Studies: Making Decisions with Confidence Intervals in Random and Mixed ANOVA Models. SIAM. ISBN   978-0-898715-88-0.
  6. AIAG (2010). Measurement System Analysis, MSA (4th ed.). Automotive Industry Action Group. ISBN   978-1-60-534211-5.
  7. AIAG (2010). Measurement System Analysis (MSA), 4th Edition. Automotive Industry Action Group. ISBN   978-1-60534-211-5.
  8. AIAG (2008). Potential Failure Mode and Effect Analysis (FMEA), 4th Edition. Automotive Industry Action Group. ISBN   978-1-60534-136-1.
  9. AIAG (2005). Statistical Process Control (SPC), 2nd Edition. Automotive Industry Action Group. ISBN   978-1-60534-108-8.
  10. AIAG (2006). Production Part Approval Process (PPAP), 4th Edition. Automotive Industry Action Group. ISBN   978-1-60534-093-7.