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How DMIS Smooths the Way
The dramatic globalization of trade in recent years has sharpened industrial focus on questions of conformance of components to specifications.  Customer-supplier disagreements as to product compliance can be costly to all parties involved. 

In dimensional metrology, new national and international standards have addressed questions of conformance to geometric dimensioning and tolerancing (GD&T) specifications, recognizing the importance of measurement traceability and the key role played by measurement uncertainty.  In addition to being essential to assertions of traceability, task specific measurement uncertainty evaluations are necessary inputs to business models that enable decisions affecting profitability and customer perception of product quality.  The DMIS standard, in its 5.0 release, provides the requisite statements to accommodate reporting of measurement uncertainties and results of application of conformance rules to measurement data on individual parts.

GD&T requirements entail the assessment of complex 3-D interrelationships of part feature characteristics.  To meet this challenge a variety of tools are available, which we may class generally as “dimensional measuring equipment” (DME), and the most broadly applied is the coordinate measuring machine (CMM).  Powerful associated data analysis software allows the transformation of raw sample points taken on part surfaces into reportable GD&T parameters such as the parallelism of the cylinders in an engine block.  The question before us is this:  How much confidence can we place in the values reported by a DME?

Task-Specific Measurement Uncertainty

U. S. National Institute of Standards and Technology (NIST) documents make the importance of measurement uncertainty clear: “A measurement result is complete only when accompanied by a quantitative statement of its uncertainty.”  Ordinarily uncertainty is expressed as a range of values within which, at a specified level of confidence, the true value of the quantity measured is believed to lie.  In dimensional metrology, a task-specific uncertainty for each and every GD&T parameter is necessary.  Required are statements like, “The uncertainty of the diameter of this particular 75.00-mm diameter hole (produced under specific manufacturing conditions) is ± 0.05 mm at 95% confidence (when determined with this particular measurement system, using this particular measuring protocol, under this particular set of environmental conditions).  As suggested by the parenthetic phrases in the last sentence, many factors will contribute to task-specific measurement uncertainties.  The same power and versatility that make DMEs attractive as measuring devices also make assessing these measurement uncertainties a formidable task.  Before we address that issue, however, consider two important roles that measurement uncertainty plays in DME applications.  The first is in measurement traceability; the second is in conformance decisions.

The ISO defines traceability as “the property of the result of a measurement or the value of a standard whereby it can be related to stated references, usually national or international standards, through an unbroken chain of comparisons all having stated uncertainties.”  The prominent role of uncertainty in completing the traceability chain is evident.  Simply having a CMM calibrated does not make its measurement results traceable.  If your CMM-derived GD&T measurements are to be traceable, you need to include defensible task-specific uncertainty evaluations as part of your report. 
See Figure 1.
















Conformance Rules
The importance of uncertainty evaluation has been further emphasized in recent standards, notably ISO 14253-1 and ASME B89.7.3.1, which create guidance for the for-mulation of decision rules to govern the acceptance or rejection of articles of commerce. Figure 2 shows that if a decision rule requires that the specification zone be reduced by the measurement uncertainty to determine the zone of acceptable values, there is a clear economic penalty for greater uncertainty.  Knowing your measurement uncertainty is key to traceability and conformance; finding ways of minimizing it can also enhance profitability.


Evaluating Task-Specific Measurement Uncertainties for CMMs
Many factors can contribute to the uncertainty in a CMM-based measurement of a GD&T parameter.  The number of these influences and the complexity of their interactions have been recognized by experts as making the application of traditional “error budget” approaches to measurement uncertainty largely impractical for CMMs.  The ISO 15530 series offers several alternative approaches.  Without attempting here to treat in detail the relative merits of the five approaches that ISO cites, let it simply be said here that Computer Simulation offers the most promise in terms of versatility, economy, robustness and predictive character.  Of course any simulation is only as valid as it is comprehensive in its treatment of the important factors influencing the physical conditions being simulated.  Here the measurement of the part is simulated repeatedly under various conditions. The ranges of variability of factors such as CMM geometry errors, sensor errors, environmental conditions, etc. are employed in a mathematical model that allows their influences to be reflected in the resulting ranges of GD&T parameters – precisely consonant with the concept of measurement uncertainty defined above.
To date, two commercial software systems address simulation of CMM measurements for the purpose of evaluating task-specific measurement uncertainties.  One (VCMM from the German PTB) requires direct incorporation within a CMM’s operating software, relying on a “run-time” actual measured part for a portion of the data needed to calculate uncertainties. Its implementation within CMM software thus far has been limited to a few cases. The other (PUNDIT/CMM by MetroSage) stands independently of any individual CMM software package, using a CAD model of the part of interest as a basis for part geometry, and drawing information on datums, tolerances, probe systems, and sampling strategies either from a DMIS program or from direct user input.  The CAD model serves as a virtual calibrated part, allowing the simulation to assess measurement bias as well as measurement variability.  And because PUNDIT/CMM is not reliant on an actual physical part, it can offer insights on measurement uncertainties even before the first article has been produced.  It likewise can predict measurement uncertainties for a variety of CMMs, so a user can schedule parts for measurement on a CMM whose accuracy is appropriate to the task.  Moreover, PUNDIT/CMM allows users to modify their measurement strategies to lower measurement uncertainties and then output a new DMIS program.
DMIS Statements Communicate Uncertainty and Conformance Information
Beginning with its 5.0 release, DMIS provides new statements to accommodate measurement uncertainty assessment and conformance rules.  Several new statements have been introduced and many more have been modified in their syntax to permit more expansive usage.  Both Input and Output statements are involved.  Briefly these provide the following specific functionalities:

On Input:
•  Designation of an uncertainty assessment algorithm to be employed
•  Designation of a conformance rule to be employed
•  Activation/Deactivation of uncertainty assessment and, optionally, conformance rule usage
On Output:
•  Indication as to whether designated uncertainty assessment algorithm is supported by the DME or not
•  Indication as to whether designated conformance rule is supported by the DME or not
•  Reported conformance status in TOL output: (simple format, rule-based conformance, non-conformance, or indeterminate status) as well as estimated mean error and expanded uncertainty of measurement.

It should also be mentioned that when a desired conformance rule is not supported by a particular DME, DMIS 5.0 also permits the specific coding of the decision rule within the DMIS program itself.  Sample code to illustrate this can is provided within the standard.
Recognition of the importance of measurement uncertainty and its role in measurement traceability and in conformance decisions is rising rapidly in the dimensional metrology community.  The DMSC, thanks to its broad-based representation of that community, has already provided the tools required to meet this need.
Kim D. Summerhays
Technical Director
MetroSage, LLC

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