This document discusses using the drift method to determine calibration intervals for gauges based on their past behavior. It summarizes the drift method, which models the wear trend of similar gauges and sets the calibration interval based on the maximum statistically observed drift. The method requires studying a large number of gauges and knowing their calibration history. The document also describes how to use calibration analysis to identify atypical gauge behavior and refine the maximum drift value over time as more calibration data is collected. Comparing drift trends within and across companies can provide insights to improve the calibration process.

1. 21 Septembre 2017
Method of the drift:
More than just an
optimization method
18th International Congress of Metrology

2. Periodic calibration
Situation overview
• Normative obligation (ISO 9001)
• Industrial cost (direct or indirect)
 Choose the calibration interval : FD X07-014
 use the result : assessment and archiving (local and binary use)
 Can we actually use the results of the periodic calibrations?

3. Summary
1. Presentation of the Drift Method (FD X07-014)
2. Use of information
 During study
 Calibration analysis
 Build up experience
 Study limited to Gauges

4. Drift method
Method idea
• Applicable to an equipment that
actually drifts
Example : Gauges
• Anticipate date of wear limit by
past behavior
Change in frequency of use of equipment may affect the drift
 Non-monotonic drift  wrong estimate of the wear date
Study the behavior of a set of equipment
12,596
12,595
12,594
12,593
12,592
12,591
12,590 Wear
limit
date

5. Drift method
Application of the method
Study:
• Study on a group of similar equipments
• Modeling of the wear trend of each
instrument
• Determination of the case where the
drift is statistically maximum = αmax
Application :
• Next calibration date of each equipment
determined by αmax
12,596
12,595
12,594
12,593
12,592
12,591
12,590 Wear
limit
Last
calibration
α max
date
Next calibration
α max
12,596
12,595
12,594
12,593
12,592
12,591
12,590 Wear
limit
date

6. Deepening of the method
Statistical study of the wear
 This histogram represents the “usual” behavior
of the company's gauge
α max
12,596
12,595
12,594
12,593
12,592
12,591
12,590 Wear
limit
date
-0,7 µm/year
µm/year
Frequency
-0,7
0 µm/year
0
Wear Histogram
+0,3 µm/year
+0,3

7. Drift method
• Advantages :
- Specific study for company
- Periodicity technically justified
- Periodicity adapted to each equipment
new ring : Large periodicity – Worn ring : low periodicity
• Drawbacks :
- Method limited to equipments that actually have drift
- Need for a large number of equipment for the statistical study
minimum 20 equipment by category
- Need to know the history of measurement
3 or 2 previous calibrations of the equipment

8. During Study
Atypical family (§3.1)
Atypical family
 Identify risk behaviors and react before the problem appears

9. During Study
Too short interval (§3.2)
4.698
4.6985
4.699
4.6995
4.7
4.7005
4.701
4.7015
Wear
Hypothesis:
• Gauge not used
• Ucalibration = 1µm
• « Opposite » measured values = 0,3µm
• Probability of the event = 8%
+7,2 µm/yearInterval 1 month
Interval 1 year +0,6 µm/year
 Very short interval is not necessary a good thing !
Scary

10. Calibration analysis
Unitarian result (§3.3.1)
Diameter
Date
Evolution of a plain plug gauge diameter
Diameter
Date
Evolution of a plain plug gauge diameter
 Don’t forget the uncertainty before concluding
Diameter
Date
Evolution of a plain plug gauge diameter

11. Diameter
Date
Gauge G032 diameter
Calibration analysis
Several “suspect” results (§3.3.1)
 Event if gauges are conform, identify the drift in the results and
analyse the impact
Diameter
Date
Gauge G046 diameter
Diameter
Date
Gauge G201 diameter
Diameter
Date
Gauge G820 diameter
Diameter
Date
Gauge G 236 diameter
• Modification of the value of the standard of
the laboratory
• Change of the operator
• Change of calibration laboratory
• Incorrect adjustment of the measuring bench
• …
“Systematic” gap
on last calibration

12. Calibration analysis
Wear too fast (§3.4)
wear
Max slope, FUmax
 Event if gauges are conform, identify the drift in the result and
analyse the impact
• Change in the use of the gauge in
the firm
• Calibration error

13. Build up experience
Refin the FUmax (§3.6.1)
• Due to calibration uncertainty, the wear slope is blurred.
• The wear histogram is enlarged.
• So the FUmax is increased.
Gauge Diameter
Exemple (Monte Carlo simulation) :
Hypothesis:
• Large familly of Gauge not used (the true slope is 0 µm/year)
• Ucalibration = 1µm
Case 1 : 1 year history Case 2 : 3 years history
2 calibrations by gauge 5 calibrations by gauge
Fumax = -1,4µm/year Fumax = -0,4µm/year
 With new calibrations, improve the knowledge of FUmax and
your wear Histogram

14. Build up experience
Inter compagnies comparisons (§3.6.2)
Reference curve built with wear slope of
defined type, from collection of various
society in similar field of use.
My curve built from my calibration
history.
Compatible
 Identify why my use of gauge can be different from usual use

15. Conclusion
Don’t let precious information get lost in archiving.
Results of periodical calibration can and should be use to improve
the knowledge of the process