SEMINAR OVER VARIOUS OPTIMIZATION TECHNIQUES OF CMM BY STUDYING THREE IMPORTANT RESEARCH PAPERS. ALSO COVERED ARTIFICIAL NEURAL NETWORK CONCEPT.

1. OPTIMIZATION OF CMM MACHINE
By,
STUDENT – VIJAY S. MOHANGEKAR
M.TECH 1ST YEAR M/CDESIGN
VJTI, MUMBAI.
ROLL NUMBER – 192090010
Rapid Product Development
Seminar
On

2. STUDY 1:
PRECISION STUDY OF A CO-ORDINATE
MEASURING MACHINE USING SEVERAL
CONTACT PROBES.
• Contact probes over non-contact probes.
• Comparative study between the precision study of a
touch probe and a scanning probe.
• Probe utilized counts in one of the most important aspect
of CMM precision.
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3. INTRODUCTION
• A comparative study between the precision obtained
with a touch probe(TP-200) and that obtained with a
scanning probe(SP-25) is carried out for a specific
coordinate measuring machine.
• Probes by RENISHAW.
• Type of probe utilized is one of the most important
aspect of Precision analysis of any CMM.
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4. SETUP LAYOUT
• Moving bridge CMM used.
• DEA Global Image Clima.
• the standard uncertainty of the
CMM is given by :
𝑢 𝐶𝑀𝑀= (1.7 + 3L/1000) μm, where
L is
the length being evaluated, and
its measuring volume is as
follows:
850 mm (X) x 1460 mm (Y) x
780 mm (Z).
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5. WORKPIECE PART
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6. 6

7. UNCERTAINTY ANALYSIS
• Expression of Uncertainty in Measurement ISO 1995 was
followed
• Expression :𝑢 𝑝𝑎𝑟𝑡
2
= 𝑢 𝑥
2
+𝑢 𝐶𝑀𝑀
2
+𝑢 𝑝𝑟𝑜𝑏𝑒
2
• 𝑢 𝑝𝑎𝑟𝑡Is the uncertainty of measured dimension.
• 𝑢 𝑥 Is the standard deviation of the mean distribution.
• 𝑢 𝐶𝑀𝑀 Is the uncertainty of the CMM.
• 𝑢 𝑝𝑟𝑜𝑏𝑒 Is the uncertainty of the used probe.
• Expanded uncertainty :
𝑈 𝑝𝑎𝑟𝑡 = 𝑘 . 𝑢 𝑝𝑎𝑟𝑡
In this study coverage factor of k = 2 (1.96) was selected which
produces an interval of confidence level 95.45%
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10. CONCLUSION OF CASE STUDY 1
• The performance of the two contact probes turned to be
different and the SP-25 probe shows a better performance than
the TP-200 probe.
• Also no significant differences in the precision of the
measurements when three, four, or five contact points were
used to define the planes of the straight ladder.
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11. Study 2 :
CMM UNCERTAINTYANALYSIS USING THE
COMBINATORIAL CYCLIC METHOD OF
OPTIMIZATION.
• Objective function: to minimize geometric deviations between a
virtual product and a real product.
• CMM accuracy verification based on Combinatorial Cyclic
method of Optimization used, over old CMM software.
• A software dedicated to perform sphere fitting and error analysis
developed by SIEMENS.
• Standard deviation is used as the accuracy indicator.
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12. COMBINATORIAL-CYCLIC METHOD
• The programe has capability of selecting the points from a
large data file, keeping almost same accuracy of the analysis.
• Developed procedures based on neural network
techniques(ANN).
• Increments in a program loop 𝑑 𝑣(j) and code values 𝑖 𝑣(j) define boundaries
and real values of variables:
𝑣(𝑗)𝑖 = (j) = 𝑣(𝑗)0 + 𝑖 𝑣(j) 𝑑 𝑣(j)
There are criteria of an accuracy estimation of curves and surfaces, which
can be used as the objective function( standard deviation)
 = 1
𝑛(𝑑(𝑖))2
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13. (ARTIFICIAL NEURAL N/W) ANN
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14. CMM ACCURACY INSPECTION
• Measuring a set of points on the reference sphere and submitting their
coordinates as input for optimization algorithm.
• We will not need a CAD model for known geometrical entity like sphere.
• The algorithm will continue to search for design variable optimal values
until the desired tolerance is achieved.
The STANDARD DEVIATION calculated for the best fit sphere is taken
as an indicator for the accuracy of sphere.
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15. CONCLUSION OF STUDY 2
• Combinatorial cyclic method of optimization method
was used for analysis of CMM accuracy.
• This approach proved it’s reliability and efficiency in
very short processing time.
• Speeding up process and quality products
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16. ARTIFICIAL NEURAL NETWORK
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18. ARTIFICIAL NEURAL NETWORK
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19. SOME REAL LIFE USES OF ANN
RESTORE COLORS TO BLACK N WHITE IMAGES :
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20. PIXEL ENHANCING :
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21. GENERATING NEW IMAGES :
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22.  LIP READING : 95% accuracy possible
 CREATING SCENE FROM SCRATCH :
e.g. Sunrise to sunset
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23. Study 3 :
DETERMINING THE OPTIMAL PARAMETER OF
CMM WITH DESIGN OF EXPERIMENT.
• Probe size, number of measurement points, measuring speed
selected as study parameters from literature review.
• Length of probe also counts in parameters
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24. LEVEL SETTING :
• A : Probe size (mm) = 0.5 (low level)
= 1 (high level)
• B : Number of points = 8 (low level)
= 16 (high level)
• C : Speed (mm/s) = 1 (low level)
= 8 (high level)
• Measurements repeated 5 times for each parameter.
• Diameter deviation and roundness deviation considered
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A case study from swage hole measurement of
hard disk drive actuator arm done.

26. RESULTS AND DISCUSSIONS
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27. CONCLUSION OF STUDY 3 :
• Smaller probe size provides significant improvement in
measurement accuracy.
• Number of measurement points has no significant effect on
accuracy.
• Lower measurement speed provides greater accuracy.
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28. FINAL CONCLUSION OVER THESE 3 CASE STUDIES.
• For optimized results from CMM we choose :
1.Contact probe.
2.Scanning probe over touch probe.
3.Combinatorial cyclic optimization method.
4.Smaller probe size.
5.More measuring points.
6.Lower measuring speed.
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29. REFERENCES
1. I. Puertasa et.al. “Precision study of a coordinate measuring machine using several
contact probes”.
1. Kusalin Sangnuan and Wimalin S. Laosiritaworn, “Determining the Optimal
Parameter of Coordinate Measuring Machine with Design of Experiment”.
2. Stanisław Kachel et.al. “Coordinate measuring machine uncertainty analysis using
the combinatorial cyclic method of optimization ”
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30. THANK YOU
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