Download - Surface Metrology Essay
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Omesh Kamat
Professor Brown
Final Paper Surface Metrology
October 21, 212
!hat " #earne$
!hat is surface metrology% Surface metrology is the measurement an$ analysis of
features of surfaces an$ its beha&iors' Surface form, wa&iness, an$ roughness are all parameters
that are most associate$ with surface metrology' !hy is surface metrology important% Surfaces
are chaotic, an$ so surface metrology helps with measurement an$ analysis of creation of the
surface an$ its beha&ior by using tools such as the Olympus #()* O#S+ Microscope'
*o better un$erstan$ surface metrology, it is important to comprehen$ roughness'
Surfaces co&er e&erything an$ so roughness is &ery important' oughness is either ma$e in
nature or man-ma$e' Manufacturing is the process use$ to ma.e surfaces with $esire$ properties'
"t is goo$ to .now that roughness is &aluable because it can be useful with lubrication, a$hesion,
an$ friction an$ roughness also influences performance' People usually belie&e that smoother is
better but that is not always the case' "n the beginning, smooth is better but then as roughness
increases later, performances increases as well' *he most commonly use$ roughness
measurement is / which is a&erage roughness' /lso there are cutoffs for specifying roughness
an$ this is usually gi&en by the $esigner' 0ifferent cutoffs ha&e a huge impact on roughness
&alues an$ so it is &ery important to get the cutoff beforehan$'
"t is not only necessary to .now what roughness is, but it is also important to .now how
to measure an$ calculate roughness' /s #or$ Kel&in sai$, !hen you measure, you ha&e to
epress it in numbers an$ then you .now something about it3' *here are many ways of $oing
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measurement of the surface but the two main ones are contact an$ optical measurement' 4ontact
is when there is a force hol$ing a stylus $own on a surface an$ it shows what the surface is li.e
on a &ertical graph' / $own-si$e of contact measurement is that sensiti&e surfaces can be
$amage$ because of the stylus an$ the force hol$ing $own on it' Optical is the use of an
instrument such as the Olympus #()* O#S+ to get a measurement an$ then analy5e it in
60' *his way, there is a great, sharp image an$ height information can be foun$ by changing it to
6 $imensional' *here are $ifferent measurements that can be foun$ using either techni7ue' 8ot
only there is the /but there is also 9 :stan$ar$ $e&iation of surface heights;, * :pea. to
&alley;, P :pea. height;, an$ < :&alley height;' /&erage roughness is sometimes useless
because it is in$epen$ent of what or$er the heights are obser&e$' *he / is also insensiti&e to the
fine scale topographic $etails'
"n surface metrology, correlating an$ $iscriminating are &ery important' 4orrelation helps
with the optimi5ation of the pro$uct an$ $esign while $iscrimination helps with 7uality
assurance' For correlation, it is important to ma.e a graph of performance &ersus roughness an$
manufacturing &ersus roughness' *his has to be $one with eperimentation' *here are many
approaches to multi-scale fractal analysis' One is scale $ecomposition where form is the largest
scale, then wa&iness, an$ finally roughness' *hen there is the $iscrimination test which is
comparing F- test to critical mean scale ratio an$ correlation test which is comparing the
$ifferent correlation coefficients of each scale'
/nother important topic is relati&e length :length scale fractal analysis;' "t is necessary to
notice that relati&e length $epen$s on the scale an$ as scale is $ecrease$, usually relati&e length
increases' *he formula for relati&e length is the sum of all :1=cos :angle in terms of ais; >
:pro?ecte$ length of step=total pro?ecte$ length;;' /rea scale fractal analysis is another techni7ue
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use$ in surface metrology' *riangular patches are use$ at $ifferent scales an$ this calculate$ the
apparent area' *hen the relati&e area is calculate$ area=nominal area' *he formula for relati&e
area is the sum of all :1=cos :angle in terms of ais;>:pro?ecte$ area of triangle=total pro?ecte$
area;;' /rea is &ery important as a teture characteri5ation parameter because it is in many
$ifferent processes such as in mass transfer, an$ 8ewton@s law of cooling' "t is necessary to .now
that the area of a surface is not uni7ue it $epen$s on the scale of obser&ation or calculation3'
For $iscrimination an$ correlation tests, the process is to first prepare the surfaces,
measure the tetures, analy5e the measurements an$ calculate characteri5ation parameters, an$
then finally run statistical tests' *o analy5e, it is goo$ to first select a metho$, then remo&e
artifacts, an$ use filtering' "n statistical tests, for $iscrimination $o F an$ * tests from statistics'
For correlation, $o the regression tests' "n the en$, $ecomposition by scale can impro&e the
ability to $iscriminate an$ fin$ correlations'
Finally, the last presentation was about aiomatic $esigns an$ how they are the best
$esigns' /n aiomatic $esign is base$ on two laws, maimi5e the in$epen$ence of the functional
elements, an$ minimi5e the information content' *his way the $esign can a&oi$ uninten$e$
conse7uences an$ maimi5e chance of success' "t is important to be able to tell a goo$ $esign
from a ba$ one' "n engineering $esign, one can either use the algorithmic approach or the
aiomatic approach' /lgorithmic approach assumes correct process results in goo$ result an$
re7uires trial an$ error' *his $oes not gi&e the guarantee of ha&ing the best solution' /iomatic
approach on the other han$, pro&i$es aioms an$ is a way of arri&ing at the best $esign solution
for the re7uirements gi&en'
*he three basic elements of engineering $esign are aioms :maimi5e in$epen$ence,
minimi5e information;, structures :hori5ontal $ecomposition, &ertical $ecomposition;, an$
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processes :5ig5agging $ecomposition, physical integration;' Some of the $omains in structures
are customer nee$s 48 what a$$s &alue, functional re7uirements F what it $oes, $esign
parameters 0P what it loo.s li.e, process &ariables P< how you ma.e it, an$ constraints
4O8 what nee$s to be a&oi$e$'