automated visual inspection
TRANSCRIPT
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IEE 572 DESIGN OF ENGINEERING EXPERIMENTS
FALL 2000
FINAL REPORT
TERM PROJECT
AN EXPERIMENTAL DESIGN FOR IMPROVING THE ACCURATE
CLASSIFICATION OF THE IMAGES OF PRESENT AND ABSENT
COMPONENTS IN PRINTED CIRCUIT BOARDS WHEN INSPECTED
BY AN AUTOMATED VISUAL INSPECTION SYSTEM
By
PRAVEEN BABU
SREENIVASULA REDDY KATHA
LUIS MAR
0
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INTRODUCTION
The current miniaturization of the assembly surface mounted devices (SMD) in
Printed Circuit Boards (PCB) makes it a difficult task for human insectors to
determine their correct ositionin! and even their resence in the board" This task
becomes even more difficult #hen the roduction cycle time for the PCBs is
small$ leavin! the insectors #ith not enou!h time to accurately comlete their
%ob"
Fi!"# $& Picture of a PCB" 'ote the size ofComonents comared to a ten cents coin"
The tyical solution to this roblem is the introduction of an utomated isual
*nsection (*) system to relace the human insectors" The imminent
advanta!e of these systems over human insectors is their caability of reliably
insectin! a lar!e number of small comonents at a fi+ed level of erformance for
lon! eriods of time ,-." /i!ure describes a tyical PCB assembly line&
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bare PCB enters the !lue disenser #here !lue is laced to the ositions in the
board #here comonents #ill later be mounted" The ne+t oeration is the
lacement of the SMD to the board" This oeration is erformed by chi1shooters
#hich oerate in tandem (lacement machine)" The comonents are fed to the
chi1shooter by a feeder$ #hich is an array of rolls containin! the comonents to
be laced in the PCB" 2nce the comonents have been fed to the chi1shooter it
laces them on the board usin! vacuum nozzles" fter the comonents have been
laced on the board the * machine insects the resence and correct lacement
of the comonents" ,.
The 3lectronics ssembly 4aboratory (34) at rizona State 5niversity is
develoin! an inte!rated 6uality environment for SMD assembly" This
environment consists of several modules that interact #ith each other to determine
in real time the 6uality of the assembly rocess for SMDs and hence the 6uality of
the roduct" These modules are&
1D
*nsectionSystem
7lueDisenser
Machine
Placement
Machine
/eeder
'ozzle
(Piette)
PCB
Fi!"# 2% PCB ssembly 4ine
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*nsection llocation Module (*M)
8uality Monitorin! Module (8MM)
*nsection Module (*M)
The *M instructs the different insection systems as to #hich elements to insect
considerin! the total available insection time$ the insection time re6uired by
each comonent and the needs of the 8MM amon! others"
The 8MM uses the information rovided by the *M to determine if the SMD
assembly rocess is in state of statistical 6uality control"
The insection module (/i!ure 9) is in char!e of the ac6uisition$ in real time$ of
the rocess information" *t consists of four Pulini+ TM ::0 monochromatic
cameras #ith a resolution of ;-0+:
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Fi!"# && Side vie# of * system
PROBLEM DEFINITION AND FACTORS TO BE CONSIDERED
The ima!es rendered by the insection system are the basis for the decision
makin! of the entire 6uality control system" *n order for these ima!es to be useful
they must rovide sufficient level of detail so that the location$ insection and
control chart lottin! al!orithms can make a decision" This decision consists of
determinin! #hether the comonents are resent or absent and if they are resent$
determinin! their location and an!le of rotation #ith resect to an ideal osition
#ithin the board" The 6uality of the ima!e rovided by the cameras in every
insection routine deends !reatly on three factors&
*ris oenin! of lenses"
n!le of illumination of the 43Ds"
:
Set of cameras
Set of 43Ds
Servomotors
PCB
Conveyor
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Fi!"# 5(isto!rams of resent and absent oulations of comonents
>hen a comonent cannot be classified none of the 6uality control techni6ues can
be alied to decide #hether the rocess is in or out of statistical control" This
creates a !eneral failure of the system"
SELECTION OF RESPONSE VARIABLE
The values obtained from the classification al!orithm for resent and absent
oulations
A
0
50
100
150
200
250
-10
10
30
50 70 90 110
130
150
170
190
210
230
250
More
Present
Absent
0
50
100
150
200
250
Present
Absent
2verlain!
ofoulations
2verlain!
of
oulations
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are calculated usin! three different inuts$ #hich are ener!y$ correlation and
diffusion all of #hich are obtained from the ima!e rendered by the insection" /or
the urose of this e+eriment and in comliance #ith the re6uest of the *
system administrator$ #e focused on the ener!y factor" fter an insection routine
is erformed$ a reort file$ #hich contains information re!ardin! ener!y$ is
!enerated" Tables - and sho# a samle of such reorts"
The comonent that #as used as basis for the e+eriment #as the most common
comonent in the PCB$ #hich is the
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The numbers !iven in the ran!e and levels of factor G- refer to sto numbers on
the ;mm focal distance T lenses that are used by each of the cameras in the
vision system #here the lo#er the sto number the !rater the oenin! of the iris"
ccordin! to the * administrator the assumtion of linearity in the factor effects
is not clear secially in the *ris oenin! factor because #hen !oin! from one sto
number to the other the oenin! varies accordin! to a constant (:;'/
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Since the number of factors of interest for the e+eriment is 9$ #e have adoted 9
desi!n$ #ith 9 relications (refer to Table :) and : center oints"
The blockin! techni6ue #as not considered to this e+eriment because none of the
factors (or the e+eriment itself) #as affected by any nuisance source of variation"
The PCB boards belon! to the same batch$ no human interaction is related to the
insection routine that renders the ima!e of the oulation of comonents #ithin
each PCB"
The run order #as determined by Desi!n 3+ert soft#are$ the comlete test matri+
is sho#n in Table 9&
T-=# && Test Matri+
-0
Factor 1 Factor 2 Factor 3 Response
Std Run Block A:ris Opening B:Angle! "egrees C:Current! Amps O#erlap! pi$els
27 1 "lo#$ 1 2&2 !7&5 0&5
22 2 "lo#$ 1 2&8 90 0&!
3 "lo#$ 1 2&8 5 0&3
17 "lo#$ 1 2&8 5 0&!
1 5 "lo#$ 1 1&! 5 0&!
8 ! "lo#$ 1 1&! 90 0&3
12 7 "lo#$ 1 2&8 90 0&31 8 "lo#$ 1 1&! 5 0&3
21 9 "lo#$ 1 1&! 90 0&!
2! 10 "lo#$ 1 2&2 !7&5 0&5
19 11 "lo#$ 1 1&! 90 0&!
9 12 "lo#$ 1 1&! 90 0&3
! 13 "lo#$ 1 2&8 5 0&3
1! 1 "lo#$ 1 2&8 5 0&!
3 15 "lo#$ 1 1&! 5 0&3
2 1! "lo#$ 1 1&! 5 0&3
11 17 "lo#$ 1 2&8 90 0&3
7 18 "lo#$ 1 1&! 90 0&3
2 19 "lo#$ 1 2&8 90 0&!
23 20 "lo#$ 1 2&8 90 0&!
18 21 "lo#$ 1 2&8 5 0&!
5 22 "lo#$ 1 2&8 5 0&3
25 23 "lo#$ 1 2&2 !7&5 0&5
10 2 "lo#$ 1 2&8 90 0&3
20 25 "lo#$ 1 1&! 90 0&!
13 2! "lo#$ 1 1&! 5 0&!
15 27 "lo#$ 1 1&! 5 0&!
28 28 "lo#$ 1 2&2 !7&5 0&5
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The results table for a number of relicatesE9 is sho#n in Table :&
T-=# '& Hesults table
The result table sho#s FF"A as the ercenta!e alha level of all effects at
standard deviations from the mean$ #hich is sufficiently accurate in terms of this
e+eriment"
PERFORMING THE EXPERIMENT
The run order (random) and combination of factor levels rovided by desi!n
e+ert #as follo#ed and the results rendered are sho#n in Table ; in the
endi+" >hile runnin! the e+eriment the most difficult factor to vary #as the
current of the 43D anels because of the lack of accessibility resented by the
layout of the machine" >hile chan!in! the *ris oenin! an ad%ustment to the focus
of the camera #as also re6uired to rovide a clear ima!e in the monitor$ this
ad%ustment (or the check for a roer ima!e) #as re6uired each time the iris
oenin! #as chan!ed from one level to the ne+t" The variation of the an!le factor
--
%o&er ( alp)a le#el *or e**ect o*
Term StdErr++ ,F Ri-S.uared 1/2 Std0 "e#0 1 Std0 "e#0 2 Std0 "e#0
A 0&201 1 0 21&1 ' !3&3 ' 99&! '
" 0&201 1 0 21&1 ' !3&3 ' 99&! '
C 0&201 1 0 21&1 ' !3&3 ' 99&! '
A" 0&201 1 0 21&1 ' !3&3 ' 99&! '
AC 0&201 1 0 21&1 ' !3&3 ' 99&! '
"C 0&201 1 0 21&1 ' !3&3 ' 99&! '
A"C 0&201 1 0 21&1 ' !3&3 ' 99&! '
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#as the one that did not resent any ma%or difficulty" The comutation of the
resonse variable in each run #as erformed by the method described earlier in
this reort"
STATISTICAL ANALYSIS OF THE DATA
The statistical analysis of the resonse variable and the interretation of the results
derived form this analysis #as erformed by usin! the Desi!n 3+ertJ soft#are"
Tables ; to < as #ell as !rahs - to are resented in the endi+" Table ;$ Table
A sho# the Hun matri+ #ith resonses and Desi!n summary resectively"
The hi!hest order interaction term #as assumed as the error term" The half normal
lot (7rah-) clearly sho#s that $ C$ C are the si!nificant factors" Takin! the
si!nificant terms as the main effects and the remainin! terms as error terms refines
the model" The de!rees of freedom for the model are 9$ for curvature - and for the
error are :"
The analysis of variance table (Table ) rovided by Desi!n 3+ert J sho#s the
values$ the / values$ De!rees of freedom$ Sum of s6uares and Mean s6uare terms"
The hi!h value of the model /1value is stron! evidence that it is si!nificant"
ccordin! to the Desi!n 3+ert J reort$ there is only a 0"0-K chance that a
LModel /1alueL this lar!e could occur due to noise" *t is imortant to mention
that as sho#n by 7rah ; (lot of residuals s" current) the assumtion of
homo!eneity of variance seems not to hold" This haens even after data
transformation has been alied to the data (S6uare root transformation #ith
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constant kE as su!!ested by Desi!n 3+ertJ #hen observations seem to follo# a
Poisson distribution)" o#ever$ due to the hi!h value of the / ratioE
Model
MS
MS
(;-" 9)$ the effects of non1constant variance #ill be very unlikely to alter the
results obtained by the e+eriment" More over$ since the e+eriment #as a
balanced fi+ed effects model the results are only sli!htly affected #hen the
assumtion of constant variance is violated ,:."
The analysis also found that there is evidence of si!nificant second1order
curvature in the resonse as measured by difference bet#een the avera!e of the
center oints and the avera!e of the factorial oints over the re!ion of e+loration"
He!ression 36uation obtained from Desi!n 3+ertJ is as sho#n belo#"
-9
(inal E)uation in *er+s of Co,e, (a#tors
.)rt/erla 2&004
3&!71378879-1&192!518 6 A
1&330008522 6 C
-0&3!7902103 6 A 6 C
(inal E)uation in *er+s of A#tual (a#tors
.)rt/erla 2&004
0&00!80250
-0&179315 6 ris ening
17&85988!01 6 Current
-&08780118 ris ening 6 Current
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ccordin! to Desi!n 3+ertJ the lack of fit is not si!nificant relative to the ure
error" This result su!!ests that this model is ade6uately fitted by the re!ression
e6uation"
Hesiduals and Model de6uacy&
The 7rah sho#s the lot of 'ormal robability vs studentized residuals "The
assumtion of normality is satisfied after the s6uare root transformation">e have
considered the s6uare root transformation since the observations in this model
follo#s the oisson distribution as our resonse deals #ith countin! the number of
comonents on the PCB board and this is also su!!ested by Desi!n 3+ertJ
B2C2 lot" The 7rahs 9 and : sho#s the lots of residuals vs" redicted
values and residuals vs" run order" These !rahs sho# that the indeendence
assumtion on the errors has not been violated and also sho#s that there is no non1
constant variance" 7rahs A and are the lots of resonse surfaces" These !rahs
su!!ests that the resonse increases #ith the increase of the increase in Current
and *ris oenin! "The interaction bet#een these si!nificant factors can be seen
from the curvature of the resonse surface"
The H1S6uared value of 0"FFAF sho#s that the roortion of the variability in the
data is mostly e+lained by the model" lso$ the LPred H1S6uaredL and theLd% H1
S6uaredL values of 0"FF;A and 0"FFAA resectively are in reasonable a!!reement
#ith each other" Because the Lde6 PrecisionL ratio (#hich measures the si!nal to
noise ratio) is --A"000 this model can be used to navi!ate the desi!n sace ,:."The
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PH3SS value of 0"9A su!!ests that the model for the e+eriment can be used in a
ne# e+eriment to redict the resonse confidently"
CONCLUSIONS AND RECOMMENDATIONS
The identification of the li!ht intensity of the 43D anels (current factor)$ the iris
oenin! of the lenses of the cameras and their interaction as the si!nificant factors
in controllin! the clarity of the ima!e used by the * system$ #ill lead to an
increase of accuracy and efficiency in the calibration rocess of the insection
machine"
The ma+imum value obtained for the difference in mean ener!y value for resent
and absent oulations (:"< i+els) #as obtained #hen the *ris factor #as in the
hi!h level (-"A ste numbers) the Current factor #as in the hi!h level (0"A ms)
and the an!le factor #as in the lo# level (:;N)" *t is then recommended to run the
insection machine at these levels" The si!nificance of the non1linearity bet#een
the hi!h and lo# levels of the factors (esecially iris oenin!) needs to be taken
into account #hen ad%ustin! the levels in future research to otimize the resonse
variable defined in this e+eriment and as su!!ested by 7rahs A and "
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REFERENCES
-" MuOoz$ 4"$ et al$Multivariate On-line Quality Monitoring of SMD Assembly$
>orkin! Paer$ The 5niversity of Te+as t 3l Paso$-FFF
" illalobos$ " and erduzco$ "$ Integration of Quality and rocess lanning
Activities in SMD Assembly$ >orkin! Paer$ The 5niversity of Te+as at 3l
Paso$-FF
9" rellano$ M" and illalobos$ "$ !ector "lassification of SMD Images$ >orkin!
Paer$ rizona State 5niversity$-FFF
:" Mont!omery$ D"C" (000)$ Design and Analysis of E#periments$;th3dn$ ohn
>iley = Sons$ 'e# Qork"
-A
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A#.>i)
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Table ;& Hun matri+ #ith resonse"
-ig? V(
nter#et 3&!71378879 1 0&021008112 3&!27920289 3&71837
A- ris en -1&192!518 1 0&021008112 -1&23592377 -1&1901 1
C-Current 1&330008522 1 0&021008112 1&28!59932 1&373!7 1
AC -0&3!7902103 1 0&021008112 -0&113!0!93 -0&32 1
Center Poin 0&75552183 1 0&055582239 0&!0535!1 0&870505 1
(inal E)uation in *er+s of Co,e, (a#tors
.)rt/erla 2&004
3&!71378879
-1&192!518 6 A
1&330008522 6 C
-0&3!7902103 6 A 6 C
(inal E)uation in *er+s of A#tual (a#tors
.)rt/erla 2&004
0&00!80250
-0&179315 6 ris ening
17&85988!01 6 Current
-&08780118 ris ening 6 Current
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Table alf :or+al lot
GEffe#tG
0&00 0&!7 1&33 2&00 2&!!
0
20
0
!0
70
80
85
90
95
97
99
A
C
ACalf 'ormalK Probability
7rah-& alf 'ormal Plot of the factor effects
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-
DE. 7:-EFPE R*Plot.)rt /1erl a3 2 &00 4
.tu,en t i He, R es i,ua ls
:or+al'
2robability
:or +a l lo t o f re s i,u a ls
-2& 72 -1&! -0&21 1&05 2&31
1
5
10
20
30
50
70
80
9095
99
7rah & 'ormal Probability Plot of Hesiduals
DE. 7:-EFPE R*Plot.)rt /1erl a3 2 &00 4
P r e , i # t e ,
.tu,entiHe,Resi,uals
Re s i,u a ls s & Pr e , i# te ,
-3&00
-1&50
0&00
1&50
3&00
1&52 2&78 &0 5&30 !&5!
7rah 9& Hesiduals vs" Predicted
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DE . : -EFPER *P lot.)r t/er la2& 004
R un : u+be r
.tu,entiHe,Resi,uals
Re s i, u a ls s & R u n
-3&00
-1&50
0&00
1&50
3&00
1 10 19 28
D E. :-E FP ER* Plot.)r t/ er l a2&004
C u r r en t
.tu,entiHe,Resi,uals
Re s i,u a ls s & Cu rr en t
-3&00
-1&50
0&00
1&50
3&00
0&30 0&37 0&5 0&52 0&!0
7rah ;& Hesiduals vs" Current
7rah :& Hesiduals vs" Hun 'umber
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DE . : -EFPER*Pl ot
.)r t/er la2& 00 4FA r is ening