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Comparison of Switchover Methods for Injection Molding
David O. Kazmer, Sugany Velusamy, Sarah Westerdale, and Stephen Johnston
Plastics Engineering DepartmentUniversity of Massachusetts, Lowell
Priamus Users Group MeetingSeptember 30th, 2008
Agenda
Motivation Manufacturing competitiveness Characteristics of highly productive
molders Switchover Methods
Overview Experimental Setup Results Conclusions
Is U.S. Manufacturing in Decline?
1950 1960 1970 1980 1990 2000 20100
5
10
15
20
25
30
35
Year
Man
ufac
turin
g E
mpl
oym
ent
(% o
f U
S W
orkf
orce
)
Is U.S. Manufacturing in Decline?
1950 1960 1970 1980 1990 2000 20100
100
200
300
400
500
600
700
800
900
Year
Man
ufac
turin
g ou
tput
(%
of
Y19
50 O
utpu
t)
U.S. Manufacturing Productivity
1950 1960 1970 1980 1990 2000 2010
1
1.1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
1.9
2
Year
Out
put
per
Uni
t of
Lab
or C
ost
(Y20
00=
100%
)
US Industry Historical Data
Historical 0.8% Productivity IncreaseRecent 1.5% Productivity Increase
Cost CategoryTypical
PlantOverseas
PlantAutomated
Plant
Direct materials (resin, sheet, fasteners, etc.) 0.50 0.48 0.50
Indirect material (supplies, lubricants, etc.) 0.03 0.03 0.03
Direct labor (operators, set-up, supervisors, etc.) 0.25 0.08 0.05
Indirect labor (maintenance, janitorial, etc.) 0.05 0.05 0.02
Fringe benefits (insurance, retirement, vacation, etc.) 0.07 0.03 0.03
Other manufacturing overhead (rent, utilities, machine depreciation, etc)
0.10 0.08 0.10
Shipping (sea, rail, truck, etc.) 0.00 0.05 0.00
“Landed” product cost 1.00 0.80 0.73
U.S. Manufacturing Productivity
Manufacturers need 1.5% annual productivity gains to remain competitive
Where is it going to
come from?
Characteristics of Highly Competitive Molders
Highly systematized Excellent layout Consistent and often
uni-directional flow of materials
Uniform internal planning processes Uniform quality control processes.
Many highly productive facilities use only one primary supplier of plastics machinery.
Characteristics of Highly Competitive Molders
Highly utilized 24 x 7 operation 90% plus machine utilization
Steady state strategy Use fewer and better machines running
continuously rather than more machines running fewer shifts
Characteristics of Highly Competitive Molders
High yields 95% typical 99.8% not necessary
High quality assurance Automatic: in-mold systems, vision, poka-
yoke Conservative rules to contain defects
Better to automatically reject 10 good parts than accept one bad part
Characteristics of Highly Competitive Molders
Industry sector andapplication focus Connectors Gears Syringes
Focus provides Advanced application-specific knowledge Market commitment and technology
investment
U.S. Manufacturing Productivity
Manufacturers need 1.5% annual productivity gains to remain competitive
Cost CategoryTypical
PlantOverseas
PlantAutomated
Plant
Direct materials (resin, sheet, fasteners, etc.) 0.50 0.48 0.50
Indirect material (supplies, lubricants, etc.) 0.03 0.03 0.03
Direct labor (operators, set-up, supervisors, etc.) 0.25 0.08 0.05
Indirect labor (maintenance, janitorial, etc.) 0.05 0.05 0.02
Fringe benefits (insurance, retirement, vacation, etc.) 0.07 0.03 0.03
Other manufacturing overhead (rent, utilities, machine depreciation, etc)
0.10 0.08 0.10
Shipping (sea, rail, truck, etc.) 0.00 0.05 0.00
“Landed” product cost 1.00 0.80 0.73
Agenda
Motivation Manufacturing competitiveness Attributes of highly productive molders
Switchover Methods Overview Experimental Setup Results Conclusions
Overview: Switchover Concept
Switchover is the point at which the filling phase ends and packing phase starts From a controls perspective, there is a switch
in the system’s boundary conditions and stiffness
Variances cause: Dimensional
errors Part weight
variations Back flow
Filling Stage
PackingStage
Nozzle Condition
Velocity=f(t)
Pressure
=f(t)
End of FlowCondition
Pressure=0
Velocity=0
StiffnessLow to
MediumVeryHigh
Velocity
timePressure
time
Switchover
Overview:Switchover Methods
Various methods for switchover: Screw Position* Injection Time Injection Pressure Cavity Pressure Cavity Temperature Nozzle Pressure Tie Bar Deflection
Other studies have been conducted. This study is more comprehensive with respect
to number of methods and also long term variation.
Packing StageFilling Stage
Experimental Setup
Molding Machine 50 metric ton All
Electric Machine Make: Ferromatik
Milacron Model: Electra 50
Evolution Plastic Material:
AMOCO Polypropylene
Grade 10-3434
Process Monitoring & Control
Extremely well instrumented machine & mold
Screw position transducer Nozzle pressure transducer Ram load transducer 3 barrel thermocouples 4 in-mold pressure transducers 2 in-mold temperature sensors Nozzle infrared pyrometer In-mold infrared pyrometer PRIAMUS DAQ8102 acquisition
Custom machine override circuit
Internal or external voltage signal triggers the machine for switchover
Signal toMachineController
+
-
Signal fromMachineLoad Cell
DAQ Switchover Signal:
+5V or +24V
20 k
10 kPotSet Control
Voltage: 0-8 V
Sensor & Machine: +24 V
100 k
10 k
100 k
10 k
Sensor & Machine: Ground
Amplifier Power:-15 V
Amplifier Power:+15 V
ResistorDisconnect
Switch
Switchover Amplifier
Signal Relay
Signal toMachineController
+
-
+
-
Signal fromMachineLoad Cell
DAQ Switchover Signal:
+5V or +24V
20 k
10 kPotSet Control
Voltage: 0-8 V
Sensor & Machine: +24 V
100 k
10 k
100 k
10 k
Sensor & Machine: Ground
Amplifier Power:-15 V
Amplifier Power:+15 V
ResistorDisconnect
Switch
Switchover Amplifier
Signal Relay
Switchover Methods & Measured Attributes
Seven Switchover Methods Machine Controlled
Screw Position Injection Pressure Injection Time
Externally Controlled Nozzle pressure Runner Pressure Tensile Cavity
Pressure Cavity Temperature
Six Measured Attributes
Impact Thickness (mm) Impact Weight (g) Impact Width (mm) Tensile Thickness (mm) Tensile Weight (g) Tensile Width (mm)
Molding Machine Statistical Characterization
100 consecutive molding cycles were monitored & data acquired The average & standard deviation was
calculated to measure of short term variation
Plasticizing stroke
Injection speed
Pack pressure
Cooling time
Barrel Temps
Coolant Temp
Plasticizing RPM
(mm) (mm/s) (bar) (s) (C) (C) (-)
Average 85 25 200 20 210 75 150
St Dev 0.088 0.321 0.153 0.123 0.167 0.1134 0.50715
Switchover Settings
Switchover values for each method were determined to provide same part weight
Switchover methods Value
1 Switchover point (mm) 17
2 Injection time (s) 2.92
3 Machine ram pressure (bar) 340
4 Nozzle pressure (V) 1.8
5 Runner pressure (bar) 206
6 Tensile bar cavity pressure (bar) 65
7 Tensile bar cavity temperature (C) 33
Design of Experiments (DOE)
DOE performed to impose long term variation
Setup #
Plasticizing
Stroke(mm)
InjectionSpeed(mm/s)
Pack Pressure
(bar)
Coolingtime (s)
BarrelTemps (oC)
CoolantTemps (oC)
Plastizing
Rate (RPM)
0 80.0 25.0 200 20.0 210 75 150
1 79.5 23.1 199 20.7 211 76 147
2 80.5 23.1 199 19.3 209 76 153
3 79.5 26.9 199 19.3 211 74 153
4 80.5 26.9 199 20.7 209 74 147
5 79.5 23.1 201 20.7 209 74 153
6 80.5 23.1 201 19.3 211 74 147
7 79.5 26.9 201 19.3 209 76 147
8 80.5 26.9 201 20.7 211 76 153
Analysis
The 90 cycle DOE was repeated for each of the seven switchover conditions
Parts weighed & dimensions measured The data was analyzed in Matlab to provide:
Individual traces for each of 630 cycles Overlaid traces for all cycles in a DOE run Overlaid traces for all cycles in a switchover
method Regression coefficients & main effects plots
Switchover Performance:Short vs. Long Run Variation
Short
Run V
ari
ati
on (
%)
Long Run Variation (%)
More ro
bust
Switchover Performance:Long-Run Variation
Scr
ew
posi
tion
Inje
ctio
n t
ime
M
ach
ine p
ress
ure
Nozz
le p
ress
ure
R
un
ner
pre
ssu
re
C
avit
y p
ress
ure
Cavit
y t
em
pera
ture
Conclusions
Cavity temperature provided the most robustness against changes the process settings. Place the sensor near but not at the very end of flow
due to small control system delays (speed matters) Cavity pressure provided reasonable
switchover control but had susceptibility to changes in melt temperature and velocity.
Position control provided reasonable control but roughly twice the variation of cavity temperature.
Injection time is the least reproducible method for the transfer from fill to pack, with literally 10 times the variation of temperature control.
Conclusions
Measured consistency is much better than SPI guidelines of 0.2% Response time of the molding machine,
controller and ram velocity are important to process repeatability.
Weight and thickness show higher COV than length and should be used for QC
In-mold instrumentation is vital to achieving process robustness, automatic quality control,
and competitiveness.