Comparison of Switchover Methods in Injection Molding for
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Transcript Comparison of Switchover Methods in Injection Molding for
Comparison of Switchover
Methods for Injection Molding
David O. Kazmer, Sugany Velusamy,
Sarah Westerdale, and Stephen Johnston
Plastics Engineering Department
University of Massachusetts, Lowell
Priamus Users Group Meeting
September 30th, 2008
Agenda
Motivation
Manufacturing competitiveness
Characteristics of highly productive
molders
Switchover Methods
Overview
Experimental Setup
Results
Conclusions
Is U.S. Manufacturing
in Decline?
Manufacturing Employment (% of US Workforce)
35
30
25
20
15
10
5
0
1950
1960
1970
1980
Year
1990
2000
2010
Is U.S. Manufacturing
in Decline?
900
Manufacturing output (% of Y1950 Output)
800
700
600
500
400
300
200
100
0
1950
1960
1970
1980
Year
1990
2000
2010
U.S. Manufacturing Productivity
2
Output per Unit of Labor Cost (Y2000=100%)
1.9
1.8
US Industry Historical Data
Historical 0.8% Productivity Increase
Recent 1.5% Productivity Increase
1.7
1.6
1.5
1.4
1.3
1.2
1.1
1
1950
1960
1970
1980
Year
1990
2000
2010
U.S. Manufacturing Productivity
Manufacturers need 1.5% annual
productivity gains to remain competitive
Cost Category
Typical
Plant
Overseas
Plant
Automated
Plant
Direct materials (resin, sheet, fasteners, etc.)
0.50
0.48
0.50
Indirect material (supplies, lubricants, etc.)
Where
is 0.05
0.08
0.05
0.05 to 0.02
it going
0.07
0.03
0.03
come from?
0.03
0.03
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
Direct labor (operators, set-up, supervisors, etc.)
Indirect labor (maintenance, janitorial, etc.)
Fringe benefits (insurance, retirement, vacation, etc.)
Other manufacturing overhead (rent, utilities, machine
depreciation, etc)
0.03
0.25
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 and
application focus
Connectors
Gears
Syringes
Focus provides
Advanced application-specific knowledge
Market commitment and technology investment
Obsolete vs. Competitive
Number of machines
Obsolete
Competitive
Obsolete vs. Competitive
Number of workers
Obsolete
Competitive
Obsolete vs. Competitive
Number of supervisors
Obsolete
Competitive
Obsolete vs. Competitive
Plant size
Obsolete
Competitive
500 m2
10,000 m2
Obsolete vs. Competitive
Energy usage
Obsolete
Competitive
U.S. Manufacturing Productivity
Manufacturers need 1.5% annual
productivity gains to remain competitive
Cost Category
Typical
Plant
Overseas
Plant
Automated
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: Velocity Switchover
Filling
Packing
Dimensional
Stage
errors
Nozzle
Velocity
Part weight
Condition
=f(t)
Pressure
variationsEnd of Flow
Pressure
Back flowCondition
=0
Stiffness
Low to
Medium
Stage
Pressure
=f(t)
Velocity
=0
Very
High
time
time
Overview:
Switchover Methods
Various methods for switchover:
Screw Position*
Injection Time
Injection Pressure
Cavity Pressure
Cavity Temperature
Nozzle Pressure
Tie Bar Deflection
Filling
Stage
Packing Stage
Other studies
have been conducted.
This study is more comprehensive with respect to
number of methods and also long term variation.
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
Sensor & Machine: Ground
DAQ Switchover
Signal:
+5V or +24V
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
100 k
Resistor 10 k
Disconnect
Switch
Amplifier
Power:
-15 V
Amplifier
Power:
+15 V
10 k
Switchover
Amplifier
Signal Relay
100 k
10 kPot
20 k
Set Control
Voltage:
0-8 V
Signal to
Machine
Controller
Signal from
Machine
Load Cell
Sensor & Machine: +24 V
Custom machine override circuit
Internal or external voltage signal
triggers the machine for switchover
Switchover Methods &
Measured Attributes
Seven Switchover Methods
Machine Controlled
Six Measured Attributes
Screw Position
Injection Pressure
Injection Time
Externally Controlled
Nozzle pressure
Runner Pressure
Tensile Cavity Pressure
Cavity Temperature
Impact Thickness (mm)
Impact Weight (g)
Impact Width (mm)
Tensile Thickness (mm)
Tensile Weight (g)
Tensile Width (mm)
Single Cycle: Screw Position,
Nozzle Pressure, & Cavity Pressure
10 Consecutive Cycles
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)
Injection
Speed
(mm/s)
Pack
Pressure
(bar)
Cooling
time
(s)
Barrel
Temps
(oC)
Coolant
Temps
(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
90 Cycles across the DOE for Ram
Position (Conventional) Switchover
Position
Switchover
Main Effects on Impact Thickness
for Ram Position Switchover
Good process robustness
Time Switchover
90 Cycles across the DOE for
Filling Time Switchover
Main Effects on Impact Thickness
for Filling Time Switchover
Very poor process robustness
90 Cycles across the DOE for
Cavity Pressure Switchover
Pressure
Switchover
Main Effects on Impact Thickness
for Cavity Pressure Switchover
Good process robustness
90 Cycles across the DOE for
Cavity Temperature Switchover
Temperature
Switchover
Main Effects on Impact Thickness
Cavity Temperature Switchover
Best process robustness
Coefficient of Variation
COV = σ / µ
Different switchovers are best for different attributes
Short Run Variation (%)
Switchover Performance:
Short vs. Long Run Variation
Long Run Variation (%)
Injection time
Cavity temperature
Cavity pressure
Runner pressure
Nozzle pressure
Machine pressure
Screw position
Switchover Performance:
Long-Run Variation
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.
Acknowledgements
National Science Foundation grant number
DMI-0428366/0428669
Priamus System Technologies