1. 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

2. Agenda Motivation Switchover Methods Manufacturing competitiveness
Characteristics of highly productive molders
Switchover Methods
Overview
Experimental Setup
Results
Conclusions

3. Is U.S. Manufacturing in Decline?

4. Is U.S. Manufacturing in Decline?

5. U.S. Manufacturing Productivity

6. U.S. Manufacturing Productivity
Manufacturers need 1.5% annual productivity gains to remain competitive
Where is it going to come from?
Cost Category
Typical Plant
Overseas Plant
Automated Plant
Direct materials (resin, sheet, fasteners, etc.)
0.50
0.48
Indirect material (supplies, lubricants, etc.)
0.03
Direct labor (operators, set-up, supervisors, etc.)
0.25
0.08
0.05
Indirect labor (maintenance, janitorial, etc.)
0.02
Fringe benefits (insurance, retirement, vacation, etc.)
0.07
Other manufacturing overhead (rent, utilities, machine depreciation, etc)
0.10
Shipping (sea, rail, truck, etc.)
0.00
“Landed” product cost
1.00
0.80
0.73

7. 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.

8. 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

9. 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

10. Characteristics of Highly Competitive Molders
Industry sector and application focus
Connectors
Gears
Syringes
Focus provides
Advanced application-specific knowledge
Market commitment and technology investment

11. Obsolete vs. Competitive
Number of machines
Obsolete Competitive

12. Obsolete vs. Competitive
Number of workers
Obsolete Competitive

13. Obsolete vs. Competitive
Number of supervisors
Obsolete Competitive

14. Obsolete vs. Competitive
Plant size
Obsolete Competitive

15. Obsolete vs. Competitive
Energy usage
Obsolete Competitive

16. 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
Indirect material (supplies, lubricants, etc.)
0.03
Direct labor (operators, set-up, supervisors, etc.)
0.25
0.08
0.05
Indirect labor (maintenance, janitorial, etc.)
0.02
Fringe benefits (insurance, retirement, vacation, etc.)
0.07
Other manufacturing overhead (rent, utilities, machine depreciation, etc)
0.10
Shipping (sea, rail, truck, etc.)
0.00
“Landed” product cost
1.00
0.80
0.73

17. Agenda Motivation Switchover Methods Manufacturing competitiveness
Attributes of highly productive molders
Switchover Methods
Overview
Experimental Setup
Results
Conclusions 17

18. 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
Velocity
time
Switchover
Filling Stage
Packing Stage
Nozzle Condition
Velocity =f(t)
Pressure =f(t)
End of Flow Condition
Pressure=0
Velocity =0
Stiffness
Low to Medium
Very High
Pressure
time 18

19. 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 Stage
Filling Stage 19

20. Experimental Setup Molding Machine Plastic Material:
50 metric ton All Electric Machine
Make: Ferromatik Milacron
Model: Electra 50 Evolution
Plastic Material:
AMOCO Polypropylene
Grade

21. 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

22. 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)

23. Single Cycle: Screw Position, Nozzle Pressure, & Cavity Pressure

24. 10 Consecutive Cycles

25. 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)
(-)
Average 85 25
200 20
210 75
150
St Dev
0.088
0.321
0.153
0.123
0.167
0.1134

26. 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

27. 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
Plastizing
Rate
(RPM)
80.0
25.0
200
20.0
210 75
150 1
79.5
23.1
199
20.7
211 76
147 2
80.5
19.3
209
153 3
26.9 74 4 5
201 6 7 8

28. 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

29. 90 Cycles across the DOE for Ram Position (Conventional) Switchover

30. Main Effects on Impact Thickness for Ram Position Switchover
Good process robustness

31. 90 Cycles across the DOE for Filling Time Switchover31

32. Main Effects on Impact Thickness for Filling Time Switchover
Very poor process robustness

33. 90 Cycles across the DOE for Cavity Pressure Switchover33

34. Main Effects on Impact Thickness for Cavity Pressure Switchover
Good process robustness

35. 90 Cycles across the DOE for Cavity Temperature Switchover35

36. Main Effects on Impact Thickness Cavity Temperature Switchover
Best process robustness

37. Coefficient of Variation COV = σ / µ
Different switchovers are best for different attributes

38. Switchover Performance: Short vs. Long Run Variation
Short Run Variation (%)
More robust
Long Run Variation (%)

39. Switchover Performance: Long-Run Variation
Injection time
Runner pressure
Machine pressure
Screw position
Cavity pressure
Nozzle pressure
Cavity temperature

40. 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. 40

41. 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.

42. Acknowledgements
National Science Foundation grant number DMI /
Priamus System Technologies 42