1. Towards Controllability in Polymer Processing David Kazmer, PE, PhD Louisiana State University April 4 th, 2008

2. Introduction ● Flow Control ● Temperature Control ● Injection Compression ● Future Introduction Flow Control Temperature Control Injection Compression Future Work Agenda

3. 19891990199119921993199419951996199719981999200020012002200320042005 Applications Engineer Intern, GE Plastics Mechanical Engineer, GE R&D Applications Engineer, GE Plastics Development Engineer, GE Plastics Tech. Programs Manager, GE Plastics Group Leader, Moldflow IPC Advisor, Dynisco Instruments Director of R&D, Dynisco BS, Mechanical Engineering MS, Mechanical Engineering ‘Future Professor of Manufacturing’ Stanford University PhD, Mechanical Engineering Assistant Prof., UMass Amherst Associate Prof., UMass Amherst Associate Prof., UMass Lowell Professor, UMass Lowell Kazmer Bio Introduction ● Flow Control ● Temperature Control ● Injection Compression ● Future

4. Unresolved Control Issues Definition: A system is controllable if every output is connected to a control input. Definition: A system is observable if its modes can be deduced from sensed outputs. Polymer processing is neither! Process states & quality are largely unknown & uncontrolled… trade-offs must be made Introduction ● Flow Control ● Temperature Control ● Injection Compression ● Future

5. The Molding Process Introduction ● Flow Control ● Temperature Control ● Injection Compression ● Future

6. Machine states can be sensed and somewhat controlled However, there are few degrees of freedom Unable to change pressure & temperature distribution in cavity Common trade-off: Retool the mold or Accept sub-optimal part quality Flow Control Introduction ● Flow Control ● Temperature Control ● Injection Compression ● Future

7. Conventional Molding Design of Experiments All dimensions are coupled to machine changes No independent controllability RPM 0.60 0.40 0.20 0.00 -0.20 PresVelTemp Key: L3 L1 L2 Main Effects Plot (% in/in) Introduction ● Flow Control ● Temperature Control ● Injection Compression ● Future

8. What if mold behavior could be changed during the molding process? Dynamic Feed Introduction ● Flow Control ● Temperature Control ● Injection Compression ● Future

9. Dynamic Feed Introduction ● Flow Control ● Temperature Control ● Injection Compression ● Future

10. Dynamic Feed Results Reduced machine dependency Improved process flexibility & controllability RPM 0.60 0.40 0.20 0.00 -0.20 PresVelTemp Main Effects Plot (% in/in) P4 P1P2P3 L3 L1 L2 Introduction ● Flow Control ● Temperature Control ● Injection Compression ● Future

11. New Valve Design Self-regulating valve Two significant forces: Top: control force Bottom: pressure force Forces must balance Pin position governed by dynamic equilibrium Melt pressure is proportional to control force via intensification factor, I Introduction ● Flow Control ● Temperature Control ● Injection Compression ● Future

12. Flow/Control Analysis Introduction ● Flow Control ● Temperature Control ● Injection Compression ● Future Results indicate 2% open loop error typical

13. Valve Deployment Advantages Multi-axis melt control without cavity pressure transducers! Injection molding & extrusion Compact & low actuation forces All the consistency & flexibility of Dynamic Feed ½ the cost Lower complexity with pneumatic or electric actuators Disadvantages: patents Introduction ● Flow Control ● Temperature Control ● Injection Compression ● Future

14. Thermal Control Motivation: Control Eliminate solidified layer during mold filling Manufacture thinner & larger products Improve part properties (gloss, strength) Introduction ● Flow Control ● Temperature Control ● Injection Compression ● Future x P T 300 C 100 C Non-isothermal Isothermal

15. Approach #1: Pulsed Cooling Process Heat with oil Fill the mold Cool with water Comments Long cycle time Very high energy cost Lenses & cockpit canopies Introduction ● Flow Control ● Temperature Control ● Injection Compression ● Future

16. Approach #2: Managed Heat Transfer Process Polymer melt (red) heats mold shell (pink) Insulator (blue) slows heat transfer Comments Energy efficient Limited control CDs & DVDs Introduction ● Flow Control ● Temperature Control ● Injection Compression ● Future

17. Approach #3: MHT with Gas Pre-Heat Process Composite mold to reduce heat transfer Pre-heat surface with hot air Run coolant colder to compensate for cycle time Comments Validated at UMass Amherst Found minimal pressure & flow control benefits Introduction ● Flow Control ● Temperature Control ● Injection Compression ● Future

18. Approach #4: Thin Film Resistive Heaters Process: Insulator and thin film heater deposited on mold surface Mold layer temperature controlled Coolant run at lower temperature to reduce cycle time Introduction ● Flow Control ● Temperature Control ● Injection Compression ● Future

19. Thin Film Heaters Introduction ● Flow Control ● Temperature Control ● Injection Compression ● Future

20. Thin Film Heaters Introduction ● Flow Control ● Temperature Control ● Injection Compression ● Future

21. Thin Film Heaters Thin film heaters have very high power density Excellent dynamic and absolute response Heated Heater Voltage (V) Mold Surface Temperature (F) Introduction ● Flow Control ● Temperature Control ● Injection Compression ● Future

22. Thin Film Heaters Increasing the mold wall temperature: Reduces or eliminates the solidified layer Allows the plastic to travel further as measured by the flow length Introduction ● Flow Control ● Temperature Control ● Injection Compression ● Future

23. Thermal Control Even though thermal control was achieved, Long filling times were required for viscous flow of melt in cavity Excessive flashing occurs due to elimination of solidified layer These are BIG practical issues Introduction ● Flow Control ● Temperature Control ● Injection Compression ● Future MOLDED SAMPLES Thermal ControlConventional

24. Injection Compression How does this apply to micro/nano molding? What we’ve learned is that flow & thermal control is expensive & limited This motivates a new process design: Convey the bulk of the melt on the macro scale Solidified layer & pressures are not an issue Rely on heat of polymer & local heating control to form micro & nano features Gas entrapment & part ejection remain practical unresolved issues Introduction ● Flow Control ● Temperature Control ● Injection Compression ● Future

25. Injection Compression Process Partly open mold Inject polymer Profile clamp force to close mold Adjust Thickness Change Element Properties Restore Old Profiles Y Calculate Pressure Calculate Cavity Force Cavity Force=Clamp Force? Calculate Temperature Move on to Next Time Step N Force Introduction ● Flow Control ● Temperature Control ● Injection Compression ● Future

26. Optical Media Molding Injection-compression molding (coining) CDs & DVDs Introduction ● Flow Control ● Temperature Control ● Injection Compression ● Future

27. Birefringence Models Constitutive model for flow induced stress (Wagner, M. H. et al) Introduction ● Flow Control ● Temperature Control ● Injection Compression ● Future

28. Birefringence Models (Cont.) Path difference (retardation): Shear stress: First normal stress difference: Integral stress-optical rule (birefringence constitutive model): Introduction ● Flow Control ● Temperature Control ● Injection Compression ● Future

29. Numerical Algorithm Incremental formulation for the integral equations: Solved by FDM in time domain: Introduction ● Flow Control ● Temperature Control ● Injection Compression ● Future

30. Simulation of Internal Stress and Post-Molding Deformation Thermal stress/warpage In-mold: FDM (Baaijens, F. P. T. et al) – Out-of-mold: FEA (plate bending) Introduction ● Flow Control ● Temperature Control ● Injection Compression ● Future

31. Finite Element Discretization Kirchhoff thin-plate elements Introduction ● Flow Control ● Temperature Control ● Injection Compression ● Future

32. Finite Element Formulation Strain-displacement relationship Stress-strain relationship Element stiffness matrix and element right-hand-side vector Introduction ● Flow Control ● Temperature Control ● Injection Compression ● Future

33. In-plane Birefringence Validation Introduction ● Flow Control ● Temperature Control ● Injection Compression ● Future Simulation results are highly dependent on low temperature melt rheology

34. TgTg Melt Relaxation Modeling WLF model fit by data at 150-280 o C Truncated at at 140, 135, 130, 125 o C Introduction ● Flow Control ● Temperature Control ● Injection Compression ● Future

35. Injection Compression Provides higher data density & lower costs Optical media simulation used for Process development and optimization Development of new polymeric materials Introduction ● Flow Control ● Temperature Control ● Injection Compression ● Future

36. Current Work: Nano Self-Assembly Assist design & optimization of nano- production processes Nano features to self-assembly according to surface template Morphology development in composite polymeric systems is a function of: Contractive behavior of polymer(s) to minimize free energy density (phase separation) Expansive behavior of polymer(s) to diffuse into other material(s) Boundary conditions to locally drive morphology via surface functionalization of template Introduction ● Flow Control ● Temperature Control ● Injection Compression ● Future

37. Template Assisted Morphology Development Attraction to polymer A Attraction to polymer B Neutral to both A & B Attraction Factor:0.04 A/B:40/60  =1.6e-5 4096Steps: 4 32256

38. # Vars R 2 R 2 adj Mallows CP Fill Time Pack Time Recovery TimeCool TimeCycle TimeScrew Displacement Filling Screw Displacement PackingScrew Displacement Cooling Fill Speed Velocity at Transfer Packing VelocityVelocity during RecoveryMax Fill Pressure Avg InjPressure FillingHold Pressure Back Pressure Injection Energy Recovery EnergyMelt Visc during filling Melt Visc during packing Avg Nozzle Temperature Avg Metering Temperature Avg Feed Temperature Avg Coolant Temperature Cushion Shot Size 138.537.8151.5 137.036.3157.3 270.369.630.7 261.560.664.7 377.376.55.6 376.175.310.2 477.876.85.7 477.776.76.1 578.777.44.3 5 78.777.44.4 679.578.03.2 679.377.84.1 779.878.04.2 779.677.94.7 880.278.24.4 880.278.2 4.5 Current Work: Quality Control Statistical analysis indicates need for orthogonal process state information Introduction ● Flow Control ● Temperature Control ● Injection Compression ● Future

39. Current Work: Sensing Developing five way in-mold “smart” sensor Infrared melt temperature, Melt pressure, Melt velocity, Melt viscosity, Part shrinkage Each already validated independently… five years to realization Introduction ● Flow Control ● Temperature Control ● Injection Compression ● Future

40. Acknowledgements Multiple NSF & other grants LSU faculty: Sungook Park, Michael C. Murphy, Dimitris Nikitopoulos, Steve Soper, & others UMass PhD Students, especially Bingfeng Fan & Steve Johnston Introduction ● Flow Control ● Temperature Control ● Injection Compression ● Future