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Advances in Molding Technology

Advances in Molding Technology. David Kazmer University of Massachusetts Lowell. Introduction. Who Is David Kazmer?. 1985 1990 1995 2000 2005. Opening Remarks. Product designs remain inefficient Minority of applications leverage simulation Wasting material, cycle time, added value…

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Advances in Molding Technology

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  1. Advances in Molding Technology David Kazmer University of Massachusetts Lowell

  2. Introduction

  3. Who Is David Kazmer? 1985 1990 1995 2000 2005

  4. Opening Remarks • Product designs remain inefficient • Minority of applications leverage simulation • Wasting material, cycle time, added value… • Processes are thought of as “proscribed” • Significant opportunities exist • Better observability through sensor fusion • Multiple sensors with real-time analysis • Better controllability through process design • Control of initial & boundary conditions

  5. Vision: Gate-Level Control ofFlow Rates & Cavity Pressures • “Decoupled Molding” • Decouple the mold from the molding machine • Decouple the gates from each other • Decouple filling from the packing at each gate • Requires two major advances: • Real-time process simulation • Improved melt valves

  6. Real Time Process Simulation

  7. 1-D Flow In A Tube • Hagen-Poiseuille Flow • Viscous, laminar flow (constant viscosity) • Relates flow rate, pressure, and viscosity • Flow conductance, k, defined as:

  8. Flow Network Analysis • Consider a two-branched hot runner system • Geometry & flow conductance known • Develop flow conductance matrix

  9. Flow Network Analysis • Apply boundary conditions: • P1, P5, & P6 observed • Q2, Q3, & Q4 equal 0 • Solve on-line in real-time

  10. Notes • Previous approach is relatively easy • Hot runner geometry known • Constant viscosity assumed • “Newtonian” • Flow conductance matrix pre-computed and remains constant • Able to invert matrix in microseconds • Definitely feasible for 64+ cavities Not so accurate: ignores shear heating and shear thinning

  11. Rheological Modeling • Newtonian • Ellis Model • WLF Model

  12. Three levels of flow analysis • Newtonian: previously described • Fast but least accurate • Modified Ellis model • Analytical solutions for temperature & flow • Very fast solution • Full mold filling simulation • Simultaneous solution of differential eq’s • Iterative solution required • CPU intensive

  13. Ellis Solution:Temperature Field • Balance shear heating, heat conduction, and heat convection

  14. Ellis Solution:Flow Field • Temperature estimated at each portion of the hot runner • Viscosity computed in each flow segment • Conductance matrix formed at each time step • Flow conductance matrix established with analytical relation (rod)

  15. Mold Filling Analysis • Heat, mass, and momentum equations • Full spatial discretization • Iterative solution of equations Most accurate but CPU intensive.

  16. Approximate Execution Speed • Newtonian flow analysis • ~20,000 times/sec (2 cavities) • Feasible for 64 cavities + • Ellis model flow analysis • ~5,000 times/sec (2 cavities) • Feasible for up to 64 cavities • Mold filling simulation • ~1,000 times/sec (2 cavities) • Feasible for up to 8 cavities, possibly more

  17. System Development • Instrumented Mold • Valve gated hot runner • Cavity pressure transducers • Control system • Signal conditioners • Data acquisition • Real time flow analysis • User interface

  18. Simulation Outputs • Continuous feedback of • Cavity pressures • Flow rates • Prior to mold opening • Part weight / short / flash conditions • Part shrinkage • Melt viscosity estimates • Other quality attributes

  19. Demonstration

  20. Experimental Validation:Newtonian Analysis • Process changes definitely observed • Temperature effect is confounding • Newtonian model likely not enough       

  21. Current Status • Validation still on-going • Rheology & melt temperature are critical • ~15% mean error • ~70% accuracy on main effects • On-line calibration being developed • Small DOE to verify accuracy • Automatic correction for mass conservation or viscosity shifts • Very promising approach, though in infancy

  22. Inj Fwd Inj Fwd Data Ram position & hyd pressure P1 & P2 Display Info Process Settings C1 & C2 V1 & V2 U1 & U2 Objective:Real Time Control • Control of pressure and flow rate at each gate in real time • New valve designs desired Inj FwdConditioner Molding Machine DAQ Computer ChargeAmplifiers Mold Operator Valve Control Relays

  23. New Valve Designs

  24. Fcontrol Fpressure Vision: Self-Regulating Pressure Valve • Ideally two forces: • Top: control force • Bottom: pressure force • Forces must balance • Pin moves to equilibriumposition • Pressure drop governedby juncture loss

  25. Fcontrol Pout Pin time time time Animation • Outlet pressure proportional to control force • Pin position determined by inlet pressure and related pressure drop

  26. Newtonian Analysis:Sizing & Pressure Drops • All dimensions normalizedto inlet radius, R • aR: outer diameter • bR: inner diameter • cR: extension diameter • dR: annulus length • eR: valve pin position

  27. Analysis of Pressure & Shear Stress Loads • Load due to pressure drop across valve • Load due to shear stresses on valve • Juncture loss (empirical estimate)

  28. Valve can be sizedfor mass rate and DP Large annulus desired for good control Analysis Results StrengthLimit ControlLimit

  29. Advanced Analysis • Axisymmetric 2D numerical simulation developed including acceleration effects

  30. General Results • Confirms feasibility of low force valve • Balance of control & pressure forces • Primary results • Pressure drops • Shear rates • Bulk temperatures • Q=f(DP) • Guidance for design

  31. Outlet Melt Pressure as a Function of Control Force Confirms closed loop meltpressure control withoutpressure feedback.

  32. Dynamic Response & Positionas a Function of Control Force Pin hovers near a closed position. Dynamics driven by resultant force.

  33. Outlet Bulk Temperature as a Function of Control Force Indicates limitson shear heating (sizing guidance)

  34. Melt pressure is proportional to pneumatic pressure Design and Implementation • Valve designed and built • Inlet diameter of 8 mm • In-line configuration • Pressure transducers • At inlet • Below valve pin • Control force provided bya pneumatic cylinder with varying pressure

  35. Transient Validation • Predicted response is fast & steady • Observed response is slower & oscillatory

  36. Hot Runner Implementation • Retrofit to valve-gated hot runner • Side entry toannular channel • Valve pin • 5 mm Diameter • Shear rates~10,000 1/sec

  37. Hot Runner Implementation

  38. Resulting Capability • Cavity pressure control without pressure transducers! • If cavity pressure transducers are used, then process simulation can provide flow rates and other quality estimates • Can measure load on extended valve pin to completely eliminate pressure transducers

  39. Conclusion

  40. Closing Statements • Vision is solid • Difficult work is done • Capability must be validated • This is “where rubber hits the road” • What is the best we can do? • Validation & specification nearly done • Commercial feasibility studies in 2005

  41. Two More Quick Projects Wireless Pressure Sensor The Alpha-Sigma Project

  42. Ceramic Insulator Preload Inner Screw Thermocouple Piezoelectric Rings Outer Electrodes Thermocouple Ceramic Insul a tor Therm ocouple Signal Leads Lead Wireless Pressure Sensor • Wireless pressure sensor • Piezoelectric energy cell • Threshold modulator • Acoustic transmitter • Next generation sensor • w=f(T) • Multiple sensor arrays • Pressure, temperature, flow rate in real time! • ~5-10 years out

  43. Alpha Sigma Pi: Confidence, Robustness, Performance • Given specifications & • Non-linear models • a confidence levels • s robustness requirements • Provides: • Process windows • Pareto optimal charts • SPC & SQC graphs • Taguchi/Axiomatic methods

  44. Graduate Students You are important! I want you to succeed!!

  45. Guidelines • How to address me? • Speaking to me: Dave • Speaking to other faculty: Prof. Kazmer • Speaking to other students: • Kazmer • #^&@@#^%

  46. Guidelines • How to work with me: • Respect and protect my time • Do high quality work • Have others check your work, especially thesis • Be proactive • You’re empowered: assume authority • Execute to plan • Commit and deliver

  47. Current Research FundingBy Sponsor ($ remaining of total) • Mold-Masters ($40k of 80k+ in-kind) • NSF Melt Valves ($120k of $210k) • NSF Sensing ($230k of $900k) • Available money: ~400k of $1200k • ~12 student-years + expenses • Enough for all your MS + 2 DEngs • No salary for Kazmer

  48. Current Research FundingBy Topic ($ remaining of total) • Advanced melt flow control ($80k of $150k) • On-line simulation ($120k of 150k) • Wireless pressure & temperature sensors ($110k of 420k)

  49. Melt flow control Vijay: Characterization Rahul: Hydrodynamics Other: Analysis On-line simulation Ranjan: Validation Hitesh: Quality Other: Extension Wireless sensing Other: Design Other: Testing Unassigned Peter Knepper Steven Johnston Kathy Garnivish OK to split topics Research Topics by Student

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