1. No standard for OE packaging and assembly automation. Misalignment between optical and geometric axes Packaging is critical to success or failure of optical microsystems 60-80 % cost is in packaging Automation is the key to high volume, low cost, and high consistency manufacturing ensuring performance, reliability, and quality. Introduction Control: Model Based Theory Hardware implementation and verification - Kulicke and Soffa Industries Inc. Advanced curve-fitting Error prediction Learning Loop implementation Model based control leads to better system performance Efficient optical modeling using the angular spectrum technique Inverse model determined with PWL segments Conclusion and Future work T.P.Kurzweg, A. Guez, S. K. Bhat, “Model Based Opto-Electronic Packaging Automation,” to be published in IEEE Journal of Selected Topics in Quantum Electronics, 2004. T.P. Kurzweg, A. Guez, S. K. Bhat, “Knowledge Based Design of Optoelectronic Packaging and Assembly Automation,” Photonics East Conference, Providence, RI., October 29-31, 2003. Publications KpKp KpKp P d (s) P r (s) + + + - R(s) E(s) If = P, Desired Power Received Power Start Input Power Measurement & Loading Initial Throughput And Coarse Alignment Control And Optimization Bonding Post-Binding Testing Unloading End Step 1 Step 2 Step 3 Step 4 Step 5 Step 6 Adhesive Application ( Epoxy ) UV Curing Time Pulsed or Positive-Displacement Adhesive Dispenser Motion Controller Actuator that holds Receiving Device Photo Detector Optical Power Meter First Light Detection Camera With Microscopic Lenses Frame Grabber DAC LIMITATIONS: Multi-modal Functions Multi-Axes convergence Slow, expensive Visual Inspect and Manual Alignment Initialization Loop Move to set point (X o ) Measure Power (P o ) Stop motion Fix Alignment Approximate Set Point=X o Assembly Alignment Task Parameters Off the shelf Motion Control (PID) (Servo Loop) ADVANTAGES: Support for Multi-modal Functions Technique is fast Cost-efficient Visual Inspect and Manual Alignment Initialization Loop Move to set point (X o ) Measure Power (P o ) Stop motion Fix Alignment Set Point=X o Learning Algorithm Model Parameter Adjustment Optical Power Propagation Model Correction to Model Parameter {X k }, {P k } FEED - FORWARD Off the shelf Motion Control (PID) (Servo Loop) Assembly Alignment Task Parameters Manufacturing Process Current State-of –the-Art Model-Based Control  x U1( ,  ) U2(x,y) r z  y Diffractive component >>λ Distance to observation plane >>λ SCALAR DIFFRACTION-RAYLEIGH SOMMERFELD FORMULATION: Scalar Approximations Full Wave Solutions Rayleigh- Sommerfeld & Fresnel-Kirchoff Fresnel (Near Field) Fraunhofer (Far field) 850nm966um4.66mm Most transfer functions are non-invertible Power distribution is non- monotonic Decompose complex waveform into Piece-Wise Linear (PWL) Segments Each segment valid in specified region Find an inverse model for each segment Optical Modeling Inverse Model For model based control, we need an accurate inverse model Microsystems VALIDITY OF SCALAR MODELS 50  m 200  m Fourier DomainSpatial Domain