Transparent Electrostatic Clamp For Visual Assembly and Packaging

This paper describes the development of a miniature assembly cell for micro-electromechanical systems (MEMS). Potential applications of the developed assembly cell are assembly of miniature optical systems, integration of optoelectronics, such as laser diodes with CMOS, and epitaxial lift-off (ELO) of thin films used in optoelectronic devices. The cell utilizes a transparent electrostatic gripper and uses several disparate sensing modalities for position control: computer vision for part alignment with respect to the gripper, a fiber-coupled laser, and a position sensitive detector (PSD) for part to assembly alignment. Assembly experiments indicate that the gripping force and stage positioning accuracy are sufficient for insertion of 500μm wide parts in 550 μm wide slots etched in silicon wafers. Details on the cell operation, the control algorithm used and their limitations are also provided. INTRODUCTION Although MEMS devices are usually fabricated via massively parallel photolithographic techniques, in some instances, sequential assembly is required. For example, heterogeneous integration for vertical cavity surface emitting lasers (VCSEL-s) with silicon-based CMOS circuitry requires placement of the laser die onto a silicon substrate containing the electronic circuitry. Further applications include the assembly of dense arrays of high aspect-ratio structures such as electrode arrays in IC probe cards. These assembly and packaging operations are costly and usually constitute the largest portion of the device’s total cost. In order to increase the manufacturing throughput and reduce the re-tooling costs, it is desirable to develop flexible assembly schemes, allowing for quick adaptation to various part geometries and configurations. Responding to this need, a considerable effort from the private sector and government investments led the development of visually servoed robotic systems, which utilized computer vision to generate knowledge about the position of objects in the robot’s work space [1-3]. Research focused on microassembly with visual servoing [4,5] has developed excellent image processing techniques for robot control in real time [6]. Two-dimensional limitations of the imaging systems has also been addressed with research on the extraction of three-dimensional position information using techniques known as “depth-from-focus” or multiple CCD arrays [2,7]. In parallel with the software improvement several research groups have also developed micro-grippers actuated with electrostatic comb drives, thermal actuators or piezo-actuators for use under computer vision controlled robotic systems. In most cases these grippers are application specific, and thus require retooling when parts with variable geometry are used. Further, the gripping force is applied point or edge wise, increasing the possibility of local surface damage due to stress concentrations. The present work describes our effort to implement a micro-assembly cell based on a previously developed optically transparent electrostatic micro-gripper for visual servoing. When compared to other approaches such as vacuum gripping [8], this technique has the advantages of applying a uniform and controllable clamping force, uses a transparent gripper, which allows complete observation of the part and can accommodate parts with different planar geometry. Thus pick and place of Vertical Cavity Surface Emitting Lasers (VCSELS) [9], lift-off of thin fragile films are a few of the potentially relevant applications of this assembly technique. II. SYSTEM LAYOUT AND OPERATION The layout of the system is graphically represented in Figure 1below. The system is controlled by personal computer equipped with frame-grabber board (Sensoray Inc., USA) and motion control board (PCI-7344 Controller, National Instruments Inc., USA). CCD camera provides the signal for the frame-grabber (L-902K Watec Inc. USA). A servo-amplifier (MC-4SA, National Aperture Inc. USA) transfers the signal from the PCI-7344 to two motorized linear stages (MM4-MX, National Aperture Inc. USA). One of the stages is attached to platform, designed to support the electrostatic gripper. A PSD (S5990-01, Hamamatsu Inc, Japan) and a 653 nm laser (FIB-635-1SM LaserMax, Inc) are attached to the gripper platform. The laser is coupled to a GRIN collimated lens. The gripper platform is attached to one of the linear stages. A xyz translational stage (Newport, Inc, USA) supports a gimbal mirror mount (Edmund Industrial Optics, USA). The mount is situated in front of the platform and supports a slotted Si wafer. The laser beam reaches the surface of the wafer at an angle. The reflected beam is directed to the 1 Author to whom the correspondence should be addressed ([email protected]) PSD by using optical prism. Motions of the platform in the direction of the stage carry out linear scans over the surface of the wafer. Figure 1. Block diagram of the assembly cell. The gripper consists of a glass substrate with transparent thin-film electrodes on top. The electrodes are coated with an insulator [10]. The optical transparency of the gripper makes possible the use of real-time visual servoing to align the part with respect to the gripper using the CCD camera. To achieve this the pattern of the gripper itself is used. Figures 2 (a) and (b) show the gripper and gripper/part assembly respectively. Figure 2. (a) Figure 2. (b) (a) Gripper Electrodes. (b) A part clamped to the gripper. Both the ITO electrodes and the part are clearly seen. Figure 3. Stage with gripper platform mounted. Figure 3 shows the laser, the collimator, the PSD and the gripper integrated into a “gripper platform”. Fine adjustment of the collimator’s optical axis was achieved by two compressed o-rings threaded over the collimator housing. First alignment of a part with respect to the gripper is performed, through the use of an image-based visual servoing. After pick-up of a part, the surface of the receptacle wafer is scanned for a slot. Upon alignment part insertion is fulfilled via the manual x-y-z stage. Image-based visual servoing is implemented by employing the Sum of Square Differences (SSD) search algorithm [11]. Two SSD algorithms are used: spiral SSD algorithm and sequential SSD algorithm. The spiral search starts from the last known feature position and probes for a match in a spiral manner. The sequential search performs consecutive line scanning. Spiral mode is used for detection of parts with known initial location. Sequential mode is used when no estimate for the initial location of the tracked feature is available. Figure 4 shows a screen capture of the software interface developed for visual servoing. In this particular example three features marked with rectangles are selected for tracking. Two features (chess pattern) belong to the gripper and one feature (edge of the part) is selected for centering between the other two. Feature 1 x x Part to be picked up Feature 2 Figure 4. Screen capture of part/gripper alignment. Optical servoing aligns the part with respect to a slot on the wafer. Successful alignment is indicated by a minimum in the total reflected light intensity measured by the PSD detector. Real-time alignment is achieved through an intensity minimizing procedure, which utilizes measurements from the PSD sensors and from the magnetic encoder of the linear stage servomotor. Encoder information is also used for feed-forward position control of the linear stage. Two control algorithms for intensity minimization were tested spatial derivative method and hill-climbing algorithm. The first one is based on a real-time spatial derivative estimation of the PSD signal. The second one is based on intensity minimum search with a predefined step size. II. SYSTEM IDENTIFICATION A simplified block-diagram of the main components is shown in Figure 5 using first-order holder equivalents of the continuous signals with sampling time ms Ts 5 . 2 = . 2.1 LINEAR STAGE AND ENCODER The linear stage/motor is modeled as a second order system containing a single time-constant due to the inertial load of the system ( ) ( ) s s a s V s X τ + = 1 ) ( 0 , (1) ) (s V and ) (s X are the Laplace transform of the motor input voltage and the linear position of the stage respectively. 138 . 0 0 Vms m a μ = and ms 6 . 13 = τ were determined experimentally by applying a step voltage to the motor and recording the velocity output ) (t x& . The servo amplifier gain is 25 . 1 = G . Lag in the feedback path of the system is caused by the processing time required for analog to digital and digital to analog signal conversion, performing floating point calculations and feature tracking. Among these, the latter is most significant and ranges between 36 ms and 111ms for a 64 × 64 pixels feature in a 128 × 128 pixels search window. The time delay during optical feedback (PSD) with 5 point sliding differentiation rule (see section 3.2) was significantly shorter ms T 5 . 2 = . Figure 5 depicts the system using first-order holder equivalents of the continuous signals with sampling time ms T 5 . 2 = . Figure 5. Block diagram of the SIMULINK model. 2.2 Reflected Intensity Distribution Mathematical model has been developed to describe the intensity of the reflected laser beam as a function of the position of the slot in the receptacle wafer. The intensity of the laser is modeled using the Gaussian distribution. It is assumed to be symmetric: 2 0 2 0 2 0 ) ( ) ( 2 max ) , ( w y y x x e I y x I − + − − = (2) 0 w is the beam waist, 0 x and 0 y are the coordinates of the center of the beam. To model the power acquired by the reflected intensity ) , ( y x I ref , the ) , ( y x I distribution was convoluted with a characteristic function of the slot     + − ∈ + − ∈ = otherwise , 1 ] 2 , 2 [ and ] 2 , 2 [ x , 0 ) , ( h y h y y w x w x y x H H H H H , (3) H x and H y are the coordinates of the centroid and w , h are the width and the height of the slot. The power of the signal is acquired after integrating the intensity over an infinite area