1. University of Pennsylvania Automated Design and Prototyping of Macro and Micro Compliant Mechanisms Compliant mechanism concept leads to a clean separation of design/modeling from manufacturing/assembly activities. The objective of this research is to provide a link between the two through efficient data translations and automated reverse engineering techniques. Optimal topology design of compliant mechanisms Automatic image interpretation and creation of solid model from optimized topology image Reverse engineering for microfabricated artifacts Image processing for edge-extraction and object-finding Writing IGES file for Pro-Engineer Macro prototyping using Stratasys FDM 1650 rapid prototyping system Micro prototyping using MCNC’s Multi-User-MEMS-Processes (MUMPs) Automated metrology for a ceramic meso-scale machining Objectives

2. University of Pennsylvania Performance Specifications Synthesis Solution Refined Design Solution Meshed Model for Analysis Solid Model from the Optimized Device Digital Format for SFF or CNC Mask Layout for Microfab. Micro Prototype Macro Prototype Refined Prototype CAD model from the macro prototype Design and Prototyping of Macro & Micro Compliant Mechanisms Fabrication/Prototyping Digital Interface Design Reverse Engineering Solid model from microscopic images

3. University of Pennsylvania Arc and line extraction Model creation Manufacturing Algorithm for model extraction We utilize a six step method for creating a solid model from either a photo or a synthesized optimal design. Image filtering Edge detection Object characterization We rely on two primary assumptions: the images of interest have high contrast the images are not cluttered with extraneous visual data Each step utilizes simple image processing techniques.

4. University of Pennsylvania 1. Image Filtering and Thresholding The synthesized designs are generally coarsely pixelated. We use a blurring operation to smooth the image A simple contrast threshold is then used to separate areas with material from ones without 2. Edge Detection We use a simple binary filter to extract edges from the image Each edge is guaranteed to be only a single pixel wide 3. Object Extraction Assume that all objects have closed loop boundaries Scan the image to find a boundary, and then follow that boundary to identify an object The connectivity of each object is stored for further processing

5. University of Pennsylvania 4. Arc and Line Extraction Each object is analyzed to generate a model based on best fit arcs and lines Algorithms inspect groups of adjacent points to see if arcs or lines can approximate points to within a given tolerance 5. Model Creation Each object is resolved into a connected set of lines and arcs and written to an IGES file The IGES file can be read by a variety of programs for FEA/FEM, solid modeling, etc. We import into Pro/Engineer and generate a 3- D model by extrusion 6. Manufacturing A macro prototype is then generated from the solid model Using a Fused Deposition Modeling (FDM) machine, a plastic prototype can be generated (it is slightly brittle) Using a CNC machining center, more robust prototypes can be machined out of polystyrene or aluminum

6. University of Pennsylvania