U. of Pennsylvania, Jan. 2000 University of Pennsylvania, Philadelphia Project goal Methodologies and tools for interface between design and manufacturing

U. of Pennsylvania, Jan. 2000

University of Pennsylvania, Philadelphia

Project goal

Methodologies and tools for interface between design and manufacturing for Micro-Electro-Mechanical Systems (MEMS)

NSF Grant CISE #9617997



Optimal topology design of compliant mechanisms Automatic image interpretation and creation of solid

model from optimized topology image Image capturing of fabricated devices Image processing for edge-extraction and object-

finding Writing image data as an IGES file for Pro-Engineer Vision-based metrology for meso-scale ceramic

devices

Past accomplishments



PerformanceSpecifications

SynthesisSolution

Refined DesignSolution

Meshed Modelfor Analysis

Solid Model fromthe OptimizedDevice

Digital Formatfor SFF or CNC

Mask Layoutfor Microfab.

MicroPrototype

MacroPrototype

RefinedPrototype

CAD model fromthe macro prototype

Fabrication/Prototyping

Digital Interface

Design

Reverse Engineering

Solid model frommicroscopic images



From optimized compliant topology image to a solid model

IGES model with line and arc segments

Optimized compliant topology using material density design parameterization

Image processing, edge extraction, and object finding



Image from the optical microscope After edge extraction

The lack of sharp edges corresponding to the actual structure poses a challenge in extracting the correct topology.

Edge extraction from 2-D images



From fabricated MEMS device to a solid modelOptical microscope image of a compliant micro crimper After edge extraction

5 µm



From fabricated MEMS device to a solid model

IGES model exported into Pro-E with line and arc segments

Extruded solid model ready for behavioral simulation



Macro prototype of a micro wedge motor

(Allen, 1998)The micro prototype was made using Sandia’s SUMMiT process.



Lithography masks for a micro wedge motor



Premise:Assuming material behavior and properties, forces can be estimated from underformed and deformed geometry of a flexible structure.

Vision-based force sensing

Goal:Non-contacting, non-interfering force sensor based on vision and computation.



Image capturing beforeand after deformation

Displacements

Strains

Stresses

Forces

Materialproperties



Inverse elastic analysis problem.

Linear (small deformations) problem is trivial.

Large deformation, small/large strain problem is of interest here.

yKf Stiffness matrix

Forces Displacement

Assumption: Correspondence between undeformed and deformed geometries is known.



y

z

At time t = 0(Undeformed)

At time t(Deformed)o

1 2

34

1 2

34

x

Computing the deformation gradient

y

y

x

yy

x

x

x

X tt

tt

00

00

Deformation gradient



Computing the large strain

)ln(VLogarithmic strain

21

CV

TXXC *



Computing the stress and element forces

Material properties for plane-stress condition

2

100

01

01

1 2

E

M

*M

eV

Te dVBF

qB

Stress

Element forces



Force recovery

Large strain case Small strain case



Macro-scale experiment



Corner detection



Comparison of computed and measured displacements



Recovered forces (experimental displacements)



Recovered forces (numerical displacements)



The procedure for computing strains from displacements is prone to numerical error.

The computed strain is very sensitive to even small perturbations in displacement data.

The sensitivity is worse for small strains than large strains.



Sensitivity analysis



Sensitivity analysis

Documents

U. of Pennsylvania, Jan. 2000 University of Pennsylvania, Philadelphia Project goal Methodologies and tools for interface between design and manufacturing