Upload
clare-kelly
View
214
Download
0
Embed Size (px)
Citation preview
1
An Information-Driven FEA Model Generation Approach
for Chip Package ApplicationsSai Zeng1, Russell Peak2*, Ryuichi Matsuki3,
Angran Xiao4, Miyako Wilson2, Robert E. Fulton1
1 Engineering Information Systems Lab2 Manufacturing Research Center
4 Systems Realization Lab
Georgia Institute of Technology, Atlanta, GA 30332-0405, USA
3 Advanced Product Design & Development Division,
Shinko Electric Industries Co., Ltd., Nagano, Japan
23rd Computers and Information in Engineering Conference
September 2–6, 2003, Chicago, Illinois
2
Example Chip Package Products Source: www.shinko.co.jp
Plastic Ball Grid Array (PBGA) Packages Quad Flat Packs (QFPs)
Wafer Level Package (WLP) System-in-Package (SIP)Glass-to-Metal Seals
3
12
3
12
3
12
4
1a
2
3a
1b
1c
3b 3c
3a 3b
2
1a 1b 1c
1d 1e
3
1a 1b
1c1d
23
4a 4b 4c
Idealized Analytical Bodies Decomposed FEA Geometry Models
original
topology change (no body change)
body change (includes topology change)
Variable Topology Multi-Body (VTMB) FEA Meshing Challenges
Labor-intensive “chopping”
Meshing & SolvingDesign
Model
4
Traditional Approach
Analysis Concepts Geometry Preparation for Mesh Generation
FEA Model Planning Sketches in Traditional Approach
Small topology changes force mesh model rebuilding from scratch
Mesh models are barely reusable using traditional approach
5
Motivation
Competition in Chip Package Industry Needs for new technologies and approaches facilitating seamless
design and analysis integration Difficulty in analysis model generation
– Hundreds of components– Variable materials– Complex geometric shapes– Changeable connectivity configurations
Modifications resulting in tedious and time consuming FEA modeling process
– package design– analysis discipline– idealization
6
Objective
Integrate chip package design using Finite Element Analysis
Automate the FEA modeling process to save the modeling time and reduce the human errors
Increase reusability of the mesh models during chip package modification and redesign
7
Frame of Reference – Multi-Representation Architecture (MRA)for CAD-CAE Interoperability
Composed of four representations (information models) Provides flexible, modular mapping between design & analysis
models Creates automated, product-specific analysis modules (CBAMs) Represents design-analysis associativity explicitly
1 Solution Method Model
ABB SMM
2 Analysis Building Block
4 Context-Based Analysis Model3
SMMABB
APM ABB
CBAM
APM
Design Tools Solution Tools
Printed Wiring Assembly (PWA)
Solder Joint
Component
PWB
body3body2
body1
body4
T0
Printed Wiring Board (PWB)
SolderJoint
Component
AnalyzableProduct Model
8
Information-Driven FEA Modeling Approach
Mapping process ABBΨRMM transforms the ABB model into a ready-to-mesh model (RMM) by geometry decomposition.
Mapping process RMMΨSMM transforms the RMM into the solvable FEA-based SMM in an automated manner.
ABB captures analytical concepts FEA based SMM = object wrapper
– Integrates pre-processor, solver and post processor information– Includes vendor-specific script file format
body3body
2
body1
body4
T0
body3body
2
body1
body4
T0
ABB Model RMM Model SMM Model
ABBΨRMM RMMΨSMM
Information-Driven FEA Modeling Approach
9
Analysis Building Block Models (ABBs)
An ABB model represents engineering analytical concepts as a set of computable information entities
Independent from specific solution techniques Analysis knowledge is captured by employing object-orient information representation
technology
a. Composition Hierarchy for ABB Continuum Systems
Continuum System
Load Structure
Continuum Connectivity Support
Shape Materials
Continuum System
Load Structure
Continuum Connectivity Support
Shape Materials
b. ABBs Catetorized by Type [1,2]
Analysis Primitives - Primitive building blocks-
Loading Variablesq(x)
Distributed Load
Temperature,Stress,Strain,
T
Loading Variablesq(x)
Distributed Load
Temperature,Stress,Strain,
Tq(x)
Distributed Load
Temperature,Stress,Strain,
T No-Slipbody 1
body 2
ConnectivityNo-Slip
body 1
body 2 No-Slipbody 1
body 2
body 1
body 2
Connectivity
Material Models
Linear-Elastic
BilinearPlastic
Low CycleFatigue
N
Material Models
Linear-Elastic
BilinearPlastic
Low CycleFatigue
N
Material Models
Linear-Elastic
BilinearPlastic
Low CycleFatigue
N
Linear-Elastic
BilinearPlastic
Low CycleFatigue
N
N
- Cantilever Beam SystemAnalysis Systems
x
y q(x)
Beam
Distributed Load
RigidSupport
- Cantilever Beam SystemAnalysis Systems
x
y q(x)
Beam
Distributed Load
RigidSupport x
y q(x)
Beam
Distributed Load
RigidSupport
RigidSupportRigidSupport
Support
ShapeShapeShapeContinua
Beam
Plane Strain Body Plate
Continua
Beam
Plane Strain Body Plate
Continua
Beam
Plane Strain Body Plate
body3body2
body1
body4
T0
body3body2
body1
body4
T0
ABB Model RMM Model SMM Model
ABBΨRMM RMMΨSMM
body3body2
body1
body4
T0
body3body2
body1
body4
T0
body3body2
body1
body4
T0
body3body2
body1
body4
T0
ABB Model RMM Model SMM Model
ABBΨRMM RMMΨSMM
Information Content for Example ABB Concepts
10
Analysis Building Block Models (ABBs)
A diving board example is presented to illustrate an ABB system
L1: Loading RelationC1: Connectivity RelationC2: Connectivity RelationS1: Support Relation
a. Diving Board Example
b. ABB Model Graphical View
L1L1
C1 C2
C1 C2
S1
Uniform pressure
Slip No-slip
Continuum A
Continuum B
Fully constraint
A Graphical View of an ABB System and its Analytical Bodies and Connectivity
body3body2
body1
body4
T0
body3body2
body1
body4
T0
ABB Model RMM Model SMM Model
ABBΨRMM RMMΨSMM
body3body2
body1
body4
T0
body3body2
body1
body4
T0
body3body2
body1
body4
T0
body3body2
body1
body4
T0
ABB Model RMM Model SMM Model
ABBΨRMM RMMΨSMM
11
Ready-to-Mesh Models (RMMs)
A RMM is obtained by geometric decomposition from a corresponding ABB
The geometry of a RMM model is composed of geometry pieces that are convex-shaped and meshable using efficient and cheap meshing techniques.
Building blocks of an ABB can be reused to construct a RMM Associativity of building blocks is changed before and after
decompositionL1L1 L1L1
C1C1 C1C1
C1C1C1C1
C2C2
C2C2S1S1
S1S1
S1S1
A Graphical View of an RMM System and its Decomposed Bodies and Connectivity
body3body2
body1
body4
T0
body3body2
body1
body4
T0
ABB Model RMM Model SMM Model
ABBΨRMM RMMΨSMM
body3body2
body1
body4
T0
body3body2
body1
body4
T0
body3body2
body1
body4
T0
body3body2
body1
body4
T0
ABB Model RMM Model SMM Model
ABBΨRMM RMMΨSMM
12
Decomposition Architecture
Decomposition is implemented to obtain conformal mesh along the interfaces of connected bodies
Decomposition deals with geometry exclusively
Decomposed model consists of decomposed bodies connected along equivalent faces
Topology and GeometryFeature Recognition
Seperator Setup
Decomposition
Meshable?
RMM Geometry
ABB Geometry
Y
N
Decomposition Process
body3body2
body1
body4
T0
body3body2
body1
body4
T0
ABB Model RMM Model SMM Model
ABBΨRMM RMMΨSMM
body3body2
body1
body4
T0
body3body2
body1
body4
T0
body3body2
body1
body4
T0
body3body2
body1
body4
T0
ABB Model RMM Model SMM Model
ABBΨRMM RMMΨSMM
13
Decomposition Associativity Mechanism
An mechanism is required to keep track of the information associativity during the geometry decomposition
Continuum A
Uniform pressure
Compositional Relations for Boundary Condition Building Blocks and Continuum Building Blocks after Decomposition
body3body2
body1
body4
T0
body3body2
body1
body4
T0
ABB Model RMM Model SMM Model
ABBΨRMM RMMΨSMM
body3body2
body1
body4
T0
body3body2
body1
body4
T0
body3body2
body1
body4
T0
body3body2
body1
body4
T0
ABB Model RMM Model SMM Model
ABBΨRMM RMMΨSMM
14
Solution Method Model (SMM)
It is an information entity that wraps solution tool inputs and outputs into a single logical package
SMM includes the SMM information objects and the SMM tool agent
1 Solution Method Model Solution Tools
preprocessormodel
meshmodel
resultsextrema
u
A
3
11 10
98
4 3
2
7
56
1
A
A2
1
CL Files
Operating SystemObject Environment
ToolAgent
inputs &control
outputs
FEA Tools
body3body2
body1
body4
T0
body3body2
body1
body4
T0
ABB Model RMM Model SMM Model
ABBΨRMM RMMΨSMM
body3body2
body1
body4
T0
body3body2
body1
body4
T0
body3body2
body1
body4
T0
body3body2
body1
body4
T0
ABB Model RMM Model SMM Model
ABBΨRMM RMMΨSMM
15
ABB - SMM- Solution Tool Interaction
ABB systems generate SMMs based on solution method considerations
– Via RMMs in these problem types
Solution tool capabilities are also usually considered
1 Solution Method Model
2 Analysis Building Block Solution Tool
inputs &control
outputs
A1
3
2
A
A
11 10
98
4 3
2
7
56
1
A1
3
2
A
A
11 10
98
4 3
2
7
56
1
preprocessormodel
meshmodel
4body
ABB SMM
resultsextrema
u
1body
3body
2body
ABBSMM
RMM Model
16
A Chip Package Thermomechanical Analysis Case – An ABB system
Four linear elastic thermomechanical continua Continua are glued together One rigid pin support Uniform temperature drop as thermal load
DieDie Attach
Mold
Die Pad
Front View
Right View
Time
TemperatureDifference
Load
a. ABB System - Original Bodies with 1/4 Symmetry
Support
Continuum BodiesNo Slip
17
A Chip Package Thermomechanical Analysis Case – An RMM
Front View
Right View
b. RMM System - Decomposed Bodies
A RMM is obtained after automatic decomposition of a ABB system With composition mechanism, information associated with geometry
can be assigned on the corresponding decomposed geometry This model can be directly input into the SMM to generate a conformal
FEA meshed model
18
A Chip Package Thermomechanical Analysis Case – An SMM
c. FEA SMM - Tool-specific Model
The tool agent translates the model information into the tool-specific computable formats, e.g. a PATRAN command language ASCII file
Modeling time is counted as information instance object creation time
Modeling time is dramatically reduced comparing to traditional FEA modeling approach
19
Complex Chip Package Thermomechanical Analysis Case
ABB Model consisting 182 Input bodies RMM consisting 9056 Decomposed bodies
FEA SMM
Decomposition
20
Closure
Presentation of information-driven FEA modeling approach
Demonstration representing product-independent analysis concepts as knowledge-based objects:
– semantically rich– reusable– modular and tool-independent
Reduction of FEA modeling time (variable topology multi-body application) - reduced from days/hours to hours/minutes
Enhancement of knowledge capture and automation level vs. traditional direct FEA modeling approaches
21
Acknowledgements
We are particularly grateful for the support of the following
people: – Kuniyuki Tanaka, Yukiharu Takeuchi, and Shinichi
Wakabayashi of Shinko Electric Ltd. – Greg Bettencourt of Shinko Electric America, Inc.– Rod Dreisbach of The Boeing Company– Mike Dickerson of the NASA Jet Propulsion Lab (JPL)– Manas Bajaj, Greg M. Mocko, Edward J. Kim, Injoong Kim at
the Engineering Information Systems Lab, Georgia Tech