A Formal Methodology for
Smart Assembly Design
A Presentation by
Kris Downey – Graduate Student
Alan Parkinson – Faculty Member
15 June 2000
Acknowledgements to NSF Grant 0084880
Presentation Outline
Introduction
 Research Objectives
 Current design techniques and analysis
methods
 Case study
 Current status of research
 Conclusions

Robust Design

Design that works properly when
subjected to variation

Current robust design methods
Focus on key characteristics
 FMEA
 DOE by Taguchi
 Six sigma analysis
 Optimization techniques

Smart Assembly

A smart assembly has features, not
otherwise required by the function of the
design, which allow the design to absorb or
cancel out the effects of variation
[Parkinson, 2000]
Smart Assembly

Examples of smart assembly features
Slotted holes
 Springs used for positioning
 Screw locators
 Sliding locators
 Shims

Smart Assembly

Types of smart assemblies
Shim
Passive
Screw
Inclined Plane
Smart Assembly

Types of smart assemblies
Passive
Can Opener
Support
Smart Assembly

Types of smart assemblies
Passive
Car frame
Smart Assembly

Types of smart assemblies
Active
Scissors Gear
Smart Assembly

Types of smart assemblies
Active
Garage Door
Roller Bearing
Research Objectives

Create a smart feature implementation
methodology
Principles developed for methodology
 Proven analysis methods implemented into
methodology


Apply methodology to case studies
Current Design Techniques
and Analysis Methods

Exact constraint design


Screw theory


Very close relationship to smart
assembly design
Constraint information inferred from
analysis
Tolerance analysis

Critical dimension information provided
Exact Constraint Design

Degrees of freedom
3 in 2D space
6 in 3D space
Exact Constraint Design

Constraint

A mechanical connection between objects that
reduces the degrees of freedom of each object
2D constraints
3D constraints
Exact Constraint Design

Exactly one constraint for each degree
of freedom

Rules for exact constraint design:
2D space




No two constraints collinear
No four constraints in a single plane
No three constraints parallel
No three constraints intersect at a point

3D space



No four constraints are parallel
No four constraints intersect at a point
No four constraints in the same plane
More mathematically-based theory is
needed in this area
Taken from [Blanding, 1999] and [Skakoon, 2000]
Exact Constraint Design

Exactly one constraint for each degree
of freedom
Underconstrained
Exactly constrained
Overconstrained
Exact Constraint Design

Conclusions:
Exact constraint design very closely related to
smart assembly
 Smart assembly provides solution to
overconstrained designs

Screw Theory
Allows determination of over- or
underconstrained designs
 Motion analysis
 Performed on individual part of assembly
 Assumes parts do not break contact
 Each joint type has distinct screwmatrices

Taken from [Ball, 1900], [Roth 1966], [Konkar, 1993], and [Adams, 1998]
Screw Theory

Steps to constraint analysis
Translate joints into twists
 Find reciprocal wrench of each twistmatrix
 Union of wrenches
 Find reciprocal twist of wrench
 Resultant twistmatrix

Screw Theory

Interpretation of resultant twistmatrix
and wrenchmatrix
Twist rows = degrees of freedom
 Wrench rows = overconstraints

Motions
Z-Rotation
Constraints
Y-Translation
Z-Translation
X-Rotation
Y-Rotation
Screw Theory

Conclusions:
Screw theory can determine if a design is
over- or underconstrained
 Location of idle degrees of freedom identified
 Information useful to smart assembly design

Tolerance Analysis
Vector loop analysis (DLM)
 Sensitivity matrix




Results provide useful
information regarding critical
part dimensions
80% of variation in angle f
is attributed to dimension a
Conclusion: Sensitivity matrix determines
preferred location of smart features
f
Case Study
Taken from Kodak design problem
Baffle design
 Overconstrained in z-direction

Taken from [Kriegel, 1994]
Case Study

Solution #1

Reinforce baffle
and frame
Taken from [Kriegel, 1994]

Results:
Less deflection
 Does not address
constraint problem
 Tabs tear from baffle

Case Study

Solution #2
Double screw
 Smart feature

Taken from [Kriegel, 1994]

Results:
Variation absorbed
 No deflection
 Expensive parts
 Increased assembly
costs

Case Study

Solution #3
Double-slotted tabs
 Smart feature

Taken from [Kriegel, 1994]

Results:
Variation absorbed
 No deflection
 “No cost” solution
 Minimal assembly
costs

Case Study

Conclusions:
Worst case tolerance analysis contributed to
need of smart features
 Overconstrained design was not initially
recognized
 Smart features allowed variation absorption
 Some smart features are more expensive than
others

Current Status of Research

Principles of smart assembly being
considered and explored
Implementation as nesting forces
 Absorption of tolerances
 Elimination of overconstraint
 Use in designs where redundant constraints
are necessary

Smart Assembly Principles

Smart assembly features as nesting forces

Eliminate mechanical play and assembly stresses
Rigid constraint
Smart feature
Smart Assembly Principles

Tolerance absorption

When other methods are not sufficient
Part A
Spring
Part B
Total gap
Part A
Part B
No gap
Smart Assembly Principles

Redundant constraints become smart features

Eliminate assembly stresses
Conclusions

Research Objectives:

Create a smart feature implementation
methodology



Principles inferred from existing designs:
 Smart features replace overconstraints
 Smart features absorb tolerances in exactly
constrained designs
 Smart features implemented as nesting forces
Proven analysis methods adapted for methodology
 Exact constraint design, screw theory and
tolerance analysis
Apply methodology to case studies

Indirect absorption of variation