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

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 Screw Inclined Plane Passive

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 Very close relationship to smart assembly design Screw theory Constraint information inferred from analysis Tolerance analysis Critical dimension information provided

Exact Constraint Design Degrees of freedom 6 in 3D space3 in 2D space

Exact Constraint Design Constraint A mechanical connection between objects that reduces the degrees of freedom of each object 2D constraints3D constraints

Exact Constraint Design Exactly one constraint for each degree of freedom No two constraints collinear No four constraints in a single plane No three constraints parallel No three constraints intersect at a point No four constraints are parallel No four constraints intersect at a point No four constraints in the same plane Rules for exact constraint design: 2D space3D space 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 Exactly constrained Overconstrained Underconstrained

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 Constraints Y-Translation Z-Translation X-Rotation Y-Rotation Z-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  is attributed to dimension a Conclusion: Sensitivity matrix determines preferred location of smart features 

Case Study Baffle design Overconstrained in z-direction Taken from [Kriegel, 1994] Taken from Kodak design problem

Case Study Results: Less deflection Does not address constraint problem Tabs tear from baffle Taken from [Kriegel, 1994] Solution #1 Reinforce baffle and frame

Case Study Solution #2 Double screw Smart feature Results: Variation absorbed No deflection Expensive parts Increased assembly costs Taken from [Kriegel, 1994]

Case Study Solution #3 Double-slotted tabs Smart feature Results: Variation absorbed No deflection “No cost” solution Minimal assembly costs Taken from [Kriegel, 1994]

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 Part B Part A Part B Total gapNo gap Spring

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