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Understand the importance of Statistical Tolerance Analysis (STA) in predicting assembly variations. Flexibility in parts poses challenges not captured by rigid body analysis. Learn the method combining STA with Finite Element Analysis (FEA) to analyze and predict forces, stresses, and deformations in flexible parts. Explore the Flexible STA method steps and the significance of covariances. Discover different Geometric Covariance Methods for accurate results.
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Tolerance Analysis of Flexible Assemblies Michael Tonks
Outline • Background • Method • Example • Geometric Covariance • Current Research
Introduction • Statistical Tolerance Analysis (STA)… • statistically predicts critical assembly variations • Why STA? • Part variations propagate through assemblies • Predicting effects of tolerance stack-up allows designer to avoid assembly problems
Flexible Parts in Assemblies • Flexible parts deform when assembled due to warping and dimensional variations • Produces internal stresses and deflections • Rigid body STA cannot predict deformations and stresses in flexible parts • A method for analyzing flexible parts is needed
Aircraft Skin Panels Automotive Body Panels Plastic Assemblies Where is Flexible STA Needed?
What is Flexible STA? Analysis method combines STA with finite element analysis (FEA) • Rigid body STA gives part misalignment • FEA used to model parts as flexible bodies, rather than rigid • Statistically predicts forces, stresses, and deformations from assembling flexible parts
The Flexible STA Method Flexible STA Method Steps • Determine misalignment • Model the compliant parts using FEA • Calculate covariances • Material • Geometric • Statistical FEA Solution for assembly forces, stresses, and deformations
1. Determine Misalignment Rigid body STA is used to find the misalignment. A mean and standard deviation of the gap is found. Gap Vectors: VA, VB = Variation of parts A and B from nominal A , B = Equilibrium deflection after assembly
MSC.Nastran MSC.Marc 2. Model Parts using FEA Parts are meshed in an FEA Program: • Create geometry • Mesh each compliant part, place nodes at fastener locations • Apply displacement boundary conditions • Output the global stiffness matrices • Create Super Elements • Create Equivalent Stiffness Matrix
Matrix reduced to create equivalent super-element matrix • Small and easy to analyze • Contains all important information Create Super Element Matrices • The equivalent stiffness matrix is condensed by eliminating interior nodes that have no displacement
Calculate equivalent stiffness The Super-element matrices from the mating parts are combined to form an equivalent stiffness matrix
With real parts, nodal variations are NOT independent • Problem solved using covariance Problems with STA Analysis • Some STA methods treat all nodes as independent from all other nodes
Partially Correlated Uncorrelated 3. Calculate Covariances Fully correlated • Covariance describes the interdependence between random variables • There are two sources of covariance in flexible assemblies: • Material Covariance • Geometric Covariance
3A. Material Covariance • Displacing one node affects the displacement of surrounding nodes • Described by the stiffness matrix of the part
3B. Geometric covariance • Nodal variations are not independently random • Part surfaces are continuous • Random surfaces must be used to include covariance effects in statistical analyses
4. Statistical FEA Solution Completely Characterizes surface with 2 FEA solutions • Mean FEA Solution • F=Keq() • Variance FEA Solution • Geometric Covariance cov = S ST • Material Covariance Fcov = Keq covKeqT Force Covariance Matrix
Example Sample problem analyzed using FASTA method and Monte-Carlo Method • Simple lap joint of two thin plates • Monte-Carlo method used with covariance • Results compared from two methods
Example Standard deviation of closure force Monte Carlo FASTA • 5,000 FE solutions • Large sample size required for accuracy • Slow • 2 FE solutions • Very similar results • Very Fast
Method Comments • Covariance matrix critical for accurate results • Material covariance method well established • Best geometric covariance method not yet determined • Best way to characterize surface is difficult question
Geometric Covariance Methods • Three surface modeling methods have been developed to calculate Geometric Covariance • Bezier Curves • Polynomial Curves • Spectral Analysis
Polynomial Method Surface Profile Variation of points is constrained to be a polynomial curve • Sensitivity matrix found in terms of neighboring points • Sensitivity matrix gives continuity conditions used in finding the geometric covariance curve
Polynomial Covariance Matrix • Matrix shows interdependence between any two nodes • Interdependence created with 3rd order polynomial Node i Node j
Polynomial Method • Advantages • Simple to apply • Can handle long wavelengths • Disadvantages • Does not consider frequency spectrum • Must be matched to wavelength of surfaces
Spectral Analysis Method FFT 2 Models surface variation as a finite sum of discrete sinusoids
Create Covariance Matrix • Because the covariance is assumed to be independent of location, every row of the covariance matrix is similar • Variance, the diagonal terms of the covariance matrix, is the autocorrelation function at zero separation • The autocorrelation function can be shifted to form each row of the geometric covariance matrix: Autocorrelation Geometric Covariance Matrix
Wavelength Effect Wavelengths of surface variation effects stress in part Standard deviation of assembly stress x \L=1 \L=1/2 \L=1/3 \L=1/4
Spectral Analysis Method • Advantages • Models surface variations • Takes in account wavelengths of variations • Disadvantages • Cannot model wavelengths longer then part lengths
Current Limitations • Results of three Geometric Covariance methods have never been fully compared • Spectral Analysis Method cannot analyze variations with wavelengths greater then surface length • Never applied to production assemblies
Flexible STA Research Sponsor: Boeing Phantom Works 3 Year Project Goal: Create software analysis package for aircraft assemblies
Research Plans • Research to be conducted at BYU • First Year Plans: • Two Masters Research Projects • Develop measurement techniques • Preparation for creation of analysis software
Application to Production Assemblies Leading Edge Assembly Flexible Skin Rigid Spars Partnership with Boeing/Salt Lake • Test Assembly Requirements: • Small enough to be measured on the BYU CMM machines. • Not too complex. Not too many parts • All metal parts. Joined by metal fasteners. • Assembly force required to close gaps between mating parts. • Available in small quantities for measurement purposes. Assembly
Project 1 Goal: To create a method that combines the strengths of current methods • Analyze simple 3-D problem with all current geometric covariance methods and compare results • Create hybrid method that can analyze surface wavelengths longer than mating surfaces
Project 2 Goal: Apply Flexible STA methods to a real assembly • Use rigid body STA to find gap variation • Measure real parts • Characterize variation statistically • Use hybrid flexible STA method to predict resultant deflections, stresses, and forces when assembled
Conclusion • Flexible assembly STA research at BYU moving from theoretical to real applications • Will be important tool for: • Aerospace • Automotive • Electronic • Many More!