Sag Analysis of an Automotive Roller Blind System in Terms of the Variation in the Production Process

Transcription

1 Sag Analysis of an Automotive Roller Blind System in Terms of the Variation in the Production Process 5th European HyperWorks Technology Conference (EHTC) November 7 9, 2011 Bonn, Germany D. Bernhardt, R. Peter Inteva Products Roof Systems Germany GmbH, Dietzenbach

2 Agenda Introduction Determination of Input Parameters Determination of Transfer Functions Determination of Input Parameter Variations Monte-Carlo Analysis Results Summary & Outlook

3 Inteva Products Roof Systems: Interior Systems: Closures: Motors & Electronics: 42 Locations 18 countries 4 continents 2.2 Billion USD Annual Revenue 2008 Inteva was born from Delphi Closures & Interiors 2011 Inteva Acquires ArvinMeritor s Body Systems Business Unit

4 Roller Blind System Main customer interface requirements Proper optical impression No significant sag of the fabric Reliable operation to control light exposure No strength, noise or operational issues mainly driven by lateral and transversal forces in the fabric Due to the variations in the manufacturing process a predictive model for the sag and the forces in the roller blind system is developed to assess and optimize scrap rates in terms of Material property limits Process specifications

5 Main Steps for Statistical Prediction by Monte- Carlo Approach INPUT ANALYSIS OUTPUT Determination of the transfer functions Determination of main input factors Determination of the variation of the input factors Random data (Populations) Monte-Carlo Analysis Key characteristics

6 Roller Blind System Design Frame Rollo Guide Rail Steel tape Fabric Cross Bow

7 Force [N] Determination of Main Input Factors retracted Force Measurement Bow open Bow close Fabric close Steel tape close Fabric open Steel tape open Linear (Fabric open) Linear (Steel tape open) Linear (Fabric close) Linear (Steel tape close) -20 extended -30 Displacement [mm] Quantitative determination of the effect of main components Sequential disassembly of components and evaluation of differences, averaged for several samples Following components are analyzed Fabric Cross Bow Steel Tape

8 Parameter Diagram Pretension distanc e Friction coefficient Steel tape force Cross bow force Production process Sun roof assembly process Normal force in fabric Fabric operational force Rollo operational force Fabric stiffness Fabric Weight Bearing distanc e Sag

9 FEA Model for Sag Analysis Analysis with ANSYS with large deformations Application of gravity load (1g) Frame with mounting conditions Cross bow Gap definitions to fabric Fabric Orthotropic material law EZ, EX, EY Steel tape merged to fabric, coupled to frame Half model application of symmetry conditions and pre-tension distance in the fabric

10 Relationship Between Sag, Normal Force and Pretension Distance FEA Equations based on rope theory: f 2 s * g * 8 H Sag s 0 s* H E * A 3 s * g 24* H 2 2 Mag Clamping displacement [mm] Froce [N iny] Relation Force [%] Sag [mm in Z] Relation Sag [%] FEA 46,58 100% 2,18 100% 1 Analytical 48,26 104% 2, % Evaluation and Correlation of numerical & analytical results

11 Analytical sag [mm] Correlation Testing for Sag/ Normal Force Measured sag [mm] A fairly good correlation between analytical solution and measurement can be achieved

12 Friction Force Relationship Operational / Normal Force 25 Force measurement device Steel cable connected to steel tape Rollo guide rails Test_1 Test_2 Linear Normal Force Determination of friction coefficient Test is performed for several weights (normal forces) Steel weights

13 Secant E-Modul [MPa] Variation of Fabric Stiffness 250,0 200,0 150,0 100,0 50,0 0,0 0 0,2 0,4 0,6 0,8 1 Stress [MPa] 1A 1B 1C 1D 1E 1F 2A 2B 2C 2D 2E 2F 3A 3B 3C 3D 3E 3F 4A 4B 4C 4D 4E 4F 5A 5B 5C 5D 5E 5F 50% 15,9% 0,135% 84,1% 99,87% Spec averg Spec Min Stress Strain data converted to secant E-Modulus Consideration of non-linear behavior by defining E-Modulus depending on the stress Variation can be captured by log normal distribution

14 Y-Displ. at bearing [mm] Variation of Bearing Distance Rollo guide rail distance for steel tape bearing Load case front part 1 mm 1 mm Guide Rail Front Part Panel 2 Rear Part Load case rear part 1 mm Guide Rail Load case panel 2 The frame is over constrained For the statistical analysis a sensitivity needs to be calculated done by FEA models and unit load cases Resulting tolerance can be calculated by including the sensitivity in the RSS approach 1,2 1 0,8 0,6 0,4 Front Part_1 mm wider Rear Part 1 mm wider Panel_2 1 mm wider 0, ,2 X-Coordiante [mm]

15 Monte-Carlo Analysis Results Scrap Scrap Sag Operational Force Monte-Carlo Analysis in Excel (5000 samples) Input of random data (populations, Minitab) derived from test results Implemented analytical relations Iteration of normal force Calculation of sag Prediction of out of spec parts

16 Summary & Outlook The response of a fairly complex system can be calculated by relatively simple analytical equations and approaches. This allows to cover the variation in the analysis w/o exorbitantly increase the calculation effort Key for this approach is to reduce the complexity of the analysis approaches, but still capture the main effects correctly. Perquisite for this is the availability of suitable test methods and data Outlook Further refinement of input statistics Including additional input parameters to better represent noise effects

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