R. Ducloux Transvalor Different Challenges for Cold Forming Simulation WORLD LEADING NUMERICAL SIMULATION SOFTWARE
Schedule User expectations Process specificities Material behavior 2
User expectation: Net Shape Aspect Rotary swaging example Incremental process with many blows (several hundreds) Produce an hollow component with some groves inside Cold Forming Process description Achieved computation 25 blows in animations, 457 computed 3
User expectation: Net Shape Aspect Final shape Inner surface detail No machining of the inner surface Groves filling is a key point for torque transmission Simulation needs to be very accurate in terms of shape Mesh with millions of elements Mesh in cross sections Damage Criterion 4
User expectation: Ability to manage Sharp Angles Threads rolling example Mesh in cross sections 5
Process specificities: Flashless No flash to accommodate possible excess of material Mechanical press not adapted to creeping mode Need to keep some room in die cavity But part surface not in contact should remain within tolerances 6
Process specificities: Flashless Four stages bushing example 7
Process specificities: Flashless Shape comparison in upper area 8
Process specificities: Flashless Shape comparison in lower area A: Shape of the edge, B Difference of extrusion, C Slope, D under filling 9
Process specificities: Complex tooling Alternative to reduce breaking risk is to use Spring loaded dies Dies remain closed to guaranty correct filling Die open in case of too high Force Implicit solving and clean forces provide stability 10
Process specificities: Complex tooling Four spring loaded die Upper Punch Prescribed kinematic Upper Int Move with UP until Force push it back Upper Die Move with UP Until contact with LD Lower Die Move under pressure Punches and external dies Upper and lower floating dies Lower Int Move under pressure Full die set 11
Process specificities: Complex tooling Initial situation Intermediate dies start To open (0.04 s) 250 200 Force 150 100 50 0-50 -100-150 -200-250 U Punch L Punch U Die 0,00 0,01 0,02 0,03 0,04 0,05 0,06 0,07 L Die U In L Int Summ 5 0 0,00 0,01 0,02 0,03 0,04 0,05 0,06 0,07-5 -10-15 -20 U Punch L Punch -25 Intermediate dies reach final position (0.055 s) Final situation -30-35 -40 U Die U Int L Die L Int -45-50 Displacement 12
Process specificities: Complex tooling Preloaded dies 10 deformable bodies (last stage of a 4 stages forming) Initial and final position First principal stress Outer ring in tension Elastic displacement 13
Process specificities: Complex die kinematic Combination of rotation and displacement Gear rolling concept 14
Material behavior: Elastic Effects, anisotropy, Forging of a bolt Stamping example Tool stack Red line: RigidPlastic (incompressible) Grey line: ElastoPlastic Comparison between actual and simulation using Hill assumption Isotropic assumption gives axisymetrical result 15
Material behavior: Elastic Effects LGV tank example Ribs are designed to accommodate Dilatation due to temperature variations Strain at different process stages 16
Material behavior: Elastic Effects First principal stress distribution at the end of stage 1 Before and after unloading Profile in thickness SpringBack 17
Material behavior: Elastic Effects Actual forming and simulation comparison Actual pat and Simulation Superposition 18
Conclusion & Outlook Simulation can be a real predictive tool providing: Process details are taken into account Accurate material behavior is used Efficient numerical technology is used to achieve computation in realistic time New frontier Keep same accuracy to predict Heat Treatment effects Include that in global optimization loop 19
Hardness of a car seating part Experiments Simulations Many experiments have been made on case hardening parts to have information on hardness, more especially the gradients of hardness in a tooth. Height 1 Height 2 Height 3 3,5 mm Hardness HV0,2 20
Dimension control of a car seating part Tracking of dimensional changes during the process Node 1 Initial CAO = 42,00 mm 1 Node 2 Initial CAO = 38,0186 mm 1 Exit Furnace Back to room temperature Delta simu Delta experiments QUENCH 42,365 41,926-0,074-0,082 CASE 42,366 41,914-0,086-0,084 2 2 Exit Furnace Back to room temperature Delta simu Delta experiments QUENCH 38,350 37,979-0,0394-0,029 CASE 38,350 37,960-0,0586-0,07 21
Automatic Optimization: Spline forging Reduce to 4 Stages Parameters: - Die geometry Objective - Reduce Energy Constrain? - Die filling - No fold 22
Automatic Optimization: Spline forging Force (T) Obtained results 50 40 30 20 10 Stage 1 Stage 2 Stage 3 Stage 4 Stage 5 New Stage 34 New Stage 5 0 0,00 0,02 0,04 0,06 0,08 0,10 0,12 4 steps Maximum force is significantly reduced -10 Time (s) 23
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