Presentation on theme: "December 8 th, 2005 Physics-Based Process Modeling offering cost reduction, time saving, and engineering decision assistance for machining and other processes."— Presentation transcript:
December 8 th, 2005 Physics-Based Process Modeling offering cost reduction, time saving, and engineering decision assistance for machining and other processes Tahany El-Wardany
2 Overview Objective of process simulation Classification of different machining models Overview of Process Modeling Physic-Based Models Mechanistic Models Finite Element Models
3 Modeling tools Lead to best practice machining process Objective of process simulation: To create scientific requisites, development of recipes and identify and model new manufacturing technologies for affordable manufacturing of any part any material any where with no waste. Justification: New features and materials designed for better part functionality are always difficult to implement and cause high scrap rate. Current products manufacturing parameters were set and approved decades ago. New tooling, coating, coolant, and machines technologies are not utilized to reduce cost. Transferring and outsourcing manufacturing processes without proper evaluation of sources of errors lead to long time to market and waste of unacceptable parts Experimentally dependent analysis of new products manufacturing processes is not enough to identify the underlying physics of problems generated and develop the proper solutions Payback: 50% reduction of manufacturing cost and time to market can be achieved. Introduction of new processes and material is simplified
4 Why Process Modeling Process Simulation provides fundamental understanding of the relationships between process variables : Optimal range of cutting parameters Chip morphology and cutting forces Development of temperatures and stresses Influence of tool wear and premature tool failure Dynamics of the tool/workpiece/machine system Workpiece surface integrity and residual stress Process simulation reduce number of iterations and results in a substantial cost savings
5 Tools Available/Required to Eliminate Sources of Waste Product cycle to market utilize CAE tools for: Product Design and planning Time management Layout planning Ergonomics Processes simulation Logistics Waiting and Transportation Inventory Unnecessary motion Tolerances & Overproduction Unnecessary risk Inefficient processing & Product defects
6 New Lightweight & high performance material New manufacturing processes Advanced monitoring methods & On line part repair Combine parts / components Modify Dimension & Tolerance Reduce size Enable function Change driveSuperplastic forming Laser repair Online Monitoring Flow Forming Process Simulation Lead to New Promising Technologies New materials and manufacturing processes can solve many problems if utilized
7 Classification of different machining models
8 Nominal Cutting Conditions Forces Chip Load Chip flow and effective cutting angles Model Chip Load Chip flow and effective cutting angles Model Cutting Force Model Cutting Force Model Isotherms prediction Finite Element Model Residual stress prediction Finite Element Model Workpiece Geometry Tool Nose radius and angles Cutting edge radius + Wear Tool and work thermal properties Coolant properties Cutting Coefficients + Chip/tool Interface Friction Model Chip/tool Interface Friction Model Ploughing Force Model Ploughing Force Model Heat Generated Model Heat Generated Model Contact length friction coefficients Wokpiece fixture Adaptive meshing & separatio n criteria Overview of Process Modeling
9 Process Modeling Physic-Based Models To developed Finite Element and/or Mechanistic models to investigate specific aspects of manufacturing process 3D FE Face Milling model To optimize high pressure coolant application Mechanistic 3-axis milling model To reduce machining time Application Prediction of instantaneous temperature distribution along chip/tool/WP interface Prediction of instantaneous cutting Forces chip load Ac = tc * dz / cos(lead) Kn, Kf – specific cutting forces depending on material & cutting condition Result Hollow Fan Blade leading/trailing edge machining Predicted 70% machining time reduction Chip Insert Temperature Isotherms 23.6 ci/min Metal Removal Rate on Titanium Demonstrated Innovative Tool Design - High pressure, integral and adjustable coolant nozzle Tool PW 4000 LE/TE Machining Cutting Time (Sec.) Force Optimization Original Production Cutting Force (N)
10 Physics-Based Model - Concept of Mechanistic Models Specific cutting pressures depend on uncut chip thickness, cutting velocity and normal rake angle For given workpiece-tool material combination, conduct cutting tests over a designed range of cutting conditions Transform the measured external cutting forces to obtain the rake face force components Based on the chip load, determine the specific normal pressure and friction pressure Determine the constants a’s and b’s by linear regression Normal force and friction force proportional to chip load: Chip load determined from cutting geometry K n and K f dependent on material combination, cutting conditions and cutting geometry
11 Physics-Based Model - Concept of Mechanistic Models Mechanistic-based modeling enables optimization of all machining process tool work chip Processing Time Constant feed rate Variable, acceptable loads 100 Slow and constant feed acceptable forces and chip loads long cycle time Traditional Process Approach Machining Loads Proportional To: 1) Chip load 2) Cutter speed 3) Material Properties Approach Using Physics Based Simulation Time Optimized Loads Variable feed rate Savings Variable feed safe, optimized loads shortened cycle time 100 Each cutting segment is simulated as simple oblique cutting Process simulator and optimizer Interaction Forces Defined & Summed UTC PROPRIETARY
12 Physics-Based Model - Concept of Mechanistic Models UTC PROPRIETARY Model predict details of cutter-work contact parameters Cutting parameters such as chip thickness and feed rate vary significantly along tool axis and tool path
13 Mechanistic Modeling Prediction of the tool deflection Edge definition in space
14 Dynamics Characterization of Flexible Part Flexible part representation Effect of part dynamics on tool geometry Real and Imaginary parts representing the dynamics of the part/fixture system 0 degree phase 270 degree phase180 degree phase 90 degree phase
15 Prediction of Dynamic Forces and tool deflection Optimize machining process for flexible tool Predicted dynamic forcesPredicted dynamic tool deflection
16 Physics-Based Model – Concept of FE Modeling Finite Element method (FEM) provides a good approximate solution to continuum problems using a numerical discretization scheme FEM models allow for real geometric relations and complex boundary conditions. FEM allows studying the effect of various material models on surface produced Detailed information can be obtained from FE simulation of machining process Excessive computational times and the need of carefully designed calibration experimentation limit the use of FEM in predicting residual stress.
17 1- Simulation of chip separation criteria Cutting is simulated by forcing the tool to move into the workpiece in small steps. Untied the nodes on previously defined parting line. Arbitrary - influence the residual stress prediction. Mesh is fixed in space and the material flow through the mesh. Iterative modification of the chip geometry to satisfy the velocity boundary conditions. Assume parting criteria such as a stress or strain value. Eliminates the effect of cutting conditions on the prediction of some process output. More accurate to simulate the chip separation resulting from plastic flow of the material. Automatic remeshing occurs to represent the deformed configuration of the workpiece based on the following criteria: Remeshing is required after specific number of increments Remeshing is required if tool penetrate the workpiece Remeshing is required if element distorted Remeshing is required if element angle deviation exceed a specified value Physics-Based Model – Concept of FE Modeling
18 Physics-Based Model – Concept of FE Modeling 2. Presentation of the physical properties of workpiece materials Accuracy of the FE analysis is principally dictated by the accuracy in presenting the material physical properties. The constitutive equation of D2 tool steel in its hardened state is units of stress, strain rate, and temperature are psi, 1/s, and deg F, respectively.
19 Effect of material flow stress equation on Chip Formation and temperature distribution Chip Formation Heat generated on the flank and rake face Heat generated on the flank and rake face Chip Formation = ( ) ( log( . / . o )(1-((T ) / ( )) = ( ) ( log( . / . o )(1-((T ) / ( )) 1.78 Physics-Based Model – Concept of FE Modeling
20 Stick-slip friction analysisNo Friction analysis Force Temperature 3. Friction characteristics in the interface zone Friction occurs at the chip tool interface under extreme conditions of temperature, pressure, and strain. It is important to determine the coefficient of friction experimentally since it is dependent on cutting conditions and tool geometry. Friction conditions affect the chip formation and consequently the accuracy of the results obtained Physics-Based Model – Concept of FE Modeling
21 4. Type of Analysis- Coupled Thermo - Mechanical Finite Element Heat Transfer Analysis Mechanical Analysis Heat generated due to plastic deformation and friction Changing geometry (remeshing) due to large deformation Changing contact conditions Temperature dependent boundary conditions Temperature dependent material Thermal expansion Temperature Thermal stress Material properties Stresses - Plastic strain - Strain rate Nodal coordinates - Contact forces Physics-Based Model – Concept of FE Modeling
22 Large strain theory Plane Strain Updated Lagrangian formulation Remeshing occurs as tool advanced to the workpiece, element distortion, or tool penetration in the workpiece; Stick slip friction representation at the tool-chip interface is used Material flow stress is function of strain, strain rate and temperature (Johnson-Cook constitutive equation) 5. Finite Element Assumption Physics-Based Model – Concept of FE Modeling
23 6. Boundary Conditions () ambientair h T-T= On surfaces S 1 () 0 = T-T= h ambient c On surfaces S c On surfaces S a T = T ambient On surface S T Chip Tool VcVc VsVs STST SaSa Workpiece S1S1 STST ScSc SaSa SnSn V STST 0 NN usselt Re [cutting velocity (V), part diameter (D), air/coolant viscosity (u)] and Pr (Prandtl number) Air Convection Coefficients Where ReReynolds NO. Physics-Based Model – Concept of FE Modeling n K n n K *0 Diameterpart Kusselt h air
24 6. Boundary Conditions Chip Tool VcVc VsVs STST SaSa Workpiece S1S1 STST ScSc SaSa SnSn V STST K heat conductivity C p specific heat v fluid viscosity fluid dynamic viscosity Coolant velocity component on the tool face or chip Contact heat transfer coefficients wp = 0.29 and tool 0.71 Btu/in^2/sec / o F Physics-Based Model – Concept of FE Modeling
25 Tremendous amount of machining data can be obtained from each run, the following results are of general interest: Predicted Residual Stress Predicted Cutting Forces Predicted Temperature Predicted Stresses on tool face Physics-Based Model – Concept of FE Modeling 7- Output
26 Stresses on the tool and workpiece To define the possible areas of tool chipping during machining, stress concentration on the tool should be predicted Minimum Principal Stress Component Shear Stress Component Maximum Principal Stress Component Cutting speed is 80 SFM, Feed is in/tooth, Axial Depth of cut is 0.3 in, Tool material is Carbide, Workpiece material is Titanium, Materials properties is function, of strain, strain rate and temperature.
27 Strain and strain rate on the tool and workpiece Shear strain Component Strain rate 1/sec Cutting speed is 80 SFM, Feed is in/tooth, Axial Depth of cut is 0.3 in, Tool material is Carbide, Workpiece material is Titanium, Materials properties is function, of strain, strain rate and temperature.
28 Temperature Isotherms on the tool and workpiece Time (sec) in Temperature generated during machining Cutting speed is 80 SFM, Feed is in/tooth, Axial Depth of cut is 0.3 in, Tool material is Carbide, Workpiece material is Titanium, Materials properties is function of strain, strain rate and temperature Cutting Temperature oF
29 Definition of Residual Stresses in Metal Cutting Residual stress is defined as the stress that exists in an elastic body after all the external loads are removed.
30 cold, no stress cold warm, compressive cold warm, compressive hot, plastic flow cold, tension cold I II IVIII YY Y x YY Y x YY Y x YY Y x Concept of Residual Stress Generation 1-Due to Thermal Load
31 To ol Chip Path of material flow Tensile Zone Compressi ve Zone Primary Deformation Zone Elastic-Plastic Deformation Zone Tension Test Bar (Position Nr.) predominantly compressive load tensile residual stress predominantly tensile load compressive residual stress (tensio n) (compressio n) strain stress (tensio n) (compression ) strain stress Concept of Residual Stress Generation 2-Due to Mechanical Load
32 These two types may occur simultaneously during machining, although they are generated by different mechanisms. Residual stress classification Residual stress is classified into two different types depending on how it is developed: Mechanical residual stresses Contingent residual stresses
34 Contingent residual stresses Those stresses that are dependent on the coexistence of the source from which they are derived Chemical reactions. Alloying. Percipitation. phase transformation. Thermal effects causing relative expansion between different constituents. Non uniform heating and cooling at the machined surface.
35 Parameters affect pattern & magnitude of residual stress Material hardness and non uniform plastic strain. Mechanical properties of workpiece materials. Cutting conditions. Tool geometry and edge preparations. Tool wear. Coolant. Mechanical deformation of the workpiece surface. Phase transformation of the workpiece structure. Restrains placed on the workpiece due to its fixture.
36 Causes of Residual Stress - and how to model it Cutting Process material properties cutting conditions tool geometry coolant fixture chip load tool wear Elast./plast. deformation friction Thermal Load Mechanical Load Residual Stress FEM model analytical model + exact geometry + inclusion of several physical effects - long calculation times + fast calculation + easy to use - simplified geometries and physical laws => necessity to simplify the process
37 Assumption usually used when mathematically predicting Residual stresses The cutting edge is sharp and no rubbing occurs. The deformation is two dimensional (i.e. no side spread). The stresses on the shear plane are uniformly distributed. The resultant force through the shear plane is equal, opposite, and co- linear with the resultant force through the rake face of the tool. Plowing forces and cutting temperature were assumed to be the main cause of residual stress.
38 Analytical Modeling of Residual Stresses in Metal Cutting Iteration Procedure Steps required of Analytical model
39 Finite Element Modeling of Residual Stress in Metal Cutting Flow chart for simulating the 3D segmental chip formation process. Effects of chip formation and (a) 0.03 mm and (b) 0.20 mm flank wear length on residual stress profile Chip formation and flank wear length on temperature distribution
40 Retention Plate S92 Yoke Grinding Process replaced by milling process 50% reduction in production time – Better Surface finish Compressive residual stress Tool Life Doubled - 3X increase in the MRR Operator intervention eliminated Prediction of Residual Stress for HSM of Titanium Prediction of Temperature for HSM of Titanium Residual Stress Modeling of High Speed Machining Process
41 Predicted residual stress for the defined Cutting Conditions
42 Predicted residual stress for 1X and 10X MRR
43 Residual stress Residual stress ksi Depth beneath the surface x0.01 in Residual stresses on the workpiece Cutting speed is 890 SFM, Feed is in/tooth, Axial Depth of cut is 0.3 in, Tool material is Carbide, Workpiece material is Titanium, Materials properties is function of strain, strain rate, and temperature
44 FE Simulation of Laser Assisted Machining 25 µm Conventional Machining Temperature Distribution 25 µm Laser Assisted Machining Shear Stress Distribution 25 µm Crack 20 µm Sub surface damage an order of magnitude smaller than grinding