Optimization of Plate Forming Process Parameters By Mohamed Jolgaf Prof. Dr. S.B. Sulaiman, Dr. M. K. A. Ariffin Dr. A. A. Faieza and Dr. B. T. H. T. Baharudin.

Slides:



Advertisements
Similar presentations
Chapter 24 ECONOMIC AND PRODUCT DESIGN CONSIDERATIONS IN MACHINING
Advertisements

Course Introduction to virtual engineering Óbuda University John von Neumann Faculty of Informatics Institute of Intelligent Engineering Systems Lecture.
Optimal Shape Design of Membrane Structures Chin Wei Lim, PhD student 1 Professor Vassili Toropov 1,2 1 School of Civil Engineering 2 School of Mechanical.
Solutions for Prestressed Reinforced Concrete Structures
University of Minho School of Engineering Institute for Polymer and Composites Uma Escola a Reinventar o Futuro – Semana da Escola de Engenharia - 24 a.
Chapter 14 設計最佳化 Design Optimization. 2/33 Contents 14.1 何謂設計最佳化 ? What is Design Optimization? 14.2ANSYS 設計最佳化 Design Optimization with ANSYS 14.3 實例.
Project 2: Torque-Arm Modeling, Simulation and Optimization
Chapter 17 Design Analysis using Inventor Stress Analysis Module
Prediction of Load-Displacement Curve for Weld-Bonded Stainless Steel Using Finite Element Method Essam Al-Bahkali Jonny Herwan Department of Mechanical.
Bulk Deformation Forming Processes
LMAF / EPFL What's new? Tested 9 specimens (3 plates, 1mm joint): 2 cameras -> local / global deformations 2 cameras -> local / global deformations variability.
A Designer’s Approach for Optimizing an End-Loaded Cantilever Beam while Achieving Structural and Manufacturing Requirements Timothy M. Demers November.
CAD/CAM Design Process and the role of CAD. Design Process Engineering and manufacturing together form largest single economic activity of western civilization.
Impression-Die Forging (cont’d) F=K p Y f A –K p – presure multiplying factor Simple shapes (without flash): 3-5 Simple shapes (with flash): 5-8 Complex.
FE Modeling Strategy Decide on details from design Find smallest dimension of interest Pick element types – 1D Beams – 2D Plate or.
MODELLING THERMAL EFFECTS IN MACHINING BY FINITE ELEMENT METHODS Authors Andrea Bareggi (presenter) Andrew Torrance Garret O’Donnell IMC 2007 Department.
Modelling and optimal design of sheet metal RP&M processes Meelis Pohlak Rein Küttner Jüri Majak Tallinn University of Technology 2004.
A Finite Element Study of the Deformability of Steel Jingyi Wang Qi Rui Jiadi Fan.
Introduction to virtual engineering László Horváth Budapest Tech John von Neumann Faculty of Informatics Institute of Intelligent Engineering.
Conventional Weld Calculation
J. McPherson; October Sensitivity of Carbon/Epoxy Laminates to Void Content A Thesis Proposal Submitted to the Graduate.
August 02, 2012 Abdolreza Bayesteh Kaustubh Ladia.
9.0 New Features Large Deformation Analysis of thin plate assembly spotwelded together Workshop 2 Spotwelds.
Computer Aided Mechanical Design
Lecture No 111 Fundamentals of Metal removal processes Dr. Ramon E. Goforth Adjunct Professor of Mechanical Engineering Southern Methodist University.
Ken YoussefiMechanical Engineering Dept. 1 Design Optimization Optimization is a component of design process The design of systems can be formulated as.
Full Representation of Shop Floor Forging Practice Advantage by Increased Insight The Virtual Forging Shop MSC.SuperForge.
Ken YoussefiMechanical Engineering Dept. 1 Design Optimization Optimization is a component of design process The design of systems can be formulated as.
1 Optimization of Reinforcement Methods for Non-round Pressure Vessels By Shawn McMahon A Presentation of a Thesis In Partial Fulfillment of the Requirements.
FORMING (Conformado) Geometry, microstructure and materials FORMING vs. CASTINGS?: Even when modern castings can possses good structural integrity and.
Written by Changhyun, SON Chapter 6. ANSYS Implementation - 1 CHAPTER 6 ANSYS Implementation.
Fundamentals of Metal Forming Metal forming includes a large group of manufacturing processes in which plastic deformation is used to change the shape.
MEGN 537 – Probabilistic Biomechanics Applying the AMV Method with a Finite Element Model Anthony J Petrella, PhD.
Machining Processes 1 (MDP 114) First Year, Mechanical Engineering Dept., Faculty of Engineering, Fayoum University Dr. Ahmed Salah Abou Taleb 1.
Problem 1: Structural Analysis of Signs Post University of Puerto Rico at Mayagüez Department of Mechanical Engineering Modified by (2008): Dr. Vijay K.
Shaping Optimization of Turbine Disk and Bearing Seal Shen-Yeh Chen Structures Dept., Product Design Honeywell ES&S, Phoenix, Arizona Aug 2001.
Stress constrained optimization using X-FEM and Level Set Description
Workshop 6: Thermal Analysis of a Plate with a Hole University of Puerto Rico at Mayagüez Department of Mechanical Engineering Modified by (2008): Dr.
Written by Changhyun, SON Chapter 5. Introduction to Design Optimization - 1 PART II Design Optimization.
Exploring the Design Domain Chapter Four. Training Manual January 30, 2001 Inventory # Exploring the Design Domain A. Overview Exploring the.
FORMING (Conformado) Geometry, microstructure and materials FORMING vs. CASTINGS?: Even when modern castings can possses good structural integrity and.
Introduction Chapter One. Training Manual January 30, 2001 Inventory # Introduction Course Overview This Design Optimization course is designed.
MSC.SuperForm in Short Overview
© 2012 Su-Jin Kim GNU Bulk Deforming Manufacturing Processes Bulk Deforming ( 부피 성형가공 ) © © Su-Jin Kim Mechanical Engineering Gyeongsiang.
A. Brown MSFC/ED21 Using Plate Elements for Modeling Fillets in Design, Optimization, and Dynamic Analysis FEMCI Workshop, May 2003 Dr. Andrew M. Brown.
Simulation and Optimization of Structures under Real Operating Conditions using Nonlinear FEA Ted B. Wertheimer MSC.Software.
Rib Forging Workshop Nine REFERENCE: Training Manual Viscoplasticity (5-35)
Parametric Modeling Chapter Two. Training Manual January 30, 2001 Inventory # Parametric Modeling The basic requirement for optimization.
Workshop 2 Steel Bracket Modified by (2008): Dr. Vijay K. Goyal Associate Professor, Department of Mechanical Engineering University of Puerto Rico at.
General Troubleshooting Nonlinear Diagnostics. Goal – In this workshop, our goal is to use the nonlinear diagnostics tools available in Solution Information.
Application Development in Engineering Optimization with Matlab and External Solvers Aalto University School of Engineering.
NLISO Material Model Workshop Four REFERENCE: Training Manual Rate-Independent Plasticity (3-65)
CAD and Finite Element Analysis Most ME CAD applications require a FEA in one or more areas: –Stress Analysis –Thermal Analysis –Structural Dynamics –Computational.
Sri Harsha Garapati 1 Analysis of Single Fiber Pushout Test of Fiber Reinforced Composite with a Nonhomogeneous Interphase By Sri Harsha Garapati MS Mechanical.
Bicycle Wrench Analysis
The University of SydneySlide 1 Simulation Driven Biomedical Optimisation Andrian Sue AMME4981/9981 Week 5 Semester 1, 2016 Lecture 5.
Metal Plasticity. Goal – Introduce a nonlinear metal plasticity material to the same large deflection model from the first workshop regarding the non-linear.
ANSYS. Overview of ANSYS It is an engineering simulation software developed in 1970 by Dr. John A. Swanson It was developed to use finite element analysis.
Lagouge TARTIBU KWANDA Mechanical Engineering
Finite element mesh and load definition
Aalto University School of Engineering
Tech/ME 140: Unit 5 Lecture Mechanism Design: Introduction to Mechanisms, Synthesis Using Graphical Approach. Motion Analysis and Simulation: Animation.
Workshop 5A Metal Plasticity
Optimization of Plate Forming Process Parameters
FEA Introduction.
Chapter 4 Power Estimation in Strip Rolling Process
OVERVIEW OF FINITE ELEMENT METHOD
Bicycle Wrench Analysis
Y. Ordonez1, A. Bituin1, K. Kyain1, A. Maxwell2, Z. Jiang2
Topology Optimization through Computer Aided Software
Presentation transcript:

Optimization of Plate Forming Process Parameters By Mohamed Jolgaf Prof. Dr. S.B. Sulaiman, Dr. M. K. A. Ariffin Dr. A. A. Faieza and Dr. B. T. H. T. Baharudin Institute of Advanced Technology Universiti Putra Malaysia

Manufacturing Process Independent variables Starting material Tool Geometry Workpiece geometry Amount of deformation Dependent variables Nature of metal flow Stress, strain, deflection Defects: Wrinkles, laps... Material Prop. of product The Engineer has direct control on Independent Variables (DV) The Engineer has no direct control on dependent Variables (SV) Experience Experiments Modelling

The Material is Al-MMC 1.Metal matrix composites consist of a metal or alloy as the matrix and the reinforcement (particulate, whiskers and long fibers). 2.Particulate MMC can be conventionally processed (casting), then secondary processing such as forging, extrusion and rolling can be used 3.MMCs are very attractive to aerospace and automotive applications (↓density, ↑strength, dim. stable at ↑Temp. 4.Formed products normally have better mechanical properties than their casted or machined counter parts. For example, the Boeing 747 has about 18,600 forgings (Acharjee, 2006) 5.Research on metal matrix composites is still very limited (Sapuan and Mujtaba, 2010). Particulate Whiskers Long Fibers

FE Analysis and Optimization Finite element modeling can greatly reduce testing and time during product design FEA steps 1.Creating model Geometry. 2.Define Material Properties. 3.Generate Mesh. 4.Apply Loads. 5.Obtain Solution. 6.Present the Results. What if we want to check another dimensions (DV) to reduce the strain or stress (SV)? Do we repeat the FEA steps every time we want to check (DV) Here we need to use Optimization in conjunction with FEA to really save time

Optimization Terms 1- Design Variables. usually geometric parameters such as thickness, angle, radius etc that will be varied during the optimization process. min < thickness (t)< max 2- State Variables. usually represent some design response and offer a means of limiting the design such as (stress, strain, laps, necking) Strain (ε) < % of fractural strain 3- Objective Function. A state variable to be minimized. (for maximization 1/x) State variable that represents the (1/tanθ) has been found and then minimized Design Variable can not be defined as Objective function To do conduct optimization on ANSYS we need to use APDL

APDL is a scripting language which can be used to automate common tasks or even build a model in terms of parameters (variables). windows APDL editor ( Building the model parametrically will allow ANSYS optimizer vary theses parameters during the optimization process. Copy and past the following lines in ANSYS command prompt. !*create, Analysis File Name /TITLE,sheet metal forming /PREP7 *AFUN,DEG FRICTION=.1 THETA=80 !Change to 40 and note the change x1=.06 x3=.03 offs=.04 R1=offs/sin(THETA) x2=R1*cos(THETA) t=.006 radius=.005 K,1,0,0,0, ! Key Points k,2,x1,0,0, k,3,x1+x2,offs,0, k,4,x1+x2+x3,offs,0, k,5,x1+x2+x3,(2*offs)+t ,0, k,6,x1+x2-(t*tan(THETA/2)),(2*offs)+t ,0, k,7,x1-(t*tan(THETA/2)),offs+t ,0, k,8,0,offs+t ,0, k,9,0,offs ,0, k,10,x1+x2+(X3),offs ,0 k,11,x1+x2+(X3),(t+offs ),0 k,12,0,t+offs ,0, K,13,x1+(.4*x2)+.001,offs ,0 K,14,x1+(.6*x2)+.004,offs ,0 K,15,x1+(.4*x2)+.001,(t+offs ),0 K,16,x1+(.6*x2)+.004,(t+offs ),0 LSTR, 2, 1 ! Lines LSTR, 3, 2 LSTR, 4, 3 LSTR, 6, 5 LSTR, 7, 6 LSTR, 8, 7 LSTR, 9, 13 LSTR, 13, 14 LSTR, 14, 10 LSTR, 10, 11 LSTR, 11, 16 LSTR, 16, 15 LSTR, 15, 12 LSTR, 12, 09 LSTR, 16, 14 LSTR, 13, 15 LFILLT,2,1,radius+(t/2),, ! Fillets Radii LFILLT,3,2,radius-(t/2),, LFILLT,5,4,radius+(t/2),, LFILLT,6,5,radius-(t/2),, ANSYS Parametric Design Language

APDL enables the user to read many results after processing (/POST1) and defined these results as (SVs) to limit the design space. This will help ANSYS optimizer refine the optimization search and omits the Infeasible results. /POST1 *GET, react, NODE, 1, rf,fy,, FoForce=-react PLNSOL, S, EQV, 0, 1, *GET, eqvsts, PLNSOL, 0, MAX,,, PLNSOL, eptt, EQV, 0, 1, *GET, eqvstn, PLNSOL, 0, MAX,,, PLNSOL,CONT,GAP,0,1.0 *GET,gap1,PLNSOL,0,Min,,, congap=-gap1 *get,k14y,kp,14,loc,y,, *get,k14x,kp,14,loc,x,, *get,k13y,kp,13,loc,y,, *get,k13x,kp,13,loc,x,, *get,n14y,Node,10,u,y,, *get,n14x,node,10,u,x,, *get,n13y,node,9,u,y,, *get,n13x,node,9,u,x,, slop=((k14x+n14x)- (k13x+n13x))/((k14y+n14y)-(k13y+n13y)) finish *end *use, Analysis File Name /OPT opanl, Analysis File Name OPVAR,THETA,DV,45,80,, OPVAR,t,DV,.003,.006,, OPVAR,radius,DV,.005,.02,, OPVAR,EQVSTN,SV,,.75,, OPVAR,congap,SV,,0.1*t,, OPVAR,slop,OBJ,,,, OPTYPE,SUBP OPSUBP,30,7, OPEQN,0,0,0,0,0, OPEXE finish Such as: A design set with high strain (higher than the fracture strain ε = 0.75 ) Or with large contact gap 0.05t (sever necking more than)

Results The optimizer runs the analysis file 8 times (8 iterations). Four sets are infeasible and 3 sets are feasible. the optimal design set is one of the feasible design sets with maximum angle which is set no 8.

Results The optimal SetInfeasible Set FEA and optimization techniques are used in metal forming simulation to reduce the need for testing and experiments and to save time in order to achieve the optimal design

Thank You Mohamed Jolgaf