1. International Journal of Engineering Research and Development
e-ISSN: 2278-067X, p-ISSN: 2278-800X, www.ijerd.com
Volume 3, Issue 3 (August 2012), PP. 11-16
Billet shape optimization for minimum forging load using FEM
analysis
Sunil Mangshetty1 , Santosh Balgar2
1
Prof., Department of Mechanical Engineering, P.D.A.College of Engg,Gulbarga,India
2
Student, Department of Mechanical Engineering, P.D.A.College of Engg,Gulbarga,India
Abstract––The objective of this project work is to obtain an optimal billet shape in the consideration of the influence of
the metal flow deformation in closed die forging process. Finite element method in conjunction with optimization
algorithm (APDL) was used to analyze the effect of billet shape on forging load in axisymmetric closed die forging
process. Finite element software (ANSYS) was used to Simulate closed die forging process and then performing a series
of optimization iterations in order to obtain the optimal shape of the billet based on forging load minimization. The
material used is aluminium metal matrix composite ( AlMgSi matrix with 10% SiC particles). The goal of the simulation
and optimization process is to minimize the forging load and produce crack-free forgings. The optimal shape of the billet
that gives minimum forging load was obtained after several optimization iterations. The approach used in this study could
be extended to the optimization of more complicated forging products. Due to the advances in computer technology based
finite element software, the forging loads can be easily estimated which is iterative process in the old technique of
prototype built up and destructive testing. In the present work considering 3 critical design parameters with critical
plastic strain limit as the state variable and keeping the forging load as the objective function and the billet shape is
optimized for different diameter to height.
Keywords––Die Forging, Finite Element Method, Metal Matrix Composites, Optimization.
I. INTRODUCTION
Manufacturing Processes face major competitions in automotive industry to produce lighter, cheaper, and more
efficient components that exhibit more precise dimensions, need less machining and require less part processing. Today
forging industry is facing stiffer challenges from alternative manufacturing processes. Forging industry has to be cost and
quality conscious if it has to maintain its position over other manufacturing processes. With the rapid increase in affordable
computing power, metal forming simulation based on finite element method is becoming a practical industrial tool. By using
such tool, a forge designer could decrease cost by improving achievable tolerance, increasing tool life, predicting and
preventing flow defects, and predicting part properties.
The optimization of forging process design and forging process plan for various work materials can be based on
the maximization of production rate, minimization of production cost, minimization of die cost, maximization of product
quality, minimization of forging loads. The finite element method provide a prediction of the results of a metal forming
process, but still relies on an experienced designer to interpret the results of the analysis and modify the process based on
prior knowledge and experience. Current research efforts have sought to use computational resources to enhance and
optimize process designs based on a starting design, and improvement of the design is based on the process independent
variables, dependent variables and objective function. The main factors effecting the material flow deformation are die
shape, material properties, billet height/diameter ratio, and frictional condition at the billet/die interface. ANSYS parametric
design language (APDL) is a scripting language that can be used to build the model in terms of parameters (variables). The
APDL is used to build the model in a parametric form to enable changing these parameters during the optimization process,
so that the optimal billet shapes is obtained. The design variable (DV) is as the billet height/diameter ratio. The equivalent
strain is given as a State Variable (SV). The state variable is working as constrain in the optimization process, forcing the
design parameters to be adjusted in order to have a strain not higher than the fractural strain.
II. FINITE ELEMENT METHOD
A cylindrical billet is going to be forged to produce the final forged part shown in Fig. 1 with a minimum load
possible by optimizing the billet height/diameter ratio. The billet is represented with initial radius and then the height is
calculated based on the volume of the die cavity. The initial billet is represented with geometrical model consisting of
assemblage of finite element. Equations relating the distribution of forces and displacements of the metal are established and
the boundary condition and die movement are imposed.
11

2. Billet shape optimization for minimum forging load using FEM analysis
Fig 1: Overall geometry of close die process
Two dimensional geometry is represented for die, container and billet are shown with dimensions in figure 1. All
major initial dimensions are represented in the problem. Ansys mixed approach is used to built the geometries. For die
shape, bottom approach and other geometry top down approach is used in the problem. The geometry is built as per the
dimensions and connectivity is not maintained to carry nonlinear large deformation contact analysis to simulate closed die
forging process.
2.1 Aluminium Metal Matrix Composites
Aluminium is the most popular matrix for metal matrix composites (MMCs). Aluminium alloys are attractive due
to their low density, their capability to be strengthened by precipitation, their good corrosion resistance, high thermal and
electric conductivity, and high damping capacity. Aluminium matrix composites (AMCs) offer a large variety of mechanical
properties depending on the chemical composition of the Aluminium matrix.
Forging MMCs cause particles and whiskers breakage, and normally result in cracks at the outer surface of the
billet. To avoid fibres and particles breakage which lead to cracks, the equivalent strain of the material must be kept lower
than the fractural strain shown in Fig.2, which is ε = 1.05. The fractural strain is used in the optimization process as a state
variable maximum limit.
Figure 2 Flow curve of AlMgSi+10% SiC particles.
2.2 Problem statement
The main objective the project is to reduce the wastage of billet material and minimize the forging load required to
forge that material by using finite element simulation in Ansys environment.
2.3Objectives
 Finite element model preparation.
 Finding the optimal billet shape for proper die filling.
 Finding the minimum forging load to get crack free forging product.
 Finding the material reduction error for experimental and analysis method.
 Finding the load reduction error for experimental and analysis method.
2.4 Material Description (AlMgSi + 10% SiC Chemical composition)
Al Mg Si SiC Density (gr/cm3)
86% 1% 3% 10% 2.72%
12

3. Billet shape optimization for minimum forging load using FEM analysis
Fig 3 Design Variables
Design Variables (DV): D1 – Die Movement, R1 – Billet radius and H1- Billet Height The figure 2 shows design variables
used in the problems. These regions are selected due to its critical nature in deciding the forging load and plastic conditions.
Design variables are nothing but geometry construction variables like diameter and height. A total of 2 design variables are
considered for optimisation of the design cycle for load optimization.
State Variables (SV): Maximum plastic strain allowed for the problem equal to 1. Beyond which cracks will start in the
forging process.
Objective Function (OF): The load required for the forging process is taken as the objective function. Here the main work
is to limit the forging load in the process by design optimising the process for design variables and state variables.
Fig 4 Contact Pair Creation
Contact elements are defined between die and billet interface, billet and contaner interface. Targe169 and
Conta172 elements are used for representation. Contact manager is used to build the contact pairs between the members.
Target elements are the rigid elements and contact elements are the flexible members. Separate contact pairs are created
with reduced penetration tolerance. A friction model of 0.1 is used for simulating the problem. Contact elements are the
surface elements which have the algorithem to represent possible sliding and penetration which movement of the members
relative to each other. The die nodes are used to apply the displacement loads. Contact elements uses lagrangian approach
for better results. The status of contact, contact penetration, sliding etc can be observed in the contact simulation
Fig 5 Vonmises stress results for initial structure
13

4. Billet shape optimization for minimum forging load using FEM analysis
Analysis results for vonmises stresses are presented above. Maximum vonmises stress of 330Mpa can be observed
in the problem. Left picture is represented in 2dimensional domain and right side picture is represented in three dimensional
domains
Fig 6 Displacement Plot along the length of the sheet
The graph indicates displacement along the top nodes of the billet. The graph almost resembles inverse shape of
die. The graph almost follows the curvature of die.
Fig 7 Stress Plot
The results are shown in figure 7 for radial, hoop and vonmises stresses. Similar stress pattern can be observed for
radial and hoop stresses. But vonmises stress is high in the beginning and later reducing along the path of the top nodes.
Maximum stresses can be observed in the higer deformation regions where the members reaches to plastic state and lesser
stresses in the lower deformation regions.
Fig 8 Contact Pressure in the problem
Analysis results for contact pressure are shown in fig 8 Contact pressure indicates metal flow reaching to the
container and interface condition of die and the billet. Higher contact pressure indicates higher closeness of the object.
14

5. Billet shape optimization for minimum forging load using FEM analysis
Table 1 : ITERATIONS RESULTS
Billet(DV)
S.No Strain value Radius Height Volume Force in KN Observation
(SV) (mm) (mm) (mm3) (OF)
01 1.2164 19 19.5 21550.978 1587.2 INFEASIBLE
02 0.99E+7 20.473 28.393 37392.149 9999 INFEASIBLE
03 0.99E+7 23.087 25.988 43522.52 9999 INFEASIBLE
04 0.99E+7 21.493 27.824 40384.97 9999 INFEASIBLE
05 1.5184 21.178 20.681 29143.89 5203.20 INFEASIBLE
06 0.99E+7 21.328 27.606 39455.72 9999 INFEASIBLE
07 0.99E+7 22.554 20.742 33151.56 9999 INFEASIBLE
08 1.7100 18.887 19.521 21879.33 83.023 INFEASIBLE
09 0.99E+7 19 19.5 22118.109 9999 INFEASIBLE
10 1.5333 19.001 19.532 22156.74 91.660 INFEASIBLE
11 1.4360 19 19.509 22128.32 104.850 INFEASIBLE
12** 1.008 21 24.962 34587.89 106.250 FEASIBLE
The above table represents optimisation results. The structure has been optimised for the design constraints and best set
shown with’*” mark in the above table. Totally 12 sets are obtained for five design variables. The optimised forging load is
shown as 106.250KN. The limiting strain requirement of 1 is very difficult to get due to higher depth of die in to the billet.
To satisfy the requirements, large number of iterations is required by varying height and radius of billet. The only feasible
set available is satisfying the design and state variables requirement.
Table 2 : EXPERIMENTAL RESULTS
Billet Volume
S.No Radius Height (mm3) Load in KN Load in KN
(mm) (mm)
01 11.8 115.758
24 21.5 38910.528
02 11.7 114.777
03 11.6 113.796
04 11.8 115.758
05 11.6 113.796
06 11.8 115.758
07 11.7 114.777
08 11.8 115.758
09 11.6 113.796
10 11.8 115.758
11 11.8 115.758
12 11.6 113.796
Calculations
1) % of volume reduction = V experimentally - V analysis
---------------------------------
V experimentally
= 38910.528 - 34587.89
-------------------------------
38910.528
= 0.1110
15

6. Billet shape optimization for minimum forging load using FEM analysis
= 11.10%
2) Force reduction = F experimentally - F analysis
= 115.758-106.250
= 9.508 KN
III. RESULTS AND DISCUSSION
From the above calculation by ansys shows the following results.
Case Experimentally Simulation
Billet size R=24 mm, H=21.5 mm R=21 mm, H=24.962 mm
Volume in mm3 38910.528 34587.89
Case Experimentally Simulation
Force in KN 115.758 106.250
From the above discussion it shows the following results:
 As per Ansys results the billet size is (R=21 mm, H=24.962 mm) and experimentally the billet size is (R=24 mm,
H=21.5 mm).
 The 11.10% of material reduction error can be observed in the measurement.
 As per Ansys results the force required is 106.250KN and experimentally the force required is 115.758KN.
 The 9.508KN of force reduction error can be observed in the measurement.
IV. CONCLUSION & FURTHER SCOPE
4.1 Conclusion:
Finite element analysis in conjunction with optimization techniques, are used to develop a system for the design of optimal
billet height/diameter ratio of closed die forging process. The finite element model was built parametrically using ANSYS
Parametric Design Language. The optimization Billet Shape Optimization for Minimum Forging Load module used the
analysis file to search for the minimum objective function (forging load) by changing billet height/diameter ratio. The
optimal set is listed in Table I (*set 12*) with billet radius (21 mm) and height 24.292 and forging load (106.250 kN).
4.2 Further scope:
* Analysis process can be carried out with thermal effects.
* Problem can be executed in three dimensional space
* Impact analysis can be carried out to find behaviour of the members in contact.
* Topology optimisation can be carried out to find optimum thickness required for dies and containers.
* Composite usage can be checked.
REFERENCES
[1]. Mohammad Haider, K. K. Pathak, Geeta Agnihotri ” Preform design for near net shape close die gear forging
using simulation technique” Scholars Research Library Archives of Applied Science Research, 2010.
[2]. Harshil Parikh, Bhavin Mehta, Jay Gunasekera ” Forging Process Analysis and Preform Design”.
[3]. Mladomir Milutinović, Dejan Movrin1, Miroslav Plančak1, Saša Ranđelović2, Tomaž Pepelnjak3 , Branimir
Barišić4 ”DESIGN OF HOT FORGING PROCESS OF PARTS WITH COMPLEX GEOMETRY IN DIGITAL
ENVIRONMENT” 15th International Research/Expert Conference ”Trends in the Development of Machinery and
Associated Technology” TMT 2011, Prague, Czech Republic, 12-18 September 2011.
[4]. Lirio Schaeffer, Alberto M.G.Bito, Martin Geier.”Numeriacl simulation using finite to develop and optimize
forging process” metal work laboratory, steel research int.76 2005 No.2/3.
[5]. M. Jolgaf, S.B. Sulaiman, M. K. A. Ariffin, A. A. Faieza and B. T. H. T. Baharudin” FE Analysis and
Optimization of Plate Forming Process” 3rd Engineering Conference on Advancement in Mechanical and
Manufacturing for Sustainable Environment April 14-16, 2010.
[6]. Nassir S. Al-Arifi, Abu S. Zamani, and Jalaluddin Khan ”Billet Optimization for Steering Knuckle Using Taguchi
Methodology” International Journal of Computer Theory and Engineering, Vol. 3, No. 4, August 2011.
[7]. ANSYS, ANSYS Release 10.0 documentation. Canonsburg, PA 15317, USA.: ANSYS, Inc,2005.
16