Journal of Failure Analysis and Prevention

, Volume 10, Issue 1, pp 38–49 | Cite as

Fatigue Failure of Extrusion Dies: Effect of Process Parameters and Design Features on Die Life

  • S. S. Akhtar
  • A. F. M. Arif
Technical Article---Peer-Reviewed


Analysis of die failure plays an important role in the prediction and prevention of die failure, and subsequently in improving economics of any metal-forming process. Industrial experience has shown that fracture is the most common mode of failure in the case of hot aluminum extrusion dies. The purpose of the present work is to implement fatigue damage models in a Finite Element code for identification of critical process parameters and die design features in the case of fatigue being the dominating failure mode. For the maximum number of billets extruded by the die before fatigue crack initiation (fatigue life cycles in extrusion), Morrow’s stress- and strain-life damage models are implemented for axisymmetric flat extrusion die. With the help of finite element software ABAQUS, extrusion process is simulated and dynamic stress and strain values were obtained by first identifying the potential fatigue location in the die. The evaluation of applicability of the damage models is done for specific hot extrusion die made of H13 steels with Al-6063 as billet material. By considering temperature and strain rate as process parameters and bearing length and fillet radius of the die as geometric features, different simulation runs are performed to investigate the effect of process and design features on the useful die life. Morrow’s stress life model shows a good correspondence between computed and actual failure of dies. By establishing correlations of die life with process and design parameters under different conditions, it was shown that the present investigation is a useful guideline at die design and extrusion process stages.


Fatigue analysis Extrusion die FE simulation Critical parameters 


A very important factor contributing to the performance and economics (efficiency and quality) of any hot metal-forming process is the service life of tooling. Product rework and rejects can be traced back to various defects spread over the die life cycle: die design, die manufacture, heat treatment, and die service. A number of mechanisms can cause initiation and propagation of die damage. Analysis of tool and die failure thus plays an important role in the prediction and prevention of die failure, and subsequently in improving process economics. In die fracture-failure, there are two common modes: one is overload fracture and the other is fatigue fracture. The large deformation load that exceeds the strength limit of the die in the forming processes can cause overload fracture, while, on the other hand, fatigue fracture is generally caused by the fact that the die works under severe loading condition, which helps the micro-crack initiation and growth in forming process as explained by Fu et al. [1]. In hot extrusion process, fracture is the root cause for die failure as investigated by Arif et al. [2, 3]. Therefore, it is very desirable to identify critical process parameters and die design features so as to predict their susceptibility to failure due to cyclic fatigue. Finite element simulation is an efficient tool for analysis of forming processes and tool loading. By application of damage models, it is possible to calculate from the stress–strain values obtained by finite element analysis a specific damage variable of the material due to fatigue loading. In Fig. 1, a typical extrusion loading cycle is shown. In each cycle, a billet is extruded through the die subjecting it to fatigue loading. As the billet is compressed against the die, a deformation zone in front of the die opening forms and extrusion begins with increase of extrusion pressure and reaches to maximum (breakthrough) pressure. Beyond the breakthrough pressure, the process enters the steady-state stage with gradual decrease of pressure. In the figure, \( \sigma_{\rm max } \) and \( \sigma_{\rm min } \) represent the maximum and minimum stresses in the die, respectively, corresponding to maximum and minimum load provided the die is not pre-stressed which is the case in hot extrusion dies. Pre-stressing is usually provided in cold extrusion dies in which case there will be some \( \sigma_{\rm min } \) even if the load is zero initially. \( \sigma_{\text{m}} \) designates the mean stress during the loading cycles, which is equal to the average of \( \sigma_{\rm max } \) and \( \sigma_{\rm min } \). Half the stress range (the difference between the maximum and minimum values) is called the stress amplitude, \( \sigma_{\text{a}} \), in the loading cycle.
Fig. 1

Extrusion loading cycles

So far, numerous studies have been performed for the improvement of tool fatigue life. Tong et al. [4] have used S-N approach and finite element analysis for the estimation of forging die fatigue life and validated it by some industrial case studies. Fu et al. [1] employed both stress- and strain-based fatigue analysis techniques to develop the relationship of die life with its various affecting factors. Falk et al. [5] used different approaches for estimation of time until crack initiation for closed cold forging die and calculated damage parameters yielding different estimates of tool life and compared with practical data. Falk et al. [6] showed that damage approaches like local stress, local energy, and volume-based lifetime approach could result in reasonable lifetime predictions. They claimed that the tool life estimation based on stress conditions should be calculated in terms of effective stress. Saroosh et al. [7] focused their research on high cycle fatigue life estimation based on material property of workpiece. Their calculation based on Morrow’s equation was proved to be more realistic compared to Basquin’s equation.

The purpose of the current study is to identify critical process parameters and die design features in fatigue life of axisymmetric extrusion die using Morrow’s stress- and strain-life models. Finite Element code ABAQUS is used for determination of stress states at the critical locations of the die. The materials of die and billet investigated are H13 steel and Al-6063, respectively. Considering temperatures and strain rate as process parameters and bearing length and fillet radius as die features, different simulation runs are performed by varying these parameters/features to investigate the effect on useful die life. The predictions are also compared with the industrial data.

Observations on Die Failures in Local Extrusion Industry

The author’s previous work [2, 3] based on real industrial data has revealed that fracture is the most dominant failure mode in actual industrial scenario. Two solid-profile dies (Die-A and Die-B) scraped due to fracture are illustrated in Fig. 2. Cross-sectional view of Die-B is also illustrated in the figure to describe the internal features of the die. These dies were manufactured at local die manufacturing plant from ORVAR 2 Microdized (AISI H13) steel, properly heat-treated and surface hardened. Cylindrical billets of Al-6063 preheated to about 425 °C were extruded using these dies. The dies were also preheated to about 425 °C before being placed into the extrusion chamber (container). The container is maintained at around 425–475 °C, but heats of friction and plastic deformation may increase this temperature to well above 500 °C. Die-A having three cavities were intended for production of 120,000 kg of aluminum profiles but failed only after extruding 91,595 kg (equivalent to 1425 billets having average length of 650 mm and 216 mm diameter). Single cavity Die-B designed for extruding 100,000 kg of aluminum profiles was scrapped after production of 42,327 kg of aluminum (equivalent to 698 billets having 254 mm diameter and average length of 500 mm). Failure regions in both these were found to be the sharp corners and square edges near the bearing area. It clearly indicates that die geometric features have prominent effect on die failure. These features can be improved at design stage to avoid early failures of die.
Fig. 2

Failed dies collected from local extrusion industry

Fatigue Failure Approaches Employed

The following Morrow’s stress- and strain-life equations are used for the prediction of fatigue life cycles of extrusion die.

Morrow’s stress-life approach:
$$ \sigma_{\text{a}} = 2N_{\text{f}} (\sigma_{\text{f}}^{\prime} - \sigma_{\text{m}} )^{b} $$
Morrow’s strain-life approach:
$$ \varepsilon_{\text{a}} = {\frac{{\sigma_{\text{f}}^{\prime} }}{E}}\left( {1 - {\frac{{\sigma_{\text{m}} }}{{\sigma_{\text{f}}^{\prime} }}}} \right)\left( {2N_{\text{f}} } \right)^{b}\,+\,\varepsilon_{\text{f}}^{\prime} \left( {1 - {\frac{{\sigma_{\text{m}} }}{{\sigma_{\text{f}}^{\prime} }}}} \right)^{c/b} \left( {2N_{\text{f}} } \right)^{c} $$
where \( \sigma_{\rm max } \) is the maximum stress, \( \sigma_{\text{a}} \) the stress amplitude, \( \sigma_{\text{m}} \) the mean stress, \( \varepsilon_{\text{a}} \) the strain amplitude, \( \sigma_{\text{f}}^{\prime} \) the fatigue strength coefficient, \( \varepsilon_{\text{f}}^{\prime} \) the fatigue ductility coefficient, b the fatigue strength exponent, c the fatigue ductility exponent, and E the modulus of elasticity.

Both these models are based on the use of damage parameters (i.e. \( \sigma_{\text{a}} \) and \( \varepsilon_{\text{a}} \)), which describe a mathematical relationship between maximum stress–strain conditions and the number of cycles to initiation of crack. These damage models are uniaxial and it is difficult to handle how process parameters and design changes will affect the multiaxial stress–strain state under loading. Successful implementation of these damage models requires the determination of existing load conditions in the potential fatigue location of the die, reliable fatigue data at required process conditions, and the accuracy and reliability of numerical values obtained from simulation [6].

Damage Parameters Used

The fundamental problem in reducing multi-axial loading conditions in the die to an equivalent uniaxial value is the choice of damage parameter used in the failure equations. The results gained from the numerical process simulation show that maximum principal stress takes small values compared to effective von Mises stress values in all case studies. Therefore, effective von Mises stress is used for the determination of damage parameter, \( \sigma_{\text{a}} \), in the case of stress-life equation. However, considering strain-life equation, the maximum principal strain is considered for calculating damage parameter, \( \varepsilon_{\text{a}} \), due to the reason that effective von Mises strain is not available as output variable in the simulation software. Since the initial stress and strain in the die is zero, the mean stress, stress amplitude, and strain amplitude is half of maximum values in all cases. Furthermore, the extrusion dies were deformed in elastic regime under extrusion pressure, elastic behavior of dies is analyzed and plastic strain values are neglected in life prediction [5]. Therefore, plastic terms are neglected in using strain-life equation (Eq 2).

Fatigue Data Used

Estimating die life using fatigue failure equations based on finite element results requires appropriate fatigue parameters. These parameters should describe the fatigue behavior of the die material. The accuracy of such material parameters is very important for accuracy of die life calculation. This information is not readily available in the literature. For die life estimation, an attempt is made to gather high-temperature properties data from different sources for H13 die steel and Al-6063 billet. Some assumptions have also been made which may affect life estimation. Apart from other fatigue parameters, it has been found that value of modulus of elasticity, E, and fatigue strength coefficient, \( \sigma_{\text{f}}^{\prime} \), greatly affect die life estimation. The constant \( \sigma_{\text{f}}^{\prime} \) is often approximately equal to true fracture strength of material, which is usually a value larger than the ultimate tensile strength by amount 50 ksi (492 MPa) as reported by Dowling [8]. Since the value of \( \sigma_{\text{f}}^{\prime} \) for H13 steel at different temperatures was not available, it is extracted from the relationship of hardness and tensile properties at different temperatures available from work done by Wallace and Schwam [9]. H13 in the hardness ranges from 45 to 52 RC is excellent steel for extrusion dies. In current industrial practice in an aluminum extrusion plant, nitriding is commonly used to surface harden the extrusion dies. In the case of H13 hot-work tool steel, the hardness of the nitrided surface may reach to approximately 56–62 HRC. Therefore, tensile strength values are attained at 56 RC hardness at selected temperatures. Considering the fact that the plastic strain values are ignored and only elastic analysis is to be carried out for dies, the fatigue ductility coefficient, \( \varepsilon_{\text{f}}^{\prime} \), and fatigue ductility exponent, c, are not required. The same is also assumed by Falk et al. [5] in their work. It is noteworthy that the value of fatigue strength exponent, b, decreases with temperature. However, due to the non-availability of b at different temperatures, a value of b equal to −0.0928 is used [8] in all case studies.


The numerical simulation of extrusion process and dynamic die stress state during the process provides a systematic approach for simultaneous modeling of billet deformation behavior and die stress and strain distribution during the forming process. From the point of view of metal-forming process, the flow behavior of billet material, which mainly depends upon working conditions like temperature and strain rate, greatly affects the die deformation response and hence the die stresses and strains. In addition, die material behavior also affects the flow properties of deforming billet. From the resulted stress and strains values, die fatigue life has been estimated for the given die design configuration, billet material, and other process parameters. Practically, there are many factors affecting the die life, searching for long die life would be an iterative process and the know-how and prior experiences are useful in decision making for the configuration of die service condition and die life improvement. In this study, it was not possible to explore every factor affecting die life. To illustrate the proposed methodology, four variables are considered: process temperature, strain rate, die bearing length, and die fillet radius. In order to check the accuracy and validity of simulation results, a published work done by Lee and Im [10] is first considered and one of their results is reworked.

In implementation of proposed methodology to analyze die fatigue failure, the following approach was used:
  • Identification of critical fatigue failure locations in the die during loading cycle.

  • Determination of stresses and strains in the die at critical locations.

  • Identification of critical process parameters and design features in the die based on estimated die life cycles using damage models.

Accuracy of Simulation

Prior to simulation of aluminum extrusion with flat die in the current study, a case study for cold extrusion process has been conducted similar to the work done by Lee and Im [10] and the results are compared for accuracy. Figure 3 shows the simulation conditions indicating die geometry, billet dimensions, material behaviors, etc. Due to symmetry, just half of the workpiece and the die is considered for analysis to reduce the computational time. Comparison of results shows that critical fatigue location (maximum stressed region) is the same in both cases. Furthermore, effective stress value (752.1 MPa) obtained by them is very close to the results obtained in the current simulation (792.7 MPa) as illustrated in Fig. 3, respectively. The small discrepancy in the results may be due to the factors such as definition of extrusion ratio, stress definition, different simulation software and solution procedure, different frictional coefficient, etc.
Fig. 3

Effective stress distribution obtained by Lee and Im [10]. (a) Validated results: maximum von Mises stress at critical location (b)

Finite Element Analysis

In fatigue life analysis of extrusion die, the die geometry and deformation simulation is the most important thing. Die geometry analysis determines and verifies the effects of the shape and geometry of die components such as die land, die angle, fillet corner radius, and extrusion ratio. Deformation analysis, on the other hand, reveals the stress and strain distribution in the die. The identified strain and stress provide the basic data and information for die life assessment. Simulation software ABAQUS is used for the determination of dynamic stresses and strains during extrusion process.

In order to see the effect of temperature, strain rate, bearing length, and fillet radius, three cases for each parameter are considered. The details are shown in Table 1. For the effect of temperature, flow curves of billet material at three temperatures, 300, 420, and 540 °C, are used as simulation inputs. These flow curves are considered at average strain rate of 1 s−1. Bearing land of 8 mm and fillet radius of 2 mm is used as die configuration. For strain rate effect, flow curves at three average strain rates, 0.01, 0.1, and 12 s−1 (at 420 °C), are used with 8 mm die bearing and 2 mm fillet radius as die configuration. Die geometry effect is also studied by varying bearing length (6, 8, and 10 mm) and fillet/lead radius (1, 2, and 3 mm), using input flow curves at 420 °C and average strain rate of 1 s−1. In addition to flow curves, modulus of elasticity and Poisson’s ratio is also taken at corresponding process temperature.
Table 1

Simulation results and estimated die life cycles

Varying process parameter/die design feature

Max von Mises stress, σmax, MPa

Max principal strain, εmax

Number of billets extruded (life cycles, N f)

Other simulation conditions/die configurations

Morrow’s stress-life approach

Morrow’s strain-life approach

Temperature (T), °C






Strain rate: 1 s−1






Fillet radius: 2 mm






Bearing length: 8 mm


Extrusion ratio: 25

Strain rate (έ), /s






Temperature: 420 °C






Fillet radius: 2 mm






Bearing length: 8 mm


Extrusion ratio: 25

Bearing length (L), mm






Temperature: 420 °C






Strain rate: 1 s−1






Fillet radius: 2 mm


Extrusion ratio: 25

Fillet radius (r), mm






Temperature: 420 °C






Strain rate: 1 s−1






Bearing length: 8 mm


Extrusion ratio: 25

Geometric Model

Due to symmetry, just half of the workpiece and the die are considered for analysis to reduce the computational time in all cases as shown in Fig. 4. Billet diameter is taken as 300 mm diameter and 300 mm length. Extrusion ratio is 25 in all cases. Dimensions of different features of the die like diameter, taper relief angle towards die exit, undercut length, etc., considered in the present study are taken the same as used in local extrusion setup. Furthermore, thickness of die (120 mm) also includes backer thickness. Die considered from real industry has dimensions of 40 mm (thick) × 300 mm (diameter) with 80 mm thick backer.
Fig. 4

Geometric model (all units in meters)

Mesh Model

In all cases, the die and billet are meshed while die container is assumed as rigid body. CAX4R (4-node bilinear axisymmetric quadrilateral, reduced integration, hourglass control) elements are used for both die and billet material. Since deformation occurs in extrusion problems, especially in those that involve flat die geometries, is extreme; an arbitrary Lagrangian-Eularian (ALE) adaptive meshing is used. A simple meshing technique has been developed as shown in Fig. 4. The mesh refinement is oriented such that the fine mesh along sides AB and DC will move up along the extruded walls as the billet is moved forward.

Solution Procedure, Boundary Conditions, and Contact Treatment

The process is assumed as quasi-static and solved using dynamic explicit with automatic time incrementation. Symmetric boundary conditions are applied on the centerline of the billet while the die is constrained in such a way that boundary conditions act as die backer. Surface-to-surface contact conditions are applied between billet–container and billet–die interfaces with coefficient of friction equal to 0.1.

Material Models

The die is considered as an elastic body and the billet is made of aluminum and is modeled as a von Mises elastic-plastic material with isotropic hardening. Predicting stresses and strains during extrusion processes using finite element method require appropriate inputs and mechanical properties of billet and die material. For billet material Al-6063, flow curves at different temperatures and strain rates used in simulation are taken from Kuhn [11] and shown in Fig. 5. The following temperature-dependent Young’s modulus values are use as inputs. These are taken from Engineeringtoolbox [12] and Wang [13] for Al-6063 and H13 steel, respectively.


Temperature, °C





200 GPa

162 GPa

145 GPa


60 GPa

52 GPa

48 GPa

Fig. 5

Flow curves of Al-6063 at different temperatures and strain rates used in the simulation

Poisson’s ratio and density for H13 material at different temperatures used in simulation are taken from Wang [13].

Results and Discussion

Various simulation cases were performed to analyze the influence of temperature, strain rate, die-bearing land, and fillet radius by varying material inputs and die geometry. A detail of these simulations is shown in Table 1. In all case studies, simulation is performed until steady state is reached in the extrusion cycle so that maximum stress/strain conditions in the billet and die could be achieved. The critical fatigue location was found to be the fillet radius or nearby regions in all simulation runs based on maximum effective von Mises stress criteria values. The maximum principal strain values were also found the highest in these regions in all cases. This can be observed in the distributions of von Mises stress and maximum principal strain for one representative simulation case (Fig. 6). The simulation conditions and die configuration for this particular case are temperature = 420 °C, strain rate = 1 s−1, die bearing land = 10 mm, and fillet radius = 2 mm. These distributions are recorded at ram displacements in the loading cycle corresponding to peak values. Variation in the stress and strain values during the extrusion loading cycle until steady state reached is also shown. The stress and strain values at critical die locations in the case of other simulation runs are given in Table 1.
Fig. 6

Variation of maximum von Mises stress (a) and maximum principal strain (b) until steady state is reached. The corresponding maximum value distributions at critical die location are also shown. The simulation conditions and die configuration are temperature = 420 °C, strain rate = 1 s−1, die bearing land = 10 mm, and fillet radius = 2 mm

Using stress and strain values from simulation results, fatigue cycles are estimated from Morrow’s stress- and strain-life approaches, respectively. The values of estimated die life based on both approaches for all case studies are shown in Table 1. The variation of die life (expressed in total number of billets extruded) with process temperature, strain rate, die bearing length, and fillet radius is shown in Fig. 7 and 8.
Fig. 7

Variation of die life cycles (number of billets extruded) with temperature (a) and strain rate (b)

Fig. 8

Variation of die life cycles (number of billets extruded) with die bearing length (a) and die fillet radius (b)

Results Validation Against Industrial Die Failure Data

It can be observed from Fig. 7 and 8 that stress-based approach results in less number of die life cycles as compared to strain-based approach in all cases. This indicates that stress conditions at potential fatigue regions of the die are more severe and detrimental as compared to the local elastic strains. For the purpose of validation of the current results, failure data of about 50 solid dies has been collected from local hot extrusion industry. All the dies were scrapped due to fracture failure. These dies had less than 1 mm fillet (lead) radius with average bearing land of 8 mm and failed under extrusion speed resulting in billet average strain rate of about 1 s−1. The extrusions were performed on a fully computerized 3500-ton SMS-Hasenclever press. Cylindrical billets of Al-6063 are pre-heated in stage wise furnaces before extrusion. Dies made of heat-treated and surface hardened H13 steel are also preheated before placed into extrusion chamber (container). The container is maintained at around 420–475 °C, but the temperature increases to well above 520 °C due to heats of friction and plastic deformation. Time-to-failure of die is expressed in terms of total number of billets extruded before failure. In general, these dies have different profiles and complexity level and contain certain common features. All the dies were ranked according to their extrusion ratios (as an indication of increasing die complexity) and plotted against the die life as shown in Fig. 9. It can be seen that die life decreases as the extrusion ratio increases. Considering extrusion ratio of 25 (as assumed in the current simulation model), the die life is about 700 number of billets indicated by arrows in Fig. 9. Taking into consideration die life resulting from simulation case which is most close with industrial conditions (Fig. 8b), the predicted die life of 610 billets resulted from stress-based approach (shown by arrows in Fig. 8b) is in close agreement with actual industrial data as compared with predicted die life of 2379 billets from strain-life approach. This shows that the stress-life approach can be more suitably applied in the case of hot extrusion dies.
Fig. 9

Variation of die life cycles (number of billets extruded) with extrusion ratio (R) based on failure data of 50 dies collected from extrusion industry. Die life corresponding to R = 25 is shown by dashed line

Effect of Process Parameters and Die Features

As can be observed from simulation results (Table 1), von Mises stress and maximum principal strain at potential fatigue regions in the die reduces with increasing extrusion temperature. This is likely due to the reduced flow stress and elastic modulus of the billet at higher temperature. As expected, these reduced stress and strain conditions at critical die location resulted in high life cycles prediction according to Eq 1 and 2, respectively. This is shown in Fig. 7(a). It must be noted that the temperature of the extrusion process is of vital importance, as it also determines other factors in addition to stress conditions in the die. These include maximum extrusion speed, hardness of the bearing surface of the die, friction conditions at the die billet interface, surface roughness of the extrudate, etc. The thickness of the nitride layer on the surface of the bearing area of the extrusion die decreases and gradually diminishes due to abrasion and decomposition at high extrusion temperature resulting in reduced die hardness. When the nitride layer disappears, the hardened bearing land of die is exposed, resulting in increased wearing rate due to increased affinity with aluminum. The wearing out of the bearing surface causes change in surface configuration and dimensional accuracy of the extruded product. Hence, it is not advisable to use temperature above the nitriding temperature.

The response of a billet to extrusion process can be influenced by the speed of deformation and hence strain rate which are proportional to each other. According to Saha [14], increasing the ram speed and hence strain rate produces increase in extrusion pressure. Billet flow stress behavior at different average strain rates is used as simulation inputs for strain rate effect on die life. Flow stress increases with increasing strain rate at any fixed temperature. As illustrated in Fig. 5, the flow stress increases with increasing strain rate from 0.01/s, to 1–12/s at 420 °C. This fact is also reflected in simulation results. von Mises stress and maximum principal strain values at critical fatigue locations increase with increasing strain rate as can be observed from Table 1. Due to highest stress and strain values at strain rate 12/s, predicted die life is lowest in both fatigue life concepts as shown in Fig 7(b).

von Mises stress and maximum principal strain values at potential fatigue locations slightly increase with increasing bearing length as given in Table 1. Such increase in stress/strain values also resulted in reduced die life cycles as shown in Fig. 8(a). It can be found that bearing length does not affect the life much. Friction at the die land is one of the controlling factors for retarding the metal flow and hence more stress and strains can be expected with longer land.

The influence of die fillet radius on die life is shown in Fig. 8(b). The minimum fillet radius for the die design is 1 mm. The results in Table 1 show that the optimal fillet radius is 3 mm where stress and strain values are the minimum. It can be observed that die fillet with 1 mm radius experienced highest stress and strain as compared to 2 and 3 mm radius. Such phenomenon can be attributed to higher resistance to flow in the case of small fillet radius. Figure 8(b) also indicates that the die life is increasing when the fillet radius is increasing. The trend shows that the stress and strains will continue to decrease (hence resulting in increasing of die life) when the fillet radius is increased. However, it is not practical to use fillet radius that is too large, where the final extrusion section may need more finishing operations or may not be accurate in final dimensions.

Concluding Remarks

The current investigation has shown that finite element simulation of extrusion process integrated with fatigue theory yield an efficient tool for the identification of critical process parameters and die design features in the case of fatigue being the dominating failure mode. It was found that Morrow’s stress based concept results in less number of die life cycles as compared to Morrow’s strain-based approach and it can be concluded that stress-based approach (high-cycle fatigue) is more suitable to apply in the case of extrusion die life. It is also validated by real die failure data on extrusion dies. Die life was found increasing with increasing temperature and reducing with increasing strain rate. Such behavior is likely associated with billet flow stress, which reduces with temperature and increases with strain rate. High-flow stress results in high die stresses/strains and hence more susceptible to short life. Small die fillet radius severely reduces die life due to more resistance to flow at die entry. Bearing length was found to have small effect on die life. Long bearing length results in comparatively reduced life. With the help of case studies for each variable, the validity and efficiency of established fatigue failure approaches are verified and it can be very helpful for the identification of critical process parameters and design features in die fatigue life.



The authors acknowledge the support of King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia, for this work through project # SB080002.


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Copyright information

© ASM International 2009

Authors and Affiliations

  1. 1.Mechanical Engineering DepartmentKing Fahd University of Petroleum & MineralsDhahranSaudi Arabia

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