- Email: [email protected]
Prediction of wear in hot forging tools by means of finite-element-analysis
Journal of Materials Processing Technology 167 (2005) 309–315
Prediction of wear in hot forging tools by means of finite-element-analysis B.-A. Behrens, F. Schaefer ∗ Institute of Metal Forming and Metal Forming Machine Tools, University of Hanover, Schoenebecker Allee 2, 30823 Garbsen, Germany
Abstract The intention of the work presented in this paper is the estimation of abrasive tool wear, as the major cause of failure of tools used for hot forging. Experiments are carried out to determine the wear amount after several numbers of forging cycles. For tool wear estimation, the analysed forging process in consideration of all process stages is represented with a finite-element model to compute the wear relevant parameters. A separate program is developed to calculate the tool wear by using the Archard wear model taking into account the hardness change of the tool surface layer with increasing number of forging cycles. In the end, the applied wear model is verified by comparing with the experimental results. © 2005 Published by Elsevier B.V. Keywords: FEM-simulation; Hot forging; Tool wear
1. Introduction Hot forging with temperatures between 900 and 1250 ◦ C has a high importance for the manufacturing of complex components. Due to high workpiece temperatures, high plastic strains are possible. At the same time, the forming forces are lower compared to warm and cold forming. It is especially suitable for high volume production of highly stressed components. Hence, the knowledge of the tool life time is of particular importance, in order to insure a high efficiency of the forging process [1]. The typical causes of failure of tools used for hot forging are wear, mechanical crack initiation, thermal crack initiation and plastic deformation. About 70% of all failures of hot forging tools are caused by wear [2,3]. A lot of investigations on tool wear in hot forging have shown that the hardness of the tool surface layer plays an important role for abrasive tool wear [4–6]. Due to this, the major effects, which influence the hardness of the tool material will be briefly described in the following. The high workpiece temperatures and high contact pressures during the forging process lead to large mechanical and thermal ∗
Corresponding author. Fax: +49 511 762 3007. E-mail address: [email protected] (F. Schaefer).
0924-0136/$ – see front matter © 2005 Published by Elsevier B.V. doi:10.1016/j.jmatprotec.2005.06.057
tool loadings. As a result of the thermal loadings a hardness loss of the tool material in the surface layer takes place, which significantly influences the wear behaviour of the tool material [4,5]. This hardness loss is induced by the high tool temperatures during the whole forging process, which cause the tempering of the tool surface layer [5,6]. Furthermore, in some areas of the tools where an especially high heat transfer from the workpiece occurs, the austenitization temperature of tool material can be reached during the forming process [6]. After the contact release between workpiece and tools, the tool surface cools down very fast supported by the cooling lubrication, so that a re-hardening can happen. The re-hardened layer, also called white layer, shows a higher hardness than the base material of the tools [5,6]. This phenomenon only appears during the first 10 forging cycles [6]. Additionally to the previous described phenomenon the normal hardness loss at higher temperatures has to be observed. In addition the contact normal stress σ N at the tool surface and the relative sliding velocity vrel between workpiece and tools are important factors for wear [5]. Several researchers used a wear model based on the Archard wear model to calculate the tool wear only taking into account the hardness loss due to the tempering of the tool material with increasing number of forging cycles [1,7,8]. Hence, the aim of this paper is to predict the tool
310
B.-A. Behrens, F. Schaefer / Journal of Materials Processing Technology 167 (2005) 309–315
wear at forging processes in consideration of all previously described hardness changes in the tool surface layer. Furthermore, all process stages of a forging cycle are included in the calculation of the tool temperatures. Within the scope of this paper a forging process in a closed die without flash is considered. To achieve the objective, experiments were carried out first to obtain the wear experimentally. For the estimation of tool wear, the forging process with all stages is represented with a finite-element model to compute the tool temperature, the relative sliding velocity vrel between workpiece and tools and the contact normal stress σ N at the tool surface. These parameters are applied for the calculation of the wear amount by using the Archard wear model. The verification of the wear model is realised by using the experimental determined wear. Fig. 2. Process stages of a forging cycle of the considered forging process.
2. Experiments For the experimental determination of tool wear a forging process in a closed die was performed. The forging tests with a cycle time of 12 s were done under standard forging conditions using sheared raw parts from 1.0503 (C45) with preheating temperature of 1250 ◦ C. In Fig. 1, the most important components of the tooling system and the geometry of the final part are shown. Due to the fact, that the highest mechanical loading in the forging process appears at the mandrel this component was of major interest in the experimental investigations. Furthermore, the mandrel is exposed to very high thermal loadings, because it always moves into the hot material in the core of the slug. Because of the high thermal and mechanical loadings the highest wear occur at the mandrel. Hence, the wear measurements are only done at the mandrel. For an optimal realisation of the forging tests the mandrel was changed after 500, 1000 and 2000 forging cycles. The tools were made of the hot working steel 1.2365 (32CrMoV12–28) with a hardness of 550 HV (vickers hardness). To reach this hardness a heat treatment consisting of hardening and two tempering processes with a duration of 1 h was carried out.
Fig. 1. Tooling system of the considered forging process.
The forging tests were performed by using an automated press. This automated facility consists of an eccentric press with a nominal force of 3150 kN, an induction furnace, a manipulator and an installation for lubrication. First, the slug was heated up to 1250 ◦ C by an induction furnace. After this, the manipulator inserted the slug to the ejector. Then the part was forged and finally extracted by the manipulator. At the end of a forging cycle, the lubrication of the tools with a graphite based lubrication medium was performed. For the estimation of tool wear the process time is very important. Due to this, a movie of some forging cycles was created to separate the duration of the single process steps illustrated in Fig. 2. In order to verify the simulation model according to the temperature distribution a thermograph movie was also generated during the first 100 forging cycles. Since, the punch and the mandrel were masked from the closing plate only the ejector and the die were considered in the thermograph shot. The die and ejector surface temperature at the end of the 80th forging cycle was determined as steady state temperature at the end of a forging cycle for the simulation. After the forging tests wear measurements at the worn out mandrels were performed. As reference geometry, the measured geometry of the corresponding original mandrel was used. In Fig. 3, the original and worn out geometries after 500, 1000 and 2000 forging cycles are faced. Fig. 3 makes clear, as expected, that the highest wear appears at the radius of the mandrel, due to very high thermal and mechanical loadings at this location. Furthermore, the high sliding velocity of the workpiece material causes noticeable wear in this area. Additionally to wear, at the flank of the mandrel after 500 and 1000 forging cycles an extra amount of material can be seen. This amount is effected by plastic deformation of the mandrel material. After 1000 forging cycles the additional amount at the flank of the mandrel is minimized and after 2000 cycles it is nearly completely removed in consequence of abrasive wear. Fig. 4 shows the wear amount
B.-A. Behrens, F. Schaefer / Journal of Materials Processing Technology 167 (2005) 309–315
311
cycles. Due to the enlargement of the radius the effects of the hardness increase as a result of the generation of a white layer and the hardness decrease in consequence of tempering are not visible directly at the wear profile of the radius. If there would be no significant difference between the mechanical and thermal loads during all forging cycles the wear increase has to enlarge with increasing numbers of forging cycles since a hardness loss due to tempering takes place. Walter [4] observed at a similar geometry and process that only at the radius a white layer is generated, as the highest temperatures appeared at this location. In this research work, a thickness of the white layer of nearly 0.1 mm was found out. At the flank of the mandrel just small wear occur due to the smaller mechanical loadings compared to the front surface. Only in the area of plastic deformed material of the mandrel a significant wear is visible as a result of the high mechanical and thermal loadings.
3. Simulation of the forging process
Fig. 3. Facing of original and worn out geometries of the mandrel after 500, 1000 and 2000 forging cycles.
at the front face and the flank of one half of the mandrel in detail. Due to the rotational symmetry of the forging process only one half of the mandrel is considered. Because of the enlargement of the mandrel radius (Fig. 3) induced by wear and plastic deformation during the forging cycles the mechanical as well as the thermal loadings are reduced at the radius. Hence, the increase of the maximal wear at the radius declines over the complete forging process. This means, that the wear at the radius after the first 500 cycles is larger than the wear between 500 and 1000 cycles. The same can be observed between 1000 and 2000 forging
Fig. 4. Wear profiles at the mandrel after 500, 1000 and 2000 forging cycles.
The finite-element-analysis (FEA) is an effective tool to predict die fill, residual stresses and forming forces. In addition, the FEA plays a decisive role in construction and optimization of forging tools. In order to analyze the thermal and mechanical loadings in the forging tools the considered forging process was represented by an finite-element (FE) model. The FEA was performed with the commercial FE-Code MSC.SuperForm. An advantage of MSC.SuperForm is, that the user is enabled by using existing subroutines to solve his specific problems. In this case, existing subroutines were used and extended for the calculation of the relative sliding velocity vrel . Furthermore, the mandrel wear was calculated and visualized by using adapted MSC.SuperForm subroutines. To include the interactions between the workpiece and the tools a thermal–mechanical FEA with thermo-elastic tool components was carried out. Owing to the rotational symmetry of the workpiece and the tools a two-dimensional simulation model was used. This leads to a substantially smaller solution time because of a major reduction of the number of degrees of freedom compared to a three dimensional simulation. The FE model is shown in Fig. 5 with the corresponding initial temperatures of each component for the simulation. Every component was represented by a contact body. The initial temperatures were extracted from the thermograph shot of the forging process after the 80th forging cycle. These temperatures were defined as steady state temperatures at the end of a forging cycle, because after the 80th cycle there was no significant increase in tool temperature detectable. The workpiece material 1.0503 (C45) properties were taken from the data base of the used commercial FE-code. Since, this data base did not contained the appropriate properties for the tool material, these properties were extracted from [9].
312
B.-A. Behrens, F. Schaefer / Journal of Materials Processing Technology 167 (2005) 309–315
Fig. 6. Temperature distribution during and at the end of the forming process. Fig. 5. Components and initial temperature of the FE model.
The temperature dependency of the material properties was considered. Additional simulation parameters are shown in Table 1. All process stages of a forging cycle were included in the simulation. The single process stages and their duration can be found in Fig. 2. During forging the interface layer between workpiece and tools is of special interest for the numerical description of the mechanical and thermal interactions in this area. For this purpose, the contact heat transfer coefficient and the friction ˙ between two concoefficient are necessary. The heat flow Q tact bodies with the temperature ϑ1 and ϑ2 is described by the following equation: ˙ = hA(ϑ2 − ϑ1 ) Q
Due to the fact that there is no universal approach for a correct description of friction during a forging process as a result of the changing contact surface, an established constant friction coefficient was used. To allow an accurate heat transfer from the workpiece to the tools, the element edge length at the workpiece surface has to be smaller than at the tool surface. With a local refinement of the FE-mesh in this contact area it was possible to simulate the interactions between workpiece and tools accurately. In Fig. 5, the mesh at the region of the mandrel is shown. Fig. 6 shows the calculated temperature distribution in the tools and the workpiece at the end of the forming stage. It can be seen, that the highest temperatures appears in the mandrel radius.
(1)
In this equation, h is the contact heat transfer coefficient and A the contact surface. The contact heat transfer is dependent on the temperature difference of the two bodies. Furthermore, there is a dependence of the contact heat transfer coefficient on the contact pressure between the two bodies. Investigations regarding the contact heat transfer coefficient in hot forging processes were performed by Naegele [10]. Based on this investigations, the contact heat transfer coefficients (Table 1) was selected. The contact pressure dependency of the coefficient was neglected during the forging process.
4. Calculation of wear
Table 1 Additional simulation parameters
h =
Parameter Heat transfer coefficient, h (forge) (W/mm2 K) Heat transfer coefficient, h (lie before and after forging) (W/mm2 K) Friction factor Film coefficient to environment (workpiece) (W/mm2 K) Film coefficient to environment (tools) (W/mm2 K) Film coefficient to environment during lubrication (tools) (W/mm2 K) Environment temperature (◦ C)
For the estimation of tool wear the Archard wear model [11] with a variable hardness was used. It is well suitable in connection with a finite-element-analysis, since all needed parameters, like contact normal stress σ N and relative sliding velocity vrel can be calculated during the simulation of the considered forging process. The following equation represents the applied wear model: N k σN vrel t H(t, T )
(2)
inc=1
Magnitude 0.035 0.001 0.4 0.00025 0.0001 0.0015 25
where h is the wear depth in mm, H(t,T) the hardness in N/mm2 dependent from the process time and temperature and t is the duration of an increment in seconds of the FEA. For the calibration of the model according to experiments the factor k is used. The wear amount is accumulated over all increments of the forming stage of the forging cycle. Since, the hardness of the tools surface is not constant over the complete process a multiplication of the wear depth of one forging cycle with the number of desired cycles is not adequate. The hardness loss due to the tempering during several forging cycles has to be considered.
B.-A. Behrens, F. Schaefer / Journal of Materials Processing Technology 167 (2005) 309–315
To include the changing of hardness because of tempering effects the main tempering curve of the mandrel material 1.2356 (Fig. 7) was used. By using the main tempering curve and the tempering parameter P, it was possible to calculate the hardness at any tempering time. This connection was applied to estimate the hardness after several forging cycles. The tempering parameter results from the following equation [12]: P = T (a + lgtt )
(3)
In this formulation, T is the tempering temperature in Kelvin, tt the tempering time in hours and the parameter a is 20 for hot working steels. In order to estimate the tempering hardness after several forging cycles a constant temperature is needed. For this purpose, the equivalent temperature Teq according to Lee et al. [8] was introduced to consider the temperature gradient during the forging cycle. By using the following equation, the equivalent temperature Teq can be determined: Teq =
2Tmax + Tmin 3
(4)
In this equation, Tmax is the maximal temperature and Tmin is the minimal temperature during a forging cycle. By means of the main tempering curve the tempering hardness after several forging cycles at room temperature was estimated. Due to the fact, that a hardness decrease takes place at higher temperatures the hot hardness has to be considered for the prediction of wear. For determination of the hot hardness also the equivalent temperature Teq according to Lee et al. [8] was used. In Fig. 7, hot hardness curves of the used hot working steel 1.2365 at different tempering stages are shown. It can be seen, that the curves run nearly parallel. Since, within the considered 2000 forging cycles only small hardness losses are reached, a parallel movement of the hardness curves is acceptable. To estimate the tool wear at every mandrel node, which can contact the workpiece the temperature, the contact normal stress σ N and the relative sliding velocity vrel between workpiece and mandrel was written to a file. If there was no contact at one node σ N and vrel were zero. To calculate vrel at
Fig. 7. Main tempering curve of 1.2365 [13].
313
every contact node of the mandrel, the velocity of the workpiece at the corresponding location of the mandrel node was calculated. Then vrel has been computed since the velocity of workpiece and mandrel was known at the location of the mandrel nodes (Fig. 8). Finally, a short program was developed to calculate the tool wear. This program used the calculated temperature, contact normal stress σ N and relative sliding velocity vrel from the finite-element-analysis of the complete forging cycle. For each increment and every contact node of the mandrel the wear was calculated and summed up with the increment before. Past any cycle the determined wear amount was divided by the current hardness. Following the calculation of the hardness is described. First the equivalent temperature Teq of any contact node of the mandrel was calculated. Subsequently, the tempering hardness against the process time resulted from the process time obtained by multiplication of the number of cycles with the duration of one cycle. The tempering hardness was calculated by using the tempering parameter P of the corresponding temperature and process time and the main tempering curve approximated by a function. By applying the tempering parameter P to the main tempering curve the tempering hardness against the process time has been estimated. After each hour of process time, a recalculation of the tempering hardness at every mandrel contact node was done. The approximated hot hardness curves were applied to the calculated tempering hardness to determine the hardness for the wear estimation. For the calibration of the wear model according to the experimental results the parameter k was used. To determine the white layer a simulation of the forming process with a high level descritisation with an element edge length of 0.05 mm was carried out to represent the mandrel surface layer optimally. As austenitization temperature of the mandrel material a temperature of 740 ◦ C according to Walter [6] was assumed. Above this temperature a forma-
Fig. 8. Hot hardness curves of 1.2365 [14] at different tempering stages.
314
B.-A. Behrens, F. Schaefer / Journal of Materials Processing Technology 167 (2005) 309–315
Hence, the mechanical and thermal loadings differ over the forging cycles. For a correct wear estimation this effect have to include in the simulation of the forging process to calculate the accurate temperature, contact normal stress σ N and relative sliding velocity vrel . By using these parameters from the FE-simulation with the original geometry of the mandrel the calibrated wear model is only valid for the number of forging cycles used for the calibration. Fig. 9. White layer at the radius of the mandrel.
5. Conclusions tion of a white layer was expected. By using this criterion in the simulation a white layer was detected only at the radius of the mandrel (Fig. 9). For the estimation of mandrel wear the nodes of the wear simulation model located in the white layer zone were assigned with a higher hardness of 700 HV in accordance with Walter [6]. According to the experiments and Walter [4] it was assumed, that after 450 forging cycles the white layer is completely worn out. Fig. 10 shows the wear profiles of the worn out mandrels after 2000 forging cycles and the estimated wear profile each normalized to the maximum value of the corresponding profile. A good qualitative correlation between measurement and wear estimation can be detected. Areas with only less wear and with maximal wear are mirrored well. Only in the range of plastic deformation there is a significant difference between measurement and estimation of wear since plastic deformation is not covered by the wear simulation model. On the basis of Fig. 10, it becomes clear that the Archard wear model is able to predict the qualitative wear in forging. This wear model includes the essential macroscopic parameters, which significantly influence the tool wear. By using the factor k an adjustment of the wear model to the experiments is possible. Within the considered forging process the contact conditions change at the radius of the mandrel due to the wear.
In hot forging the abrasive wear is the major cause of failure of tools, therefore, the estimation of wear is of high importance to ensure an optimized process design. The Archard wear model was used for the estimation of tool wear. Since, this model can be applied to different forging processes it had to be adjusted to the considered hot forging process. Therefore, forging tests with closed tools was performed to observe the wear and to provide a basis for estimation of tool wear by means of the FEA. It was found out that the changing contact condition at the radius of the mandrel has an essential influence on the wear progress. To estimate the tool wear the relevant parameters for the Archard wear model were computed with the aid of the finite-element-method. The considered forging process with all process stages was represented by a finite-element model to determine the correct temperature distribution over the whole cycle. Furthermore, the contact normal stress σ N and the relative sliding velocity vrel between workpiece and mandrel was calculated. Of special interest for the wear estimation in hot forging is the hardness of the tool surface layer. On this account the hardness increase due to re-hardening at the radius of the mandrel and the hardness loss as a result of tempering were considered in the prediction of tool wear. Finally, to the maximal value normalized wear profiles after 2000 forging cycles from estimation and experiments were compared. A good agreement between the two curves was found, so that the wear model is able to predict the qualitative wear trend. Since, the changing of the contact conditions at the radius of the mandrel are not considered, the calibrated wear model is only valid for the number of forging cycles used for the calibration. Therefore, further improvements of the simulation model and an adaptation of the wear model are necessary.
Acknowledgments
Fig. 10. Wear profiles normalized to maximal value of forging test and simulation after 2000 cycles.
The presented work has been developed within the Collaborative Research Centre 489 “Prozesskette zur Herstellung praezionsgeschmiedeter Hochleistungs-bauteile” supported by the “Deutsche Forschungs-gemeinschaft (DFG-German Research Foundation)”.
B.-A. Behrens, F. Schaefer / Journal of Materials Processing Technology 167 (2005) 309–315
References [1] J.H. Kang, I.W. Park, et al., A study on a die wear model considering thermal softening: (I) application of the suggested wear model, J. Mater. Process. Technol. 94 (1999) 183–188. [2] D. Heinemeyer, Untersuchungen zur Frage der Haltbarkeit von Schmiedegesenken, Dr.-Ing. -Thesis, Hannover, 1976. [3] L. Cser, M. Geiger, et al., Tool life and tool quality in bulk metal forming, Proc. Inst. Mech. Eng. 207 (1993) 223–239. [4] E. Doege, P. Groche, Th. Bobke, Application of adhesion theory to friction and wear processes, in: Proceedings of the Third International Conference on Technology of Plasticity, vol. 1, Kyoto, July 1990, pp. 27–32. [5] T. Bobke, Randschichtphaenomene bei Verschleiss-vorgaengen an Gesenkschmiedewerkzeugen, Dr.-Ing. -thesis, Hannover, 1991. [6] S. Walter, Beitrag zu den Werkstoffversagens-mechanismen beim Gesenkschmieden, Dr.-Ing. -thesis, Hannover, 1999. [7] J.H. Kang, I.W. Park, et al., A study on a die wear model considering thermal softening: (I) construction of the wear model, J. Mater. Process. Technol. 96 (1999) 53–58.
315
[8] H.C. Lee, B.M. Kim, et al., Estimation of die service life in hot forging considering lubricants and surface treatments, Proc. Inst. Mech. Eng. 217 (2003) 1011–1022. [9] I. Schruff, Zusammenstellung der Eigenschaften und Werkstoffkennwerte der Warmarbeitsstaehle X38CrMoV51 (Thyrotherm 2343), X40CrMo51 (Thyrotherm 2344), X32CrMoV33 (Thyrotherm 2365) und X38CrMoV53 (Thyrotherm 2367), Thyssen Edelstahl Technische Berichte, 15, Band, Heft 2, 1989, pp. 70–81. [10] H. Naegele, Simulation des Herstellungsprozesses praezisionsgeschmiedeter Zahnraeder mit der Finite-Elemente Methode, Dr.-Ing. -thesis, Hannover, 1995. [11] J.F. Archard, Contact and rubbing of flat surfaces, J. Appl. Phys. (1953) 981–988. [12] D. Liedtke, R. Joensson, Waermebehandlung: Grundlagen und Anwendungen f¨ur Eisenwerkstoffe, 4. durchges. Aufl., expert-Verlag, Renningen-Malsheim, 2000. [13] N.N. Boehler, Edelstahlhandbuch 2.1 Version 2.1e, Boehler Edelstahl GMBH. [14] R. Schneider, Verschleißvorausbestimmung bei Gesenkschmiedewerkzeugen, Drahtwelt 11-1984, 1984, pp. 299–302.
Prediction of wear in hot forging tools by means of finite-element-analysis B.-A. Behrens, F. Schaefer ∗ Institute of Metal Forming and Metal Forming Machine Tools, University of Hanover, Schoenebecker Allee 2, 30823 Garbsen, Germany
Abstract The intention of the work presented in this paper is the estimation of abrasive tool wear, as the major cause of failure of tools used for hot forging. Experiments are carried out to determine the wear amount after several numbers of forging cycles. For tool wear estimation, the analysed forging process in consideration of all process stages is represented with a finite-element model to compute the wear relevant parameters. A separate program is developed to calculate the tool wear by using the Archard wear model taking into account the hardness change of the tool surface layer with increasing number of forging cycles. In the end, the applied wear model is verified by comparing with the experimental results. © 2005 Published by Elsevier B.V. Keywords: FEM-simulation; Hot forging; Tool wear
1. Introduction Hot forging with temperatures between 900 and 1250 ◦ C has a high importance for the manufacturing of complex components. Due to high workpiece temperatures, high plastic strains are possible. At the same time, the forming forces are lower compared to warm and cold forming. It is especially suitable for high volume production of highly stressed components. Hence, the knowledge of the tool life time is of particular importance, in order to insure a high efficiency of the forging process [1]. The typical causes of failure of tools used for hot forging are wear, mechanical crack initiation, thermal crack initiation and plastic deformation. About 70% of all failures of hot forging tools are caused by wear [2,3]. A lot of investigations on tool wear in hot forging have shown that the hardness of the tool surface layer plays an important role for abrasive tool wear [4–6]. Due to this, the major effects, which influence the hardness of the tool material will be briefly described in the following. The high workpiece temperatures and high contact pressures during the forging process lead to large mechanical and thermal ∗
Corresponding author. Fax: +49 511 762 3007. E-mail address: [email protected] (F. Schaefer).
0924-0136/$ – see front matter © 2005 Published by Elsevier B.V. doi:10.1016/j.jmatprotec.2005.06.057
tool loadings. As a result of the thermal loadings a hardness loss of the tool material in the surface layer takes place, which significantly influences the wear behaviour of the tool material [4,5]. This hardness loss is induced by the high tool temperatures during the whole forging process, which cause the tempering of the tool surface layer [5,6]. Furthermore, in some areas of the tools where an especially high heat transfer from the workpiece occurs, the austenitization temperature of tool material can be reached during the forming process [6]. After the contact release between workpiece and tools, the tool surface cools down very fast supported by the cooling lubrication, so that a re-hardening can happen. The re-hardened layer, also called white layer, shows a higher hardness than the base material of the tools [5,6]. This phenomenon only appears during the first 10 forging cycles [6]. Additionally to the previous described phenomenon the normal hardness loss at higher temperatures has to be observed. In addition the contact normal stress σ N at the tool surface and the relative sliding velocity vrel between workpiece and tools are important factors for wear [5]. Several researchers used a wear model based on the Archard wear model to calculate the tool wear only taking into account the hardness loss due to the tempering of the tool material with increasing number of forging cycles [1,7,8]. Hence, the aim of this paper is to predict the tool
310
B.-A. Behrens, F. Schaefer / Journal of Materials Processing Technology 167 (2005) 309–315
wear at forging processes in consideration of all previously described hardness changes in the tool surface layer. Furthermore, all process stages of a forging cycle are included in the calculation of the tool temperatures. Within the scope of this paper a forging process in a closed die without flash is considered. To achieve the objective, experiments were carried out first to obtain the wear experimentally. For the estimation of tool wear, the forging process with all stages is represented with a finite-element model to compute the tool temperature, the relative sliding velocity vrel between workpiece and tools and the contact normal stress σ N at the tool surface. These parameters are applied for the calculation of the wear amount by using the Archard wear model. The verification of the wear model is realised by using the experimental determined wear. Fig. 2. Process stages of a forging cycle of the considered forging process.
2. Experiments For the experimental determination of tool wear a forging process in a closed die was performed. The forging tests with a cycle time of 12 s were done under standard forging conditions using sheared raw parts from 1.0503 (C45) with preheating temperature of 1250 ◦ C. In Fig. 1, the most important components of the tooling system and the geometry of the final part are shown. Due to the fact, that the highest mechanical loading in the forging process appears at the mandrel this component was of major interest in the experimental investigations. Furthermore, the mandrel is exposed to very high thermal loadings, because it always moves into the hot material in the core of the slug. Because of the high thermal and mechanical loadings the highest wear occur at the mandrel. Hence, the wear measurements are only done at the mandrel. For an optimal realisation of the forging tests the mandrel was changed after 500, 1000 and 2000 forging cycles. The tools were made of the hot working steel 1.2365 (32CrMoV12–28) with a hardness of 550 HV (vickers hardness). To reach this hardness a heat treatment consisting of hardening and two tempering processes with a duration of 1 h was carried out.
Fig. 1. Tooling system of the considered forging process.
The forging tests were performed by using an automated press. This automated facility consists of an eccentric press with a nominal force of 3150 kN, an induction furnace, a manipulator and an installation for lubrication. First, the slug was heated up to 1250 ◦ C by an induction furnace. After this, the manipulator inserted the slug to the ejector. Then the part was forged and finally extracted by the manipulator. At the end of a forging cycle, the lubrication of the tools with a graphite based lubrication medium was performed. For the estimation of tool wear the process time is very important. Due to this, a movie of some forging cycles was created to separate the duration of the single process steps illustrated in Fig. 2. In order to verify the simulation model according to the temperature distribution a thermograph movie was also generated during the first 100 forging cycles. Since, the punch and the mandrel were masked from the closing plate only the ejector and the die were considered in the thermograph shot. The die and ejector surface temperature at the end of the 80th forging cycle was determined as steady state temperature at the end of a forging cycle for the simulation. After the forging tests wear measurements at the worn out mandrels were performed. As reference geometry, the measured geometry of the corresponding original mandrel was used. In Fig. 3, the original and worn out geometries after 500, 1000 and 2000 forging cycles are faced. Fig. 3 makes clear, as expected, that the highest wear appears at the radius of the mandrel, due to very high thermal and mechanical loadings at this location. Furthermore, the high sliding velocity of the workpiece material causes noticeable wear in this area. Additionally to wear, at the flank of the mandrel after 500 and 1000 forging cycles an extra amount of material can be seen. This amount is effected by plastic deformation of the mandrel material. After 1000 forging cycles the additional amount at the flank of the mandrel is minimized and after 2000 cycles it is nearly completely removed in consequence of abrasive wear. Fig. 4 shows the wear amount
B.-A. Behrens, F. Schaefer / Journal of Materials Processing Technology 167 (2005) 309–315
311
cycles. Due to the enlargement of the radius the effects of the hardness increase as a result of the generation of a white layer and the hardness decrease in consequence of tempering are not visible directly at the wear profile of the radius. If there would be no significant difference between the mechanical and thermal loads during all forging cycles the wear increase has to enlarge with increasing numbers of forging cycles since a hardness loss due to tempering takes place. Walter [4] observed at a similar geometry and process that only at the radius a white layer is generated, as the highest temperatures appeared at this location. In this research work, a thickness of the white layer of nearly 0.1 mm was found out. At the flank of the mandrel just small wear occur due to the smaller mechanical loadings compared to the front surface. Only in the area of plastic deformed material of the mandrel a significant wear is visible as a result of the high mechanical and thermal loadings.
3. Simulation of the forging process
Fig. 3. Facing of original and worn out geometries of the mandrel after 500, 1000 and 2000 forging cycles.
at the front face and the flank of one half of the mandrel in detail. Due to the rotational symmetry of the forging process only one half of the mandrel is considered. Because of the enlargement of the mandrel radius (Fig. 3) induced by wear and plastic deformation during the forging cycles the mechanical as well as the thermal loadings are reduced at the radius. Hence, the increase of the maximal wear at the radius declines over the complete forging process. This means, that the wear at the radius after the first 500 cycles is larger than the wear between 500 and 1000 cycles. The same can be observed between 1000 and 2000 forging
Fig. 4. Wear profiles at the mandrel after 500, 1000 and 2000 forging cycles.
The finite-element-analysis (FEA) is an effective tool to predict die fill, residual stresses and forming forces. In addition, the FEA plays a decisive role in construction and optimization of forging tools. In order to analyze the thermal and mechanical loadings in the forging tools the considered forging process was represented by an finite-element (FE) model. The FEA was performed with the commercial FE-Code MSC.SuperForm. An advantage of MSC.SuperForm is, that the user is enabled by using existing subroutines to solve his specific problems. In this case, existing subroutines were used and extended for the calculation of the relative sliding velocity vrel . Furthermore, the mandrel wear was calculated and visualized by using adapted MSC.SuperForm subroutines. To include the interactions between the workpiece and the tools a thermal–mechanical FEA with thermo-elastic tool components was carried out. Owing to the rotational symmetry of the workpiece and the tools a two-dimensional simulation model was used. This leads to a substantially smaller solution time because of a major reduction of the number of degrees of freedom compared to a three dimensional simulation. The FE model is shown in Fig. 5 with the corresponding initial temperatures of each component for the simulation. Every component was represented by a contact body. The initial temperatures were extracted from the thermograph shot of the forging process after the 80th forging cycle. These temperatures were defined as steady state temperatures at the end of a forging cycle, because after the 80th cycle there was no significant increase in tool temperature detectable. The workpiece material 1.0503 (C45) properties were taken from the data base of the used commercial FE-code. Since, this data base did not contained the appropriate properties for the tool material, these properties were extracted from [9].
312
B.-A. Behrens, F. Schaefer / Journal of Materials Processing Technology 167 (2005) 309–315
Fig. 6. Temperature distribution during and at the end of the forming process. Fig. 5. Components and initial temperature of the FE model.
The temperature dependency of the material properties was considered. Additional simulation parameters are shown in Table 1. All process stages of a forging cycle were included in the simulation. The single process stages and their duration can be found in Fig. 2. During forging the interface layer between workpiece and tools is of special interest for the numerical description of the mechanical and thermal interactions in this area. For this purpose, the contact heat transfer coefficient and the friction ˙ between two concoefficient are necessary. The heat flow Q tact bodies with the temperature ϑ1 and ϑ2 is described by the following equation: ˙ = hA(ϑ2 − ϑ1 ) Q
Due to the fact that there is no universal approach for a correct description of friction during a forging process as a result of the changing contact surface, an established constant friction coefficient was used. To allow an accurate heat transfer from the workpiece to the tools, the element edge length at the workpiece surface has to be smaller than at the tool surface. With a local refinement of the FE-mesh in this contact area it was possible to simulate the interactions between workpiece and tools accurately. In Fig. 5, the mesh at the region of the mandrel is shown. Fig. 6 shows the calculated temperature distribution in the tools and the workpiece at the end of the forming stage. It can be seen, that the highest temperatures appears in the mandrel radius.
(1)
In this equation, h is the contact heat transfer coefficient and A the contact surface. The contact heat transfer is dependent on the temperature difference of the two bodies. Furthermore, there is a dependence of the contact heat transfer coefficient on the contact pressure between the two bodies. Investigations regarding the contact heat transfer coefficient in hot forging processes were performed by Naegele [10]. Based on this investigations, the contact heat transfer coefficients (Table 1) was selected. The contact pressure dependency of the coefficient was neglected during the forging process.
4. Calculation of wear
Table 1 Additional simulation parameters
h =
Parameter Heat transfer coefficient, h (forge) (W/mm2 K) Heat transfer coefficient, h (lie before and after forging) (W/mm2 K) Friction factor Film coefficient to environment (workpiece) (W/mm2 K) Film coefficient to environment (tools) (W/mm2 K) Film coefficient to environment during lubrication (tools) (W/mm2 K) Environment temperature (◦ C)
For the estimation of tool wear the Archard wear model [11] with a variable hardness was used. It is well suitable in connection with a finite-element-analysis, since all needed parameters, like contact normal stress σ N and relative sliding velocity vrel can be calculated during the simulation of the considered forging process. The following equation represents the applied wear model: N k σN vrel t H(t, T )
(2)
inc=1
Magnitude 0.035 0.001 0.4 0.00025 0.0001 0.0015 25
where h is the wear depth in mm, H(t,T) the hardness in N/mm2 dependent from the process time and temperature and t is the duration of an increment in seconds of the FEA. For the calibration of the model according to experiments the factor k is used. The wear amount is accumulated over all increments of the forming stage of the forging cycle. Since, the hardness of the tools surface is not constant over the complete process a multiplication of the wear depth of one forging cycle with the number of desired cycles is not adequate. The hardness loss due to the tempering during several forging cycles has to be considered.
B.-A. Behrens, F. Schaefer / Journal of Materials Processing Technology 167 (2005) 309–315
To include the changing of hardness because of tempering effects the main tempering curve of the mandrel material 1.2356 (Fig. 7) was used. By using the main tempering curve and the tempering parameter P, it was possible to calculate the hardness at any tempering time. This connection was applied to estimate the hardness after several forging cycles. The tempering parameter results from the following equation [12]: P = T (a + lgtt )
(3)
In this formulation, T is the tempering temperature in Kelvin, tt the tempering time in hours and the parameter a is 20 for hot working steels. In order to estimate the tempering hardness after several forging cycles a constant temperature is needed. For this purpose, the equivalent temperature Teq according to Lee et al. [8] was introduced to consider the temperature gradient during the forging cycle. By using the following equation, the equivalent temperature Teq can be determined: Teq =
2Tmax + Tmin 3
(4)
In this equation, Tmax is the maximal temperature and Tmin is the minimal temperature during a forging cycle. By means of the main tempering curve the tempering hardness after several forging cycles at room temperature was estimated. Due to the fact, that a hardness decrease takes place at higher temperatures the hot hardness has to be considered for the prediction of wear. For determination of the hot hardness also the equivalent temperature Teq according to Lee et al. [8] was used. In Fig. 7, hot hardness curves of the used hot working steel 1.2365 at different tempering stages are shown. It can be seen, that the curves run nearly parallel. Since, within the considered 2000 forging cycles only small hardness losses are reached, a parallel movement of the hardness curves is acceptable. To estimate the tool wear at every mandrel node, which can contact the workpiece the temperature, the contact normal stress σ N and the relative sliding velocity vrel between workpiece and mandrel was written to a file. If there was no contact at one node σ N and vrel were zero. To calculate vrel at
Fig. 7. Main tempering curve of 1.2365 [13].
313
every contact node of the mandrel, the velocity of the workpiece at the corresponding location of the mandrel node was calculated. Then vrel has been computed since the velocity of workpiece and mandrel was known at the location of the mandrel nodes (Fig. 8). Finally, a short program was developed to calculate the tool wear. This program used the calculated temperature, contact normal stress σ N and relative sliding velocity vrel from the finite-element-analysis of the complete forging cycle. For each increment and every contact node of the mandrel the wear was calculated and summed up with the increment before. Past any cycle the determined wear amount was divided by the current hardness. Following the calculation of the hardness is described. First the equivalent temperature Teq of any contact node of the mandrel was calculated. Subsequently, the tempering hardness against the process time resulted from the process time obtained by multiplication of the number of cycles with the duration of one cycle. The tempering hardness was calculated by using the tempering parameter P of the corresponding temperature and process time and the main tempering curve approximated by a function. By applying the tempering parameter P to the main tempering curve the tempering hardness against the process time has been estimated. After each hour of process time, a recalculation of the tempering hardness at every mandrel contact node was done. The approximated hot hardness curves were applied to the calculated tempering hardness to determine the hardness for the wear estimation. For the calibration of the wear model according to the experimental results the parameter k was used. To determine the white layer a simulation of the forming process with a high level descritisation with an element edge length of 0.05 mm was carried out to represent the mandrel surface layer optimally. As austenitization temperature of the mandrel material a temperature of 740 ◦ C according to Walter [6] was assumed. Above this temperature a forma-
Fig. 8. Hot hardness curves of 1.2365 [14] at different tempering stages.
314
B.-A. Behrens, F. Schaefer / Journal of Materials Processing Technology 167 (2005) 309–315
Hence, the mechanical and thermal loadings differ over the forging cycles. For a correct wear estimation this effect have to include in the simulation of the forging process to calculate the accurate temperature, contact normal stress σ N and relative sliding velocity vrel . By using these parameters from the FE-simulation with the original geometry of the mandrel the calibrated wear model is only valid for the number of forging cycles used for the calibration. Fig. 9. White layer at the radius of the mandrel.
5. Conclusions tion of a white layer was expected. By using this criterion in the simulation a white layer was detected only at the radius of the mandrel (Fig. 9). For the estimation of mandrel wear the nodes of the wear simulation model located in the white layer zone were assigned with a higher hardness of 700 HV in accordance with Walter [6]. According to the experiments and Walter [4] it was assumed, that after 450 forging cycles the white layer is completely worn out. Fig. 10 shows the wear profiles of the worn out mandrels after 2000 forging cycles and the estimated wear profile each normalized to the maximum value of the corresponding profile. A good qualitative correlation between measurement and wear estimation can be detected. Areas with only less wear and with maximal wear are mirrored well. Only in the range of plastic deformation there is a significant difference between measurement and estimation of wear since plastic deformation is not covered by the wear simulation model. On the basis of Fig. 10, it becomes clear that the Archard wear model is able to predict the qualitative wear in forging. This wear model includes the essential macroscopic parameters, which significantly influence the tool wear. By using the factor k an adjustment of the wear model to the experiments is possible. Within the considered forging process the contact conditions change at the radius of the mandrel due to the wear.
In hot forging the abrasive wear is the major cause of failure of tools, therefore, the estimation of wear is of high importance to ensure an optimized process design. The Archard wear model was used for the estimation of tool wear. Since, this model can be applied to different forging processes it had to be adjusted to the considered hot forging process. Therefore, forging tests with closed tools was performed to observe the wear and to provide a basis for estimation of tool wear by means of the FEA. It was found out that the changing contact condition at the radius of the mandrel has an essential influence on the wear progress. To estimate the tool wear the relevant parameters for the Archard wear model were computed with the aid of the finite-element-method. The considered forging process with all process stages was represented by a finite-element model to determine the correct temperature distribution over the whole cycle. Furthermore, the contact normal stress σ N and the relative sliding velocity vrel between workpiece and mandrel was calculated. Of special interest for the wear estimation in hot forging is the hardness of the tool surface layer. On this account the hardness increase due to re-hardening at the radius of the mandrel and the hardness loss as a result of tempering were considered in the prediction of tool wear. Finally, to the maximal value normalized wear profiles after 2000 forging cycles from estimation and experiments were compared. A good agreement between the two curves was found, so that the wear model is able to predict the qualitative wear trend. Since, the changing of the contact conditions at the radius of the mandrel are not considered, the calibrated wear model is only valid for the number of forging cycles used for the calibration. Therefore, further improvements of the simulation model and an adaptation of the wear model are necessary.
Acknowledgments
Fig. 10. Wear profiles normalized to maximal value of forging test and simulation after 2000 cycles.
The presented work has been developed within the Collaborative Research Centre 489 “Prozesskette zur Herstellung praezionsgeschmiedeter Hochleistungs-bauteile” supported by the “Deutsche Forschungs-gemeinschaft (DFG-German Research Foundation)”.
B.-A. Behrens, F. Schaefer / Journal of Materials Processing Technology 167 (2005) 309–315
References [1] J.H. Kang, I.W. Park, et al., A study on a die wear model considering thermal softening: (I) application of the suggested wear model, J. Mater. Process. Technol. 94 (1999) 183–188. [2] D. Heinemeyer, Untersuchungen zur Frage der Haltbarkeit von Schmiedegesenken, Dr.-Ing. -Thesis, Hannover, 1976. [3] L. Cser, M. Geiger, et al., Tool life and tool quality in bulk metal forming, Proc. Inst. Mech. Eng. 207 (1993) 223–239. [4] E. Doege, P. Groche, Th. Bobke, Application of adhesion theory to friction and wear processes, in: Proceedings of the Third International Conference on Technology of Plasticity, vol. 1, Kyoto, July 1990, pp. 27–32. [5] T. Bobke, Randschichtphaenomene bei Verschleiss-vorgaengen an Gesenkschmiedewerkzeugen, Dr.-Ing. -thesis, Hannover, 1991. [6] S. Walter, Beitrag zu den Werkstoffversagens-mechanismen beim Gesenkschmieden, Dr.-Ing. -thesis, Hannover, 1999. [7] J.H. Kang, I.W. Park, et al., A study on a die wear model considering thermal softening: (I) construction of the wear model, J. Mater. Process. Technol. 96 (1999) 53–58.
315
[8] H.C. Lee, B.M. Kim, et al., Estimation of die service life in hot forging considering lubricants and surface treatments, Proc. Inst. Mech. Eng. 217 (2003) 1011–1022. [9] I. Schruff, Zusammenstellung der Eigenschaften und Werkstoffkennwerte der Warmarbeitsstaehle X38CrMoV51 (Thyrotherm 2343), X40CrMo51 (Thyrotherm 2344), X32CrMoV33 (Thyrotherm 2365) und X38CrMoV53 (Thyrotherm 2367), Thyssen Edelstahl Technische Berichte, 15, Band, Heft 2, 1989, pp. 70–81. [10] H. Naegele, Simulation des Herstellungsprozesses praezisionsgeschmiedeter Zahnraeder mit der Finite-Elemente Methode, Dr.-Ing. -thesis, Hannover, 1995. [11] J.F. Archard, Contact and rubbing of flat surfaces, J. Appl. Phys. (1953) 981–988. [12] D. Liedtke, R. Joensson, Waermebehandlung: Grundlagen und Anwendungen f¨ur Eisenwerkstoffe, 4. durchges. Aufl., expert-Verlag, Renningen-Malsheim, 2000. [13] N.N. Boehler, Edelstahlhandbuch 2.1 Version 2.1e, Boehler Edelstahl GMBH. [14] R. Schneider, Verschleißvorausbestimmung bei Gesenkschmiedewerkzeugen, Drahtwelt 11-1984, 1984, pp. 299–302.