**3. Design of deep drawing tools produced by rapid tooling technologies**

In all industries, customized and tailored design is gaining importance, and therefore small series production has increased in the last decade. The increasing number of variant types and also the decreasing number of the same parts affect the manufacturing processes deeply. For instance, metal forming is known to be economical for large series production. One of the main factors affecting the cost of the metal forming process is tool costs. Conventional methods and materials

#### *Design and Manufacturing*

to produce forming tools result in certain disadvantages: Not only the production process takes too much time, but also the whole process is expensive.

Therefore, rapid tooling methodologies are gaining importance also for metal forming technologies in recent years. Rapid tooling methods offer indispensable advantages in time, though the cost of the tool must be optimized according to the number of parts to be produced, material couple to be chosen, and the production methodology.

To optimize the part quality, the method, and the cost prediction, a methodology to predict the most appropriate rapid tooling method as well as the prediction of the tool life becomes indispensable.

As the abrasive wear on the metal forming tools increases, it is getting more and more important to predict the tool wear and the life of the tool, when the tool is in design stage. By this way the most appropriate tool materials, design, and maintenance periods can be planned.

First a methodology to ensure that the chosen rapid tooling technique and material are appropriate to produce the part must be introduced. This includes the dimensional accuracy, mechanical properties, the surface quality of the rapid tooling process, the related production process parameters like deformation of the tool, temperature distribution, and a determination of tribologically matching material couple and surface properties important factors can also be seen in **Figure 7**.


#### **Figure 7.**

*The main factors affecting the choice of the rapid tooling material and production method.*

**99**

**Figure 10.**

**Figure 9.**

*deep drawing geometry [14].*

*Utilization of Additive Manufacturing to Produce Tools DOI: http://dx.doi.org/10.5772/intechopen.89804*

ing approach is offered.

methodology can be found in [13].

als are generally very susceptible to abrasive wear.

in **Figure 8** [13].

Then the number of parts, which can be produced with this rapidly produced tool, must be predicted. In order to predict the operation time of a tool, the follow-

A metal forming process is economically advantageous, if and only if the tool costs can be controlled and predicted. Forecasts of the number of parts to be produced with the tools are of highest advantage. Therefore, in the PhD thesis, a method to predict tool wear is established and validated and verified an approach is depicted

This approach is tested with a simple cup deep-drawing geometry. The die is made of rapid tooling, whereas the punch and blankholder are produced by conventional methods out of tool steel as given in **Figure 9**. For that reason, the punch and blankholder are modeled as rigid body, whereas the die is modeled with 3D deformable elements.

In order to enable testing, a follow-on tool is designed, and an optical and tactile

The contact pressure distribution is obtained by finite element methodology as depicted in **Figure 10**. As the die material is made out of rapid tooling, these materi-

*(a) Schematic presentation of deep drawing of a cup geometry. (b) a quarter model of a simplified circular* 

*Comparison of wear behavior of different rapidly produced tools (PA220 (PA-SLS), ZAMAK (SLA + casting), LaserFormA6 (SLS RapidSteel) vs. tool steel (conventional method) [14].*

measurement methodology is determined. The die made out of rapid tooling is measured at determined intervals, and the wear propagation over time is measured. Four different locations are measured, and the experiments are conducted up to five times. The details of the repeatability and reliability of the data and measurement

#### **Figure 8.**

*Approach to predict the wear on forming tools.*

*Utilization of Additive Manufacturing to Produce Tools DOI: http://dx.doi.org/10.5772/intechopen.89804*

*Design and Manufacturing*

of the tool life becomes indispensable.

nance periods can be planned.

to produce forming tools result in certain disadvantages: Not only the production

to be produced, material couple to be chosen, and the production methodology.

Therefore, rapid tooling methodologies are gaining importance also for metal forming technologies in recent years. Rapid tooling methods offer indispensable advantages in time, though the cost of the tool must be optimized according to the number of parts

To optimize the part quality, the method, and the cost prediction, a methodology to predict the most appropriate rapid tooling method as well as the prediction

As the abrasive wear on the metal forming tools increases, it is getting more and more important to predict the tool wear and the life of the tool, when the tool is in design stage. By this way the most appropriate tool materials, design, and mainte-

First a methodology to ensure that the chosen rapid tooling technique and material are appropriate to produce the part must be introduced. This includes the dimensional accuracy, mechanical properties, the surface quality of the rapid tooling process, the related production process parameters like deformation of the tool, temperature distribution, and a determination of tribologically matching material couple and surface properties important factors can also be seen in **Figure 7**.

*The main factors affecting the choice of the rapid tooling material and production method.*

process takes too much time, but also the whole process is expensive.

**98**

**Figure 8.**

**Figure 7.**

*Approach to predict the wear on forming tools.*

Then the number of parts, which can be produced with this rapidly produced tool, must be predicted. In order to predict the operation time of a tool, the following approach is offered.

A metal forming process is economically advantageous, if and only if the tool costs can be controlled and predicted. Forecasts of the number of parts to be produced with the tools are of highest advantage. Therefore, in the PhD thesis, a method to predict tool wear is established and validated and verified an approach is depicted in **Figure 8** [13].

This approach is tested with a simple cup deep-drawing geometry. The die is made of rapid tooling, whereas the punch and blankholder are produced by conventional methods out of tool steel as given in **Figure 9**. For that reason, the punch and blankholder are modeled as rigid body, whereas the die is modeled with 3D deformable elements.

In order to enable testing, a follow-on tool is designed, and an optical and tactile measurement methodology is determined. The die made out of rapid tooling is measured at determined intervals, and the wear propagation over time is measured. Four different locations are measured, and the experiments are conducted up to five times. The details of the repeatability and reliability of the data and measurement methodology can be found in [13].

The contact pressure distribution is obtained by finite element methodology as depicted in **Figure 10**. As the die material is made out of rapid tooling, these materials are generally very susceptible to abrasive wear.

#### **Figure 9.**

*(a) Schematic presentation of deep drawing of a cup geometry. (b) a quarter model of a simplified circular deep drawing geometry [14].*

#### **Figure 10.**

*Comparison of wear behavior of different rapidly produced tools (PA220 (PA-SLS), ZAMAK (SLA + casting), LaserFormA6 (SLS RapidSteel) vs. tool steel (conventional method) [14].*

#### *Design and Manufacturing*

The key technology for predicting the development of wear in metal forming tools is numerical simulation. In forming applications, a wear is commonly described using models based on contact mechanics, the most important one being the Archard wear equation. Here the parameters affecting the wear are contact pressure, sliding distance, hardness, and a tribological constant.

With the offered methodology, the wear depth at each location at each punch stroke can be predicted. **Figure 11** depicts as an example a predicted vs. measured die radius wear rate after 10,000 punch strokes.

The **Figure 12** shows the wear rate of different dies produced by AM technologies, measured at different time intervals. As expected all rapidly produced tools have higher wear, i.e., shorter operation times. LaserFormA6 a kind of stainless

**Figure 11.**

*Contact pressure obtained by finite element simulation [14].*

**Figure 12.** *Measured wear depth in the profile (gray) compared to the simulation results of the same location (black) [14].*

**101**

*Utilization of Additive Manufacturing to Produce Tools DOI: http://dx.doi.org/10.5772/intechopen.89804*

time, i.e., number of parts, sliding distance, or wear work.

**4. Conclusion**

the method of production.

surface characteristics tribologically.

the time and cost constraints.

steel powder produced by SLS RapidSteel has the best wear resistance as expected, among others. Polyamide die has remarkably high wear rate which indicates that these are not appropriate for any series more than 100 parts. ZAMAK (zinc, aluminum, copper alloy) produced by casting into a SLA mold turns out to have a moderate wear resistance. All these trends obtained in these experiments are in accordance with the Archard theory, where the wear of the tool is indirectly proportional to the hardness of the die materials. Still, when investigated in detail their wear behavior, their elastic deformation, and tribological behavior affect the wear distribution over

This implies that according to the geometry and the number of the parts needed,

Customized and tailored design is gaining significance in all areas in the recent decades. The growing amount of variants and the declining amount of the same components also have a profound impact on the production procedures. Additive manufacturing is gaining importance due to many advantages, and in tool design it is used mostly due to its lead time advantage. Even if AM in tool production offers indispensable advantages in time, the cost of the tool must be optimized according to the number of parts to be produced, the couple of materials to be selected, and

A methodology for predicting the most suitable AM technique for tooling, as well as predicting the life of the tool, becomes indispensable in order to optimize the part quality, process, and price prediction. First, it must be guaranteed that the selected fast tooling method and material are suitable for producing the tool. This involves dimensional precision, mechanical characteristics, surface quality of the selected AM method, associated process parameters such as tool deformation and temperature distribution, and determination of corresponding material pair and

In this chapter a metal forming tool in a simplified round die geometry is chosen

as an example to predict the wear of a AM-produced tool, and the results show that the AM-produced tool has a shorter operation life, showing a wider range of lifetime depending on the AM technique and the tool material which are used. From these results it can be concluded that in the chosen AM method, the material must be optimized according to the geometry of the part to be produced, number of parts to be produced, process parameters, tribological requirements, and

this method can also be considered an alternative for sheet metal forming tool.

*Utilization of Additive Manufacturing to Produce Tools DOI: http://dx.doi.org/10.5772/intechopen.89804*

steel powder produced by SLS RapidSteel has the best wear resistance as expected, among others. Polyamide die has remarkably high wear rate which indicates that these are not appropriate for any series more than 100 parts. ZAMAK (zinc, aluminum, copper alloy) produced by casting into a SLA mold turns out to have a moderate wear resistance. All these trends obtained in these experiments are in accordance with the Archard theory, where the wear of the tool is indirectly proportional to the hardness of the die materials. Still, when investigated in detail their wear behavior, their elastic deformation, and tribological behavior affect the wear distribution over time, i.e., number of parts, sliding distance, or wear work.

This implies that according to the geometry and the number of the parts needed, this method can also be considered an alternative for sheet metal forming tool.

### **4. Conclusion**

*Design and Manufacturing*

The key technology for predicting the development of wear in metal forming tools is numerical simulation. In forming applications, a wear is commonly described

Archard wear equation. Here the parameters affecting the wear are contact pressure,

With the offered methodology, the wear depth at each location at each punch stroke can be predicted. **Figure 11** depicts as an example a predicted vs. measured

The **Figure 12** shows the wear rate of different dies produced by AM technologies, measured at different time intervals. As expected all rapidly produced tools have higher wear, i.e., shorter operation times. LaserFormA6 a kind of stainless

*Measured wear depth in the profile (gray) compared to the simulation results of the same location (black) [14].*

using models based on contact mechanics, the most important one being the

sliding distance, hardness, and a tribological constant.

die radius wear rate after 10,000 punch strokes.

*Contact pressure obtained by finite element simulation [14].*

**100**

**Figure 12.**

**Figure 11.**

Customized and tailored design is gaining significance in all areas in the recent decades. The growing amount of variants and the declining amount of the same components also have a profound impact on the production procedures. Additive manufacturing is gaining importance due to many advantages, and in tool design it is used mostly due to its lead time advantage. Even if AM in tool production offers indispensable advantages in time, the cost of the tool must be optimized according to the number of parts to be produced, the couple of materials to be selected, and the method of production.

A methodology for predicting the most suitable AM technique for tooling, as well as predicting the life of the tool, becomes indispensable in order to optimize the part quality, process, and price prediction. First, it must be guaranteed that the selected fast tooling method and material are suitable for producing the tool. This involves dimensional precision, mechanical characteristics, surface quality of the selected AM method, associated process parameters such as tool deformation and temperature distribution, and determination of corresponding material pair and surface characteristics tribologically.

In this chapter a metal forming tool in a simplified round die geometry is chosen as an example to predict the wear of a AM-produced tool, and the results show that the AM-produced tool has a shorter operation life, showing a wider range of lifetime depending on the AM technique and the tool material which are used.

From these results it can be concluded that in the chosen AM method, the material must be optimized according to the geometry of the part to be produced, number of parts to be produced, process parameters, tribological requirements, and the time and cost constraints.

*Design and Manufacturing*
