ComputerAided_Design_Engineering_amp_Manufactur.pdf
ComputerAided_Design_Engineering_amp_Manufactur.pdf
ComputerAided_Design_Engineering_amp_Manufactur.pdf
You also want an ePaper? Increase the reach of your titles
YUMPU automatically turns print PDFs into web optimized ePapers that Google loves.
strong reasons to support a move to 3-D CAD representation of progressive dies:<br />
1. In an automated design environment where most of the design tasks are left to the computer, it<br />
is important to provide the designer with an effective tool to perform the final inspection of the<br />
die assembly. A 3-D model is the ideal visualization aid for the designer to use to check for and<br />
correct any mistakes made by the design automation system.<br />
2. Similarly, a 3-D model of the strip can be laid on die assembly both in the open and shut positions.<br />
This provides a fast and effective means for the visual confirmation of the total solution. Any operational<br />
problems that may be caused by the interference of the strip with the die can be picked up quickly.<br />
3. An accurate CAD representation of the non-standard components can be used directly to program<br />
the NC codes required for their fabrication.<br />
4. Many CAD/CAM systems provide aids to produce 2-D drawings from 3-D models. Hence, traditional<br />
die drawings can still be produced very quickly.<br />
3-D CAD models can be produced from the engineering model in several ways, depending on the<br />
capabilities of the knowledge-based system and the CAD system. For ex<strong>amp</strong>le, functions can be written<br />
in the knowledge-based system to scan the engineering model and translate it into neutral file descriptions.<br />
Macros can be written in the CAD system to read these neutral files and generate the 3-D CAD<br />
model. Alternatively, the knowledge-based system can fire functions to generate solid modeling kernel<br />
data files for each and every component. These files can then be read by a CAD system.<br />
Figure 7.15 shows the exploded view of a punch plate subassembly generated using the MBR approach.<br />
Figure 7.16 shows a partial assembly of a two-stage piercing and blanking die generated using some of<br />
the techniques described.<br />
7.13 Feature-Based Process Planning for the <strong>Manufactur</strong>e<br />
of Progressive Dies<br />
There have been many attempts to automate the process planning function for the manufacture of<br />
engineering components. Invariably, these systems involve a machining feature extraction function to<br />
transform the geometrical and topological information of a product model held in a CAD system into<br />
relevant machining features such as holes, slots, fillet, chamfer, etc. This approach involves the use of<br />
complex algorithms that consume a considerable amount of computer resources.<br />
There is no need for the feature extraction task if one adopts the MBR approach for die synthesize.<br />
This is because the machining features can be extracted directly from the engineering model of the die<br />
stored in the knowledge-based system. For ex<strong>amp</strong>le, the following machining features can be deduced<br />
from the model-based description of the punch plate:<br />
• Dowel holes are straight thru circular holes.<br />
• Holes for screws on punch plate are threaded counterbore holes.<br />
• Retaining holes for straight punches are non-circular thru holes.<br />
• Retaining holes for block punches are rectangular thru holes.<br />
• Retaining holes for circular shoulder punches are counterbore holes.<br />
• Retaining holes for non-circular shoulder punches (i.e., with keys) are complex features consisting<br />
of a thru hole and an irregular pocket.<br />
• Retaining holes for pilots are counterbore holes.<br />
Similarly, formulas for the calculation of dimensional and geometrical tolerance values for these<br />
machining features can be programmed as methods in their object representations. In other words, the<br />
MBR approach is able to generate sufficient information to initiate the automated process planning task.<br />
Hence, the framework identified in this chapter can be extended to perform the process planning task if