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ComputerAided_Design_Engineering_amp_Manufactur.pdf

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A metal st<strong>amp</strong>ing can have the following features:<br />

St<strong>amp</strong>ed features: holes, notches, cutouts, slots, etc.<br />

Formed/bend features: bends, flanges, hems, seams, drawings, embossing, etc.<br />

Formed/st<strong>amp</strong>ed features: countersinks, etc.<br />

Each of these features can be associated with a metal st<strong>amp</strong>ing operation. They have attributes in the<br />

form of their geometrical and topological descriptions and technical specifications (e.g., tolerancing and<br />

finishing properties). A product can be described by connecting these features using feature relationships<br />

such as ‘‘connect_to’’ and ‘‘part_of.’’ The feature representation of a workpiece is shown in Figure 7.2.<br />

There are several advantages associated with the use of metal-forming features to describe a workpiece<br />

in an intelligent system:<br />

• The feature representation provides an “intelligent” description of the product.<br />

• The feature representation provides a convenient means for representation as objects in a knowledgebased<br />

system.<br />

• As each feature is associated with a st<strong>amp</strong>ing operation, it facilitates the generation of the process<br />

plan and the generation of the die. For ex<strong>amp</strong>le, when we are staging the die operations, we can<br />

build the rules to ensure that the sides of the wall of a bend feature must be notched before it is<br />

bent. Thereafter, the punches can be configured from the notch features and the tools associated<br />

with bending (i.e., bending punch, bending block, pressure pads, etc.) can be configured from the<br />

bend feature.<br />

• The ‘‘intelligent’’ association between a feature and the st<strong>amp</strong>ing operation required to manufacture<br />

it makes it possible to develop product design tools that provide product designers with tooling<br />

advice. For ex<strong>amp</strong>le, Mantripragada et al. (1996) developed an interactive design tool for box-type<br />

sheet metal parts that can be used to alert the designers to potential production problems, defects,<br />

and failures; it can also provide them with information that can be used to explore alternative design,<br />

evaluate trade-offs, and arrive at optimal design for the given process conditions.<br />

• The features and the associated ‘‘feature-relationship tree’’ can be used as a criterion to index the<br />

product in a design data base. The design data base is a data base of products and their associated<br />

progressive dies manufactured by a company. A die designer usually builds a progressive die by<br />

adopting an old design to meet the manufacturing requirements of the new product. Hence the<br />

features and the feature-relationship tree of a new product can be used to search through the<br />

design data base and retrieve the past design of the nearest product manufactured by the company<br />

for use as a reference to manufacture the new product. The use of features to index a product can<br />

be considered as the basis for the development of a case-based planning system for progressive<br />

dies. We will discuss the application of a case-based planning approach for progressive die design<br />

in another section.<br />

7.5 Pattern Processing and Recognition Tasks Associated<br />

with Operations Planning<br />

In essence, the operations planning task to develop the strip layout is a spatial planning exercise involving<br />

pattern processing and shape recognition skills best performed by human beings. Very little research<br />

work has been done to solve this problem and the operations planning task remains a major stumbling<br />

block in the development of an integrated system for the manufacture of progressive dies. Computerassisted<br />

pattern processing and shape recognition tasks are computationally intensive in nature. If the<br />

computer takes too long to perform these tasks, it would render the interactive, iterative feedback planning<br />

system ineffective. Therefore, there is a need to reduce the spatial planning tasks into smaller and simpler<br />

pattern processing and shape recognition subtasks done by the computer, while leaving the more complex<br />

decision making tasks to the user.

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