Manufacturing Feature Recognition from Solid Models
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Abstract
Indiscrete part manufacturing a product undergoes a finite number of machining and
assembly operations. When a finished design is passed to the manufacturing department,
detailed instructions are required to convert the work material (blank) from its initial form to final
form defined by an engineering drawing or product model. These detailed instructions required
are known as process plan. So once the process planning phase has been completed, actual
production of the part begins, according to instructions generated during the process planning. So
the interface between the design and manufacturing is process planning - Today computer aided
design (CAD) and computer aided manufacturing (CAM), have been implemented. Process
planning is the critical bridge between design and manufacturing. In CAD/CAM Integration,
computer aided process planning (CAPP) system plays a Key role between design and
manufacturing.
In a typical CAD/CAPP/CAM/ integration, there are two basic interfaces to be
established, CAD/CAPP interface and CAPP/CAM interface.
The former is accomplished by a "Feature Recognizer ", whereas the latter is achieved
by an "NC part programme Generator"
Informally, features are generic shapes or other characteristics of a part with which
engineers can associate knowledge useful for reasoning about the part. These are many
published, definitions of the concept of a feature. Even enough there definitions seem to be
dissimilar, they are consider features as entities which are of semantically higher level than the
pure geometric elements typically used in solid modeling systems. Features are generally be
classified into three categories; design features, machining feature and geometric features.
The geometric aspects of features are defined as volumes enveloped by a set of real and
imaginary faces. Geometric elements are solid primitives in CSG type solid models (blocks,
Cylinders, spheres, tore) or boundary elements used in B-Rep type solid models (faces, edges,
vortices)- Almost Universally, the concept of generic feature classes is used and models are built
from Instances of genetic features - The generic type may be organized into feature taxonomy,
often realized as a collection of classes with in inheritance of information according to the
principles of object-oriented programming. In the type - instance approach, feature instances are
represented in terms of various feature attributes, common attributes include the intrinsic
geometric attributes of shape corresponding to the feature (length, width, depth, radius), the
position and orientation of the feature with respect to some global coordinate frame, geometric
tolerances, material properties, references of the type.
A manufacturing feature is commonly defined as a collection of related geometric
elements which correspond to a particular manufacturing method or process, or which can be
used to reason about the suitable manufacturing method or processes for creating that geometry.
The Development of an automatic CAD/CAPP interface with the use of features has
generally been proposed within the following two main philosophies; First is Design the part with
solid modeling system and then manufacturing specific information is Retrieved from the
geometrical Representation of component alone is known as Automatic Feature Recognition or
Extraction.
Second approach is Design the part with a feature-based modeling system and thereby
incorporate manufacturing information in the model at the design stage is known as Feature
Based Modeling.
Automatic feature Recognition has been an active Research area in solid modeling for
many years and is considered as critical component for integration of computer-Aided design and
computer Aided Manufacturing(CAD/CAM).Advanced Computing methods used in feature
processing include the use of Expert systems and Artificial Intelligence(AI) techniques ,so these
techniques are also discussed in detail. This Thesis gives an overview of the state-of-the-art in
feature recognition research. Various Algorithmic approaches for feature Recognition: graph
based algorithm, volumetric decomposition techniques, and hint based geometric reasoning.
Each approach is discussed in detail with some assessments of the technology.
