3D modeling and machine drawing assignment| |feature recognition systems and techniques||

 QUESTIONS:

A1.1) survey on Classification of feature recognition systems and techniques.

A1.2) Compare the techniques for recognizing features from CSG and B-rep solid modeling approaches with Merits and de-merits2)

A1.3) Stance taken with conclusion.

ANSWERS:

A1.Survey on classification of feature recognition systems and techniques

The Feature recognition is required to interpret the low-level part information into high-level and domain-specific features such as machining features. As the Conventional CAD models only provide pure geometry and topology for mechanical designs such as vertices, edges, faces, simple primitives, and the relationship among them. It serves as an automatic and intelligent interpreter to link CAD with CAM, regardless of the CAD output being a pure geometric model or a feature model from a FBD system. To be specific, the goal of feature recognition systems is to bridge the gap between a CAD database and a CAPP system by automatically recognizing features of a part from the data stored in the CAD system, and based on the recognized features, to drive the CAPP system which produces process plans for manufacturing the part.

 

Figure 1.1 process of feature recognition

 

The above flow chart shows the process of a feature recognition working, firstly the input will be a fully defined geometric CAD model, this will undergo the feature identification process which is the most difficult task among four steps in here the geometric model will be scanned with features such as hole, pocket, slot, etc. Next step is to determine the parameters of the features such as depth of hole, diameter of hole, etc. Then comes feature extraction where the features are removed from the geometric model to form a stand-alone feature entity. And finally the feature organization , here the features are named and arranged in a particular structure. A fully defined Feature model is ready as an output, which will be used in CAM.

 

Classification of feature recognition

 

The feature recognition is commonly classified by actual techniques used by systems and those are

1. ·        syntactic pattern recognition approach
2. ·        geometric decomposition
3. ·        expert system rule/logic approach
4. ·        graph-based approach

or some may classify them upon machining nature i.e. recognition by rotational or non-rotational feature in manufacturing processes.

 

In fewest possible way, some features are recognized by detecting  geometric model with the help of pre-defined libraries called feature detection and some features are recognized by generating using the CAD model by various techniques called feature generation.

 

1.      Feature detection

Algorithms used for feature detection normally vary with the different feature representation

schemes adopted in the feature libraries. The following are the tasks involved in feature detection

• re-constructing the geometric model topologically and/or geometrically;

• searching the database to match topologic/geometric patterns with those in the feature library

• extracting detected feature(s) from the database is prohibited.

• completing the feature geometric model

• analyzing and re-constructing features.

 

Although, all the steps are not necessary for feature detection. The feature detection is based on depression oriented approach and depend on different feature detection techniques which  are

 

(     (a)    Graph-based method : When dealing with a boundary representation of a component, faces can be considered as nodes of the graph and face-face relationships form the arc/links of the graph. The feature recognition methods utilising the graph-based techniques usually have two steps. First of all, the component model is represented in a “face adjacency graph (FAG)”. Then, parsers are developed to decompose this FAG into pre-defined FAG’s that correspond to various features. Pattern matching is eventually carried out to identify the features from the component. This type of graph-based feature recognition method is purely based on topologic information.

 

     (b)   syntax-based method : Feature syntax can be expressed in terms of either edges or faces, and it is based on their local characteristics. For specific feature there exists a particular syntax. The only difference is that these appropriate techniques have been extended from catering for 2D situations to 3D situations.

 

     (c)    rule-based method : For different features, rules can be written for detecting directly the underlining features. Templates are normally defined first for both general and specific features. Then rules are constructed for each of the feature template. More often than not, both geometric and topological conditions are tested. Rule-based methods can detect features that graph-based and syntax-based methods cannot. It is also easy to construct and alter rules when necessary. It is also been widely used together with other types of methods for feature recognition.

 

     (d)   techniques for recognizing features from CSG models : Recognising features from a CSG model, re-arrangement and re-interpretation are usually the two steps to follow. So that it corresponds to the expression of the desired machining feature CSG model can be expressed in more than one way which makes it possible to re-arrange it. And as modification are done because CSG primitives are not necessarily machining feature volumes, and they often overlap with each other re-interpretation is needed.

 

2.      Feature generation

 

Feature generation differs from feature detection in that there is not a complete, pre-defined feature library or feature template to be consulted with and/or matched to when features are being recognised. Therefore, feature generation approaches have to take into consideration more manufacturing information such as the types of machine tools and cutting tools to be used. Special techniques or tools are usually introduced and performed upon the geometric model to help generate features.

 

Feature generation techniques can be classified here into two categories

Technique based approach and direct model interrogation approach.

 

·        Technique-based approaches is further classified as

       (a)  cell decomposition :

       (b) section techniques.

      (c) convex-hull algorithm.

(d)backward growing.

 

·        Direct model interrogation approach

 

Direct model interrogation approaches differ from technique-based approaches in that the geometric model of a part remains intact while the feature generation process is carried out. Further classified as

 

    (a)    Geometric reasoning.

    (b)   Volume decomposition.

 

 

 

 

 

 

 

 

 

 

A2. Comparison of the techniques for recognizing features from CSG and B-rep solid modeling approaches with merits and de-merits

	CSG	B-Representation
Data structure	Simple	complicated
Amount of Data	small	Large
Validity	Represents only valid objects	Represents
Data exchange	Available(into B-reps)	Difficult(into CSG)
Re-modification	Simple	Depending on data structure
Local modification	Difficult	Easy
Speed of display	Slow	Fast
Surface representation	Difficult	Relatively easy

 

A3. Stance taken with conclusion

Yes, feature recognition techniques make geometric models more versatile and powerful integration entities in the entire product development cycle as feature recognition systems act as a mere interface between CAD and CAM and it will be more time consuming if even a skilled manufacturer replaces the work of feature recognition system.

                                                          ALL the credits goes to gautam