Feature extraction and feature based design approaches in the development of design interface for process planning

1990 ◽  
Vol 1 (1) ◽  
pp. 1-15 ◽  
Author(s):  
Sanjay Joshi ◽  
Tien-Chien Chang



Author(s):  
C. Jebaraj ◽  
D. Kingsly Jeba Singh

This work explains the development of an integrated modeler, which is applied in the design-to-manufacturing stages of manufacturing processes namely machining, sheet metal processing and forging. Its system architecture is broadly divided into four modules namely, Feature Based Design (FBD), Virtual Factory Environment (VFE), Process Based Feature Mapping (PBFM) and Process Planning (PP). Feature based design is used for the design, modeling, synthesis, representation and validation of the components for manufacturing applications. New set of features namely integrated features are pre-defined as feature templates and instanced to get / derive the information required for the design-to-manufacturing stages of the components. VFE defines the factory, which provides the database for operations, machines, cutting tools, work pieces etc. The knowledge base of the developed system maps validated features of the component into operation sets in the first phase of the PBFM. Each operation in the operation sets can be executed using different machines and tools in a factory. All these possible choices are obtained in the second phase of PBFM. Genetic algorithm is used to find the optimal sequence of operations, machines and tools for different criteria in the process planning stage. This paper explains the developed system with case studies.





Author(s):  
JungHyun Han ◽  
Aristides A. G. Requicha

Abstract Process planning for machined parts typically requires that a part be described through machining features such as holes, slots and pockets. This paper presents a novel feature finder, which automatically generates a part interpretation in terms of machining features, by utilizing information from a variety of sources such as nominal geometry, tolerances and attributes, and design features. The feature finder strives to produce a desirable interpretation of the part as quickly as possible. If this interpretation is judged unacceptable by a process planner, alternatives can be generated on demand. The feature finder uses a hint-based approach, and combines artificial intelligence techniques, such as blackboard architecture and uncertain reasoning, with the geometric completion procedures first introduced in the OOFF system previously developed at USC.



Author(s):  
Jian Dong ◽  
Sreedharan Vijayan

Abstract The elements of Computer-Aided Manufacturing, do not make full use of the part description stored in a CAD model because it exists in terms of low-level faces, edges and vertices or primitive volumes related to the manufacturing planning task. Consequently manufacturing planning still depends upon human expertise and input to interpret the part definition according to manufacturing needs. Feature-based technology is becoming an important tool to resolve this and other related problems. One approach is to design the part using Features directly. Another approach is Manufacturing Feature Extraction and Recognition. Manufacturing Feature Extraction consists of searching for the part description, recognizing cavity features, extracting those features as solid volumes of material to be removed. Feature Recognition involves raising this information to the level of part features which can be read by a process planning program. The feature extraction can be called optimal if the manufacturing cost of the component using those features can be minimized. An optimized feature extraction technique using two powerful optimization methods viz., Simulated Annealing and Genetic Algorithm is presented in this paper. This work has relevance in the areas of CAD/CAM linking, process planning and manufacturability assessment.



1990 ◽  
Vol 14 (2) ◽  
pp. 225-235 ◽  
Author(s):  
D.C. Anderson ◽  
T.C. Chang


2007 ◽  
Vol 46 (3) ◽  
pp. 675-701 ◽  
Author(s):  
D. Kingsly Jeba Singh ◽  
C. Jebaraj


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