MEDIATOR: A Resource Adaptive Feature Recognizer that Intertwines Feature Extraction and Manufacturing Analysis

A deterrent to practical use of many feature extraction systems is that they are difficult to maintain, either because they depend on the use of a library of feature-types which must be updated when the underlying manufacturing resources change (e.g. Cools and fixtures ), or they rely on the use of task-specific post processors, which must also be updated. For such systems to become practical, it must be easy for a user to update the system to match the current resources. This paper presents MEDIATOR (Maintainable, Extensible Design and manufacturing Integration Architecture and TranslatOR). MEDIATOR is a resource adaptive feature extraction and early process planning system for 3-axis milling, A resource adaptive system is one that changes its behavior as the manufacturing resources in a shop change, MEDIATOR allows users to select from a standard set of tools and fixtures, and automatically identifies any changes in the features that result, It attains its resource adaptive behavior by blurring the line between feature extraction and process planning; descriptions of the manufacturing resources are used to directly identify manufacturable areas of the part. A non-programmer can easily update MEDIATOR by selecting different shop resources.

[1]  Satyandra K. Gupta,et al.  Feature Recognition for Manufacturability Analysis , 1994 .

[2]  Amy J. C. Trappey,et al.  Fixture configuration using projective geometry , 1993 .

[3]  Satyandra K. Gupta,et al.  AI Planning Versus Manufacturing-Operation Planning: A Case Study , 1995, IJCAI.

[4]  Aristides A. G. Requicha,et al.  Spatial Reasoning for the Automatic Recognition of Machinable Features in Solid Models , 1993, IEEE Trans. Pattern Anal. Mach. Intell..

[5]  Steven J. Fenves,et al.  Towards a Framework for Concurrent Design , 1989, MIT-JSME Workshop.

[6]  T. C. Chang,et al.  Graph-based heuristics for recognition of machined features from a 3D solid model , 1988 .

[7]  Satyandra K. Gupta,et al.  Building MRSEV models for CAM applications , 1994 .

[8]  J. Shah,et al.  Determination Of Machining Volumes From Extensible Sets Of Design Features , 1994 .

[9]  Caroline C. Hayes P3: a process planner for manufacturability analysis , 1996, IEEE Trans. Robotics Autom..

[10]  A. Márkus,et al.  Experiments with the integration of reasoning, optimization and generalization in process planning , 1994 .

[11]  Satyandra K. Gupta,et al.  Estimation of Setup Time for Machined Parts: Accounting for Work-Holding Constraints , 1995 .

[12]  Y. Kim Volumetric Feature Recognition Using Convex Decomposition , 1994 .

[13]  Douglas E. R. Clark,et al.  Method for finding holes and pockets that connect multiple faces in 2 1/2D objects , 1991, Comput. Aided Des..

[14]  Leila De Floriani Feature Extraction from Boundary Models of Three-Dimensional Objects , 1989, IEEE Trans. Pattern Anal. Mach. Intell..

[15]  O. W. Salomons,et al.  Review of research in feature-based design , 1993 .

[16]  Byoung Kyu Choi,et al.  Automatic recognition of machined surfaces from a 3D solid model , 1984 .

[17]  Rangasami L. Kashyap,et al.  Geometric Reasoning for Recognition of Three-Dimensional Object Features , 1990, IEEE Trans. Pattern Anal. Mach. Intell..