| J. Han, M. Pratt, W. Regli. Manufacturing feature recognition from solid models: a status report. IEEE Trans. Robotics and Automation, 6(6):782--796, 2000. |
....design and manufacturing stages to be more easily integrated. 2.6.1 Types of Machining Feature Recognition Algorithms There are a large number of research papers on this subject and the following review is only 25 a sample. For a fuller review of AFR methods, the reader is referred to Han et al. [22] or Marefat and Ji [33] In this brief overview we consider the following: Graph Based Algorithms. Hint Based Algorithms. Cell Based Algorithms. Neural Net Based Algorithms. Volumes Based Methods. Hybrid Algorithms. 2.6.1.1 Graph Based Algorithms Perhaps the most common type of ....
Han J.H., Pratt M. & Regli W.C., "Manufacturing feature recognition from solid models: a status report", IEEE Transactions on Robotics and Automation, Vol. 16, No. 6, December 2000, pp. 782-796. 141
....which as a whole correspond or can be associated to a particular manufacturing method or process. Thus a hole feature is associated with drilling and other hole making processes. In machining applications, typical manufacturing features include holes, slots and pockets. According to Han and Regli [5], two basic approaches are employed for the aforementioned purpose: feature recognition and feature model conversion. The feature recognition approach analyzes boundary representation and or CSG tree data from solid modeling geometry to identify manufacturing features. The second approach performs ....
J.Han and W.C.Regli, "Manufacturing Feature Recognition from Solid Models: A status report", IEEE Transactions on Robotics and Automation, Vol. 16, No. 6, pp. 782-796, December 2000.
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J. Han, M. Pratt, W. Regli. Manufacturing feature recognition from solid models: a status report. IEEE Trans. Robotics and Automation, 6(6):782--796, 2000.
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