B-code Generation for a CNC Dentistry Wire Bending Mechanism

In the present study, the generation of CNC wire bending code (B-code) is explored and an automatic converter is developed in Excel through some mathematical formulae. The B-code comprises of three parameters which have been determined from the previous work, known as feeding length (L), plane rotation angle (R) and bend-ing angle (A). These parameters control the movement of the designed wire bending machine in this way; (L) tells the feeding mechanism how long the straight wire to be fed, (R) constructs the turning mechanism to rotate in certain degrees before the bending operation starts and (A) determines the degrees of bend, performed by the bending mechanism. The input of the converter is the Cartesian XYZ coordinate of each bend point, obtained from the CAD file. This paper also describes the XYZ extraction process from an IGES file, in addition to the CNC code generation. The practicality of these procedures is demonstrated through an example, starting from the wire design, follows by the XYZ extraction and ends with the B-code generation. Moreover, the graphical simulation of the bending operation by the designed mechanism is also presented. However, the capability of these codes in controlling the wire bending machine in the real bending operation will not be discussed in the present work

A multi-perspective dynamic feature concept in adaptive NC machining of complex freeform surfaces

This paper presents a new concept of feature for freeform surface machining that defines the changes in feature status during real manufacturing situations which have not been sufficiently addressed by current international standards and previous research in feature technology. These changes are multi-perspective, including (i) changes in depth-of-cut: the geometry of a feature in the depth-of-cut direction changes during different machining operations such as roughing, semi-finishing and finishing; (ii) changes across the surface: a surface may be divided into different machining regions (effectively sub-features) for the selection of appropriate manufacturing methods for each region such as different cutting tools, parameters, set-ups or machine tools; and (iii) changes in resources or manufacturing capabilities may require the re-planning of depth-of-cuts, division of machining regions and manufacturing operations (machines, tools, set-ups and parameters). Adding the above dynamic information to the part information models in current CAD systems (which only represent the final state of parts) would significantly improve the accuracy, efficiency and timeliness of manufacturing planning and optimisation, especially for the integrated NC machining planning for complex freeform surfaces. A case study in an aircraft manufacturing company will be included in this paper

Automatic extraction of free-form surface features (FFSFs)

This paper presents a new algorithm for extracting Free-Form Surface Features (FFSFs) from a surface model. The extraction algorithm is based on a modified taxonomy of FFSFs from that proposed in the literature. A new classification scheme has been proposed for FFSFs to enable their representation and extraction. The paper proposes a separating curve as a signature of FFSFs in a surface model. FFSFs are classified based on the characteristics of the separating curve (number and type) and the influence region (the region enclosed by the separating curve). A method to extract these entities is presented. The algorithm has been implemented and tested for various free-form surface features on different types of free-form surfaces (base surfaces) and is found to correctly identify and represent the features irrespective of the type of underlying surface. The representation and extraction algorithm are both based on topology and geometry. The algorithm is data-driven and does not use any pre-defined templates. The definition presented for a feature is unambiguous and application independent. The proposed classification of FFSFs can be used to develop an ontology to determine semantic equivalences for the feature to be exchanged, mapped and used across PLM applications. (C) 2011 Elsevier Ltd. All rights reserved

Framework for Automatic Identification of Paper Watermarks with Chain Codes

Title from PDF of title page viewed May 21, 2018Dissertation advisor: Reza DerakhshaniVitaIncludes bibliographical references (pages 220-235)Thesis (Ph.D.)--School of Computing and Engineering. University of Missouri--Kansas City, 2017In this dissertation, I present a new framework for automated description, archiving, and identification of paper watermarks found in historical documents and manuscripts. The early manufacturers of paper have introduced the embedding of identifying marks and patterns as a sign of a distinct origin and perhaps as a signature of quality. Thousands of watermarks have been studied, classified, and archived. Most of the classification categories are based on image similarity and are searchable based on a set of defined contextual descriptors. The novel method presented here is for automatic classification, identification (matching) and retrieval of watermark images based on chain code descriptors (CC). The approach for generation of unique CC includes a novel image preprocessing method to provide a solution for rotation and scale invariant representation of watermarks. The unique codes are truly reversible, providing high ratio lossless compression, fast searching, and image matching. The development of a novel distance measure for CC comparison is also presented. Examples for the complete process are given using the recently acquired watermarks digitized with hyper-spectral imaging of Summa Theologica, the work of Antonino Pierozzi (1389 – 1459). The performance of the algorithm on large datasets is demonstrated using watermarks datasets from well-known library catalogue collections.Introduction -- Paper and paper watermarks -- Automatic identification of paper watermarks -- Rotation, Scale and translation invariant chain code -- Comparison of RST_Invariant chain code -- Automatic identification of watermarks with chain codes -- Watermark composite feature vector -- Summary -- Appendix A. Watermarks from the Bernstein Collection used in this study -- Appendix B. The original and transformed images of watermarks -- Appendix C. The transformed and scaled images of watermarks -- Appendix D. Example of chain cod