ComputerAided_Design_Engineering_amp_Manufactur.pdf

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FIGURE 7.4 Final punch shapes selected by modifying the strips in Figure 7.3(b). of the two adjacent edges to the fillet. The strips are generated for the new edges. Finally, the filleted corners are re-introduced to the punch shape. • The edge of the punch that is adjacent to the edge of a workpiece is the cutting edge. The punch clearance is automatically applied to this edge. • Overlap allowance is automatically applied to the non-cutting (unbounded) edge to prevent blurr formation. These punch shape modification commands can be used to select the final punches required to stamp out the external profile of a workpiece. Figure 7.4 shows how the strips initially generated to stamp out the part shown in Figure 7.3a can be modified into practical punch shapes. The strip approach has the tendency to produce too many notching punches. In addition, it does not take into consideration the relative location of the center of pressure of the notch contour to the shape of the punch. Hence, there is a need for the user to retain control in the final selection of the punch shapes. This can be achieved by providing a set of punch shape modification commands for the user to modify the strips to meet his requirements. Some of the functions of punch shape modification commands required are • Automatic calculation and display of the center of pressure of a notch contour relative to the shape of the punch • Combination of two or more neighboring shapes into one • Stretching selected edges of a shape by an offset distance • Spiltting a larger shape into two smaller ones • Automatic generation of a shape based on boundaries defined by the users. The complex task of punch shape decomposition is reduced by dividing the process into smaller, manageable subtasks where the computer concentrates on the number-crunching geometry processing tasks while the designer concentrates on making decisions to guide the system towards an optimum solution. This generate-then-modify approach appears to be an efficient tool to solve the progressive die design automation problem. It helps to eliminate the tedious construction and calculation chores associated with the traditional approach and hence allows the designer to concentrate on selecting the optimum shapes.
A Skeletal Approach for the Recognition of Punch Shapes The design of progressive dies involves the process of matching the profiles of the punch designed by the user with a catalogue of standard punch shapes supplied by the die component’s manufacturer. There are two advantages associated with using standard components: first, they are usually cheaper than custom made component, and second, they are readily available, hence reducing the production lead time. When a die designer is developing the strip using the traditional approach, he is continually taking off dimensions from the product drawings to develop the various punch shapes. Hence, the manual task of matching punch profiles with the standard punches provided in the catalogue becomes a natural extension of the measuring and construction tasks. However, in an automated environment, the punch profiles are derived directly from the geometry of the respective features stored in the knowledge base. It would be a tedious exercise for the user of the die design automation system to pick off the dimensions of the punch profiles developed by the system and manually select the standard punch shapes from the catalogue. Furthermore, it would defeat the main objective of providing the die design automation system, i.e., to allow the designer to concentrate on the important task of making design decisions by relieving him from the mundane and tedious tasks of measuring, checking, and flipping through catalogues. The use of the skeleton as a descriptor of shape has been adopted by many researchers to simplify image processing and recognition problems. Several efficient ‘‘skeletonization’’ schemes have also been developed. One group of researchers (Wu et al., 1994a, Wu and Chen, 1994b) introduced the use of the simplified line skeleton for the classification of 2-D workpieces. They defined the simplified skeleton of the polygon as the set of points where the firings of two non-neighboring edges meet in their advancing paths. They divided the simplified skeleton into real and virtual links. They also proved that the simplified skeleton correctly represents the global shape information of a rectilinear contour. The Enhanced Simplified Line (ESL) skeleton was developed at the National University of Singapore specifically for the recognition of punch shapes. The ESL skeleton is a modification of Wu and Chen’s simplified line skeleton. In addition to the real and virtual links, extension links are introduced to represent the local shape information at the corners and ends of a profile. In addition, the ESL skeleton can be applied to non-rectilinear contours. If a contour consists of circular segments, they are approximated by straight lines; its ESL skeleton is derived regardless of whether the sides are non-rectilinear. The steps required for the construction of the ESL skeleton for an L-shaped contour are illustrated in Figure 7.5. In the final skeleton, FG and DE are the real links. FG has a shrinkage grade of (d1+d2) while DE has a shrinkage grade of d1. GD is the virtual link while the dashed lines are the extension links. A commercial die components catalogue consists of many standard punch shapes. For example, there are 78 basic and special punch shapes in the Face ’88–’89 Misumi Press Die Standard Components and System Technical Specifications (Misumi, 1988). After detailed analysis of the ESL skeletons of the standard punch shapes, it was discovered that the following skeletal features can be used to help recognize FIGURE 7.5 Steps taken to generate the ESL skeleton of an L-shaped contour.
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COMPUTER-AIDED DESIGN, ENGINEERING,
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Library of Congress Cataloging-in-P
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Editor Cornelius T. Leondes, B.S.,
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Chapter 1 Chapter 2 Chapter 3 Chapt
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the implementation of the IPD syste
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In our IPD system implementations,
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2. Specification of analysis-specif
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FIGURE 1.2 base or the design insta
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FIGURE 1.4 System architecture of t
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of a beam is considered for FEA. Th
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FIGURE 1.7 through the control expe
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2. machining facility (e.g., gang m
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from the FBDS. The user also specif
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Depending on the type of feature to
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TABLE 1.6 Tolerance synthesis is de
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FIGURE 1.12 Display of the NC tool
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component geometric entities and va
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FIGURE 1.14 The system architecture
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TABLE 1.10 User Input for the Toler
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TABLE 1.11 Tolerance Specifications
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7. Z. Young and I. R. Groose. A rul
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FIGURE 2.1 Tool paths generated for
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FIGURE 2.2 sented by instances of f
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TABLE 2.1 A CAD-Generated Hole Conf
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FIGURE 2.6 mounted on the rotary ta
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FIGURE 2.8 fixture for the machinin
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FIGURE 2.10 or best-fit, or the cur
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FIGURE 2.11 Linear approximation of
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FIGURE 2.13 Circular approximation
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FIGURE 2.14(b) Circular approximati
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FIGURE 2.16 Types of biarcs. FIGURE
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FIGURE 2.18 Approximation of scanne
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FIGURE 2.20 A touch trigger probe c
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TABLE 2.4 Substitute Elements in CM
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FIGURE 2.21 CMM planning requiremen
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Product Model Representation for Co
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© 2001 by CRC Press LLC TABLE 2.5
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TABLE 2.7 Partial Listing of Dimens
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24. Makinouchi, S., Okamoto, M., an
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Bijan Shirinzadeh Monash University
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FIGURE 3.1 Trends in flexible manuf
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FIGURE 3.3 and constrain different
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Other Fixturing Techniques There ar
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FIGURE 3.6 contact point. The geome
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FIGURE 3.8 The vertical support fix
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and moments about the contact point
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een identified, the normals are use
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one of choosing the variables: such
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Fixture Module Location An importan
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FIGURE 3.15 Illustration of functio
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FIGURE 3.18 Minimum separation test
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direction) the face, respectively.
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FIGURE 3.21 Software structure for
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3.8 Conclusion A reconfigurable fix
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Heui Jae Pahk Seoul National Univer
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FIGURE 4.1(b) Conceptual framework
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4.3 Measurement Points Sampling and
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Surface S2 Measurement Path FIGURE
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FIGURE 4.4 Rough phase alignment ba
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deviation between the nominal CAD d
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FIGURE 4.6(a) Sum of squares distan
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FIGURE 4.7(c) Trailing edge. (c) th
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FIGURE 4.8(a) Profile tolerance of
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The calculated minimum form error i
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FIGURE 4.11(a) A typical mold havin
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FIGURE 4.11(d) Inspection results f
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FIGURE 4.12(c) Maximum deviation (p
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5.1 Introduction Developments in th
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process plan for a part (Figure 5.3
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FIGURE 5.5 leading to the developme
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the previously stored process plan
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FIGURE 5.7 Techniques of defining a
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Feature Recognition and Extraction
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in relation to another feature (e.g
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FIGURE 5.9 Framework for building a
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FIGURE 5.10 Process plan content.
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FIGURE 5.12 Schematic sketch of the
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Several techniques of defining a fe
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TABLE 5.1 Data Structure for Repres
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FIGURE 5.16 Classification of the t
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system to ensure that the part bein
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FIGURE 5.19 Graphical model of the
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TABLE 5.4 Data Structure for Repres
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FIGURE 5.20 Mapping between machini
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algorithms. (Some details of the pr
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FIGURE 5.24 An example rotational p
Page 173 and 174: FIGURE 5.26 Down_face-turn-up_face
Page 175 and 176: FIGURE 5.27 Procedure for machine t
Page 177 and 178: FIGURE 5.28 Determining the number
Page 179 and 180: DL is needed to be set only if the
Page 181 and 182: FIGURE 5.31 Operation sequencing co
Page 183 and 184: Cutting Tool Selection Selection of
Page 185 and 186: 1. A tool is searched for in the da
Page 187 and 188: FIGURE 5.32 Inputs to optimization
Page 189 and 190: When these values are substituted,
Page 191 and 192: Usually, maximum and minimum speed
Page 193 and 194: FIGURE 5.33 Solution methodology.
Page 195 and 196: TABLE 5.6 Process Plan Internal Rep
Page 197 and 198: In a strict theoretical perspective
Page 199 and 200: 18. Domazet, D. S. and Lu, S. C. Y,
Page 201 and 202: 63. Prasad, A. V. S. R. K., Rao, P.
Page 203 and 204: CAD systems. The sample consists of
Page 205 and 206: learn to master the new system. An
Page 207 and 208: Although researchers appear to agre
Page 209 and 210: Link and Zmud28 found that organic
Page 211 and 212: Informal Training Informal CAD trai
Page 213 and 214: informal training programs, felt th
Page 215 and 216: 6. C. A. Beatty, Tall Tales and Rea
Page 217 and 218: A.Y.C. Nee National University of S
Page 219 and 220: FIGURE 7.1 Planning, design, and ma
Page 221 and 222: A metal stamping can have the follo
Page 223: FIGURE 7.3 Strips used to notch out
Page 227 and 228: These findings can be used to devel
Page 229 and 230: Semi-Direct Piloting In cases where
Page 231 and 232: a larger value, the die operations
Page 233 and 234: FIGURE 7.9 Symbolic relationship be
Page 235 and 236: FIGURE 7.11 The shape of the envelo
Page 237 and 238: TABLE 7.1 Schema for the Generation
Page 239 and 240: strong reasons to support a move to
Page 241 and 242: FIGURE 7.16 3-D CAD model of a part
Page 243 and 244: References Cheok, B.T. et al. (1994
Page 245 and 246: include the once forbidden generati
Page 247 and 248: A temporal matrix (T-Matrix) is pro
Page 249 and 250: FIGURE 8.1 A basic process. (From R
Page 251 and 252: FIGURE 8.4(a) Generate a new IG usi
Page 253 and 254: Note if the pair of nodes are both
Page 255 and 256: TABLE 8.1 Summary of the Rules Cond
Page 257 and 258: The correctness of these rules is e
Page 259 and 260: needs to show that after each full
Page 261 and 262: ule is violated, a warning should b
Page 263 and 264: Π1 Π3 Π4 FIGURE 8.8(a) After add
Page 265 and 266: 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
Page 267 and 268: A ik � ‘U’ and is in a cycle
Page 269 and 270: FIGURE 8.12(a) Add [p2 t7 p7 t8 p4]
Page 271 and 272: FIGURE 8.12(c) Add a token to p8 vi
Page 273 and 274: FIGURE 8.12(e) Add [p8 t9 p14 t10 p
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FIGURE 8.13 An example of rule TT.0
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FIGURE 8.14 A GPN model of a machin
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FIGURE 8.15(b) The first exclusive
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FIGURE 8.15(d) The last exclusive T
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FIGURE 8.15(f) After entering the a
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FIGURE 8.15(h) Completion of Compon
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FIGURE 8.15(j) Two PP-generations:
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FIGURE 8.15(l) The last exclusive T
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t1 t5 p1 p5 t6 (a) t2 t3 t4 2 2 p2
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FIGURE 8.17 An example of partial f
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Theorem 10: If pi → pk in a synth
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Note that control transitions are o
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t j than the lower at , it indicate
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• Programming logic and VLSI arra
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7. Chao, D. Y. and D. T. Wang, Appl
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53. Villaroel, J. L., J. Martinez,
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q u : the numerator of the least ra
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geometric modeling, engineering ana
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In dimension driven or parametric d
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FIGURE 9.3 configuration of bodies
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FIGURE 9.6 FIGURE 9.7 Geometric Int
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FIGURE 9.8 Intersection of degrees
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will introduce a way to propagate p
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Completeness of Dimensions Complete
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FIGURE 9.12 3-D constraints. © 200
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The distance constraint from pt �
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therefore: Now merge the lists and
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Quantity analysis methods have the
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y a revolute joint. By selecting al
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