ComputerAided_Design_Engineering_amp_Manufactur.pdf

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Checker Specifications Design Ideas User File Manipulator Graph Editor Display Petri Net Graphics Behavior Analyzer Reduction Tool Synthesizer Auto Simulator Step Break Net Protocol FIGURE 8.10 Structure of the CAD tool for designing, analysis, and synthesis of protocols. (From Reference 2a. With permission.) construct a PN either using the “DRAW” button to draw transitions, places and arcs, or using the “FILE” button to input a PN file. Buttons “Move,” “Pan,” and “Zoom,” to allow large PNs to be drawn. Clicking the “Pan” button centers the graphics at a chosen location. In addition, the vertical (horizontal) scrollbar allows the graphics to be moved up and down (left and right). After the PN is drawn or displayed on the screen, graphical interconnection among places and transitions are translated into internal representations for further manipulations. A user can initiate the synthesis by clicking the “Petri” button of the “Synthesis” menu. Afterwards, no further clicking is necessary for further generations except for clicking the “T-Matrix” button to display the T-Matrix in the bottom window (called “text_w”) after a new generation. An example of this process to the synthesis of an automated manufacturing system (Figure 8.11) is shown in Figure 8.12. Shown in the bottom is a message window “text_w.” After each generation step, this window displays the kind of generation, and signals any rule violations or whether tokens must be added to places in the NPs. Upon an interaction generation, a new window pops up that displays an arrow linking two sets of nodes and invites the designer to pick one node in the left-hand (right-hand) set as ng( nj) . Each time a node is picked, the tool will call a filtering procedure to eliminate nodes in the set that are sequential to the node just picked and then redisplay the window. This process continues until both sides are empty and no more NPs need to be generated for this specific IG. In the displayed T-Matrix, each structural relationship is expressed by a single letter (e.g., “E”) different from the two letters (SE) presented earlier. The correspondence is shown in Table 8.2. In addition, Aik � ‘Y’ if Aik � ‘X’ and �i is in a cycle that has a place with more than one input transition; Aik � ‘Z’ if
A ik � ‘U’ and is in a cycle that has a place with more than one input transition. We now apply the tool to the synthesis of an automated manufacturing system (Figure 8.11). Description of a Manufacturing System This automated manufacturing system consists of the following major components (Table 8.3): two entries, two exits, five machines, two robots, two automatic guided vehicles (AGV), and related conveyors. It can produce two types of products. An unlimited source of raw materials is assumed. Once machines, robots, or AGVs start any operation, they cannot be interrupted until the work is complete. We now build up a well-behaved PN model. Modeling and Synthesis Process TABLE 8.2 Structure Relationship Correspondence Sequentially earlier E SE Sequentially later L SL Sequentially next N SN Sequentially previous P SP Exclusive X EX Concurrent U CN Cyclic C CL TABLE 8.3 Major Components Components Number Function Entries 2 Inputs two types (A and B) of raw materials Exits 2 for final A parts and B parts, respectively. Robots R1 Serves machines, M1, M2, and M4 with no priorities. Randomly choose one ready machine with raw material. R2 Loads machine M3 and M5. AGV Systems From Machines M1 and M2 AGV1 Deliver intermediate A parts to M3. AGV2 Deliver intermediate B Parts to M5. � i First, synthesize the production portion from Entry 1 to Exit 1, followed by that from Entry 2 to Exit 2. For the first portion, pick a basic process by identifying a sequence of operations of loading by R1, machining by M1, unloading via AGV1, loading by R2, and machining by M3 modeled as shown by the solid cycle [p1 t1 p2 t2 p3 t3 p4 t4 p5 t5 p6 t6 p1] in Figure 8.12(a). In this basic process, p1 models the availability of A-raw materials. Upon this basic process, generate a new PSP [p2 t7 p7 t8 p4] shown as the dashed line in Figure 8.12(a) using Rule PP.1 since ng � p2 and nj � p4; both are from the same basic process. The new PSP models another alternative to produce A-parts by Machine 2. Now there are three unique PSPs, i.e., �1 (or psp1) � [p4 t4 p5 t5 t5 p6 t6 p1], �2 (or psp2) � [p2 t2 p3 t3 p4], and �3 (or psp3) � [p2 t7 p7 t8 p4]. The tool also displays the T-Matrix after the PP generation in the bottom window. It is easy to see that �2 �3 and �1 is sequential to both �2 and �3 . Now since the operation in p3 requires Robot 1, generate a backward TT-path from t2 (in �2 ) to t1 (in �1), i.e., [t2 p8 t1]. In addition, a token in place p8, standing for Robot 1, using Rule TT.2. Furthermore, since the local exclusive set LEX (�2, �1 ) � { �2 , �3 }, generate a TP-path [t7 p8] via Rule TT.4.1 from a transition in �3 to p8. Since LEX( �1 , �2 ) � { �1}, nothing more needs to be added via Rule TT.4.2.
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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
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FIGURE 5.26 Down_face-turn-up_face
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FIGURE 5.27 Procedure for machine t
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FIGURE 5.28 Determining the number
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DL is needed to be set only if the
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FIGURE 5.31 Operation sequencing co
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Cutting Tool Selection Selection of
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1. A tool is searched for in the da
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FIGURE 5.32 Inputs to optimization
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When these values are substituted,
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Usually, maximum and minimum speed
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FIGURE 5.33 Solution methodology.
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TABLE 5.6 Process Plan Internal Rep
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In a strict theoretical perspective
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18. Domazet, D. S. and Lu, S. C. Y,
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63. Prasad, A. V. S. R. K., Rao, P.
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CAD systems. The sample consists of
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learn to master the new system. An
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Although researchers appear to agre
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Link and Zmud28 found that organic
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Informal Training Informal CAD trai
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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 and 224: FIGURE 7.3 Strips used to notch out
Page 225 and 226: A Skeletal Approach for the Recogni
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: 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
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
Page 275 and 276: FIGURE 8.13 An example of rule TT.0
Page 277 and 278: FIGURE 8.14 A GPN model of a machin
Page 279 and 280: FIGURE 8.15(b) The first exclusive
Page 281 and 282: FIGURE 8.15(d) The last exclusive T
Page 283 and 284: FIGURE 8.15(f) After entering the a
Page 285 and 286: FIGURE 8.15(h) Completion of Compon
Page 287 and 288: FIGURE 8.15(j) Two PP-generations:
Page 289 and 290: FIGURE 8.15(l) The last exclusive T
Page 291 and 292: t1 t5 p1 p5 t6 (a) t2 t3 t4 2 2 p2
Page 293 and 294: FIGURE 8.17 An example of partial f
Page 295 and 296: Theorem 10: If pi → pk in a synth
Page 297 and 298: Note that control transitions are o
Page 299 and 300: t j than the lower at , it indicate
Page 301 and 302: • Programming logic and VLSI arra
Page 303 and 304: 7. Chao, D. Y. and D. T. Wang, Appl
Page 305 and 306: 53. Villaroel, J. L., J. Martinez,
Page 307 and 308: q u : the numerator of the least ra
Page 309 and 310: geometric modeling, engineering ana
Page 311 and 312: In dimension driven or parametric d
Page 313 and 314: FIGURE 9.3 configuration of bodies
Page 315 and 316: 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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