ComputerAided_Design_Engineering_amp_Manufactur.pdf

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53. Villaroel, J. L., J. Martinez, and M. Silva, GRAMAN: a graphic system for manufacturing system design, Proc. IMACS International Symp. on Syst. Model and Simul., Cetraro, Italy, 1988. 54. Wang, D. T., and D. Y. Chao, Enhanced knitting technique to Petri net synthesis, Proc. 1994 IEEE Int’l. Conf. SMC, San Antonio, TX, October 2–5, pp. 658–663. 55. Wang, D. T., and D. Y. Chao, New knitting technique for large Petri net synthesis with automatic preservation of liveness, boundedness and reversibility, (Invited) Proc. 1995 IEEE Int’l. Conf. SMC, Vancouver, Canada, October 22–25, pp. 1460–1465. 56. Wilson, R. G. and B. H. Krogh, Petri net tools for the specification and analysis of discrete event controllers, IEEE Trans. Software Engineering., SE-16, No. 1, 1990, pp. 39–50. 57. Yau, S. S., and Caglayan, Distributed software system design representation using modified Petri nets, IEEE Trans. Software Engineering, SE-9, No. 6, November 1983, pp. 733–745. 58. Yaw, Y., Analysis and Synthesis of Distributed Systems and Protocols, Ph.D. Dissertation, Dept. of EECS, U.C. Berkeley, 1987. 59. Yaw, Y., C. V. Ramamoorthy, and W. T. Tsai, A synthesis technique for designing concurrent systems, Second Parallel Processing Symposium, April 1988, pp. 143–166. 60. Yaw, Y., C. V. Ramamoorthy, and W. T. Tsai, Synthesis rules for cyclic interactions among processes in concurrent systems, Proc. COMSAC Symp., October 1988, pp. 496–504. 61. Yaw, Y. and F. L. Foun, The algorithm of a synthesis technique for concurrent systems, Proc. 1989 IEEE Int’l. Workshop on Petri Nets and Performance Models, Tokyo, pp. 266–276. 62. Zhou, M. C. and F. DiCesare, Parallel and sequential mutual exclusions for Petri net modeling for manufacturing systems with shared resources, IEEE Trans. on Robotics and Automation, RA-7 No. 4, 1991, pp. 515–527. 63. Zhou, M. C., F. DiCesare, and A. A. Desrochers, A hybrid methodology for Petri net synthesis of manufacturing systems, IEEE Trans. on Robotics and Automation, RA-8, No. 3, 1992, pp. 350–361. 64. Zhou, M. C., K. McDermott, and A. Patel, Petri net synthesis and analysis of a flexible manufacturing systems cell, IEEE Trans. SMC, Vol. 23, No. 1, March 1993, pp. 524–531. 65. Chao, D. Y., Final-matrix based and fast implementation of recurrent DSP scheduling, Proc. ICSPAT ’96/DSP World Expo, Boston, October 1996, pp. 171–175. 66. Chao, D. Y., A CAD tool for network simulation based on a protocol design CAD tool, Proc. ICSPAT ’96/DSP World Expo, Boston, October 1996, pp. 836–840. 67. Heemstra, S. M. et al., Range-chart-guided iterative data-flow graph scheduling, IEEE Trans. Circ. Syst., CAS-39, No. 5, 351–364, 1992. Appendix A ab : entries of stucture matrix a� jj1 : the weight on the arc from pj to tj1 AC: asymmetric-choice nets AGV: automatic guided vehicles �: the total number of final PSPs in the final system �: the total numbr of nodes in the final system B: a bridge CL (o): cyclic C: local concurrent set Cik : LCN ( �i, �k) CT : the set of control transitions CN (�): concurrent d: synchronic distance d : structure synchronic distance DEP: directed elementary path DFG: data flow graph s
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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
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6. C. A. Beatty, Tall Tales and Rea
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A.Y.C. Nee National University of S
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FIGURE 7.1 Planning, design, and ma
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A metal stamping can have the follo
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FIGURE 7.3 Strips used to notch out
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A Skeletal Approach for the Recogni
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These findings can be used to devel
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Semi-Direct Piloting In cases where
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a larger value, the die operations
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FIGURE 7.9 Symbolic relationship be
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FIGURE 7.11 The shape of the envelo
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TABLE 7.1 Schema for the Generation
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strong reasons to support a move to
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FIGURE 7.16 3-D CAD model of a part
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References Cheok, B.T. et al. (1994
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include the once forbidden generati
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A temporal matrix (T-Matrix) is pro
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FIGURE 8.1 A basic process. (From R
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FIGURE 8.4(a) Generate a new IG usi
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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
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: 7. Chao, D. Y. and D. T. Wang, Appl
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
Page 317 and 318: FIGURE 9.8 Intersection of degrees
Page 319 and 320: will introduce a way to propagate p
Page 321 and 322: Completeness of Dimensions Complete
Page 323 and 324: FIGURE 9.12 3-D constraints. © 200
Page 325 and 326: The distance constraint from pt �
Page 327 and 328: therefore: Now merge the lists and
Page 329 and 330: Quantity analysis methods have the
Page 331 and 332: y a revolute joint. By selecting al
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