ComputerAided_Design_Engineering_amp_Manufactur.pdf

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D. Inference Engine for Expert Systems: This allows both forward and backward chaining. 11 Coding and the associated compilation are not required, thus avoiding grammatical and typographical errors. In addition, the user can easily modify the designed inference network in a graphical fashion. An example of the inference network for car diagnosis has been demonstrated. Rules can be represented by transitions and preconditions, or symptoms can be represented by tokens in places. Clicking the “Auto” button of the “Simulate” submenu of the “Analysis” menu fires the production rules (transitions) and, when the firing terminates, the places holding tokens indicate the cause of the problem. 8.9 Conclusions The tool, based on the synthesis rules and the algorithm, helps designers to construct large PNs interactively and to synthesize an automated manufacturing system in a user-friendly fashion. None of the existing tools integrate drawing, file manipulation, analysis, simulation, animation, reduction, synthesis, and property query in one software package. Furthermore, because PNs model discrete-event systems, the tool finds applications in communication protocols, flexible manufacturing systems, (extended) finite state machines, expert systems, interactive parallel debuggers, 11 digital signal processing, 5,7,11 etc. We have enhanced the tool to include models not only of PNs but also of state diagrams and data flow graphs (DFGs) with few code changes. Thus a designer can choose the model with which he is familiar. For instance, DSP professionals do not know PNs well. They can, however, draw DFGs and obtain iteration bounds, critical loops, rate-optimal scheduling, etc. by just clicking a button. 4,5,65 We have also implemented a reduction algorithm based on the rules; the code is very simple, containing less than 100 lines. The distinct point of this approach is that, besides the possibility of continuous enhancement, while reducing, it can discover wrong designs and suggest how to fix the problem based on the knitting rules. This work overcomes some drawbacks of most existing synthesis approaches; i.e., they do not • Deal with the algorithm and CAD tool using graphical user interface for synthesis explicitly • Show how to continuously update their synthesis techniques • Indicate how to extend the synthesis for analysis • Show temporal relationships among processes after synthesis • Find the maximum concurrency of the synthesized net. References 1. Agerwala, T. and Y. Choed-Amphai, A synthesis rule for concurrent systems, Proc. of Design Automation Conference, 1978, pp. 305–311. 2. Berthelot, G., Checking properties of nets using transformations, in Advances in Petri Nets, G. Rozenberg (ed.), 1985, Springer-Verlag, pp. 19–40. 2a. Chao, D.Y., Application of a synthesis algorithm to flexible manufacturing systems, Journal of Information Science and Engineering, Vol. 14, No. 2, June 1998, pp. 409–477. 3. Chao, D. Y. and D. T. Wang, Synchronized choice ordinary Petri net, (Invited) Proc. 1995 IEEE Int’l Conf. SMC, Vancouver, Canada, October 22–25, pp. 1442–1447. 4. Chao, D. Y. and D. T. Wang, XPN-FMS: A modeling and simulation software for FMS using Petri nets and X windows,” International Journal of Flexible Manufacturing Systems, Vol. 7, No. 4, October 1955, pp. 339–360. 5. Chao, D. Y. and D. T. Wang, Iteration bounds of single-rate data flow graphs for concurrent processing, IEEE Trans. Circuits Syst., CAS-40, No. 9, September 1993, pp. 629–634. 6. Chao, D. Y. and D. T. Wang, Two theoretical and practical aspects of knitting techniques—invariants and a new class of Petri net, IEEE Trans. SMC_27, No. 6, December 1997, pp. 962–977.
7. Chao, D. Y. and D. T. Wang, Application of final matrix to data flow graph scheduling using multiprocessors, MIS Review, Vol. 5, December 1995, pp. 65–80. 8. Chao, D. Y. and D. T. Wang, X-Window implementation of an algorithm to synthesize ordinary Petri nets, Journal of National Cheng Chi University, Vol. 73, October 1996, pp. 451–496. 9. Chao, D. Y., M. C. Zhou, and D. T. Wang, Extending knitting technique to Petri net synthesis of automated manufacturing systems, The Computer Journal, Oxford University Press, Vol. 37, No. 1–2, 1994, pp. 1–10. 10. Chao, D. Y. and D. T. Wang, A synthesis technique of general Petri nets, J. Systems Integration, Vol. 4, No. 1, 1994, pp. 67–102. 11. Chao, D. Y. and D. T. Wang, An interactive tool for design, simulation, verification, and synthesis for protocols, Software-Practice and Experience, an International Journal, Vol. 24, No. 8, August 1994, pp. 747–783. 12. Chao, D. Y. and D. T. Wang, Petri net synthesis and synchronization using knitting technique, Proc. 1994 IEEE Int’l Conf. SMC, San Antonio, TX, October 2–5, pp. 652–657. 13. Chao, D. Y. and D. T. Wang, Knitting technique and structural matrix for deadlock analysis and synthesis of Petri nets with sequential exclusion, Proc. 1994 IEEE Int’l Conf. SMC, San Antonio, TX, October 2–5, pp. 1334–1339. 14. Chao, D. Y. and D. T. Wang, Knitting technique with TP-PT generations for Petri net synthesis, (Invited) Proc. 1995 IEEE Int’l Conf. SMC, Vancouver, Canada, October 22–25, pp. 1454–1459. 15. Chao, D. Y. and D. T. Wang, Linear algebra based verification of well-behaved properties and Pinvariants of Petri nets synthesized using knitting technique, MIS Review, Vol. 5, December 1995, pp. 27–48. 16. Chen, Y., W. T. Tsai, and D. Y. Chao, Dependency analysis—a compositional technique for building large Petri net, IEEE Trans. on Parallel and Distributed Systems, PDS-4, No. 4, 1993, pp. 414–426. 17. Chu, W. W. and K. K. Leung, Task response time model and its application for real-time distributed processing systems, Proc. 1984 IEEE Real Time Syst. Symp., pp. 225–236. 18. Datta, A. and S. Ghosh, Synthesis of a class of deadlock-free Petri nets, Journal of ACM, Vol. 31, No. 3, 1984, pp. 486–506. 19. Datta, A., Modular synthesis of deadlock-free control structures, in Foundations of Software Technology and Theoretical Computer Science, G. Goos and J. Hartmanis, (eds.), Springer-Verlag, Vol. 241, 1986, pp. 288–318. 20. Dong, T., The Modeling, Analysis, and Synthesis of Communication Protocols, Ph.D. Dissertation, Computer Science Division, EECS. 21. Esparza, J. and M. Silva, Circuits, handles, bridges, and nets, in LNCS, Advances in Petri Nets 1991, Springer-Verlag, pp. 210–242. 22. Esparza, J. and M. Silva, On the analysis and synthesis of free choice systems, in LNCS, Advances in Petri Nets 1991, Springer-Verlag, pp. 243–286. 23. Huang, J. P., Modeling of software partition for distributed real-time application, IEEE Trans. on Software Eng., SE-11, October 1985, pp. 1113–1126. 24. Hyung, L-K. and J. Favrel, Analysis of Petri nets by hierarchical reduction and partition, in IASTED Modelling and Simulation, Acta Press, Zurich, Switzerland, 1982, pp. 363–366. 25. Hyung, L-K. and J. Favrel, Hierarchical reduction method for analysis of decomposition of Petri nets, IEEE Trans. Syst., Man, Cybern., SMC-15, No.2, March 1985, pp. 272–280. 26. Hyung, L-K., Generalized Petri net reduction method, IEEE Trans. Syst., Man, Cybern., SMC-17, No. 2, 1987, pp. 297–303. 27. Koh, I. and F. DiCesare, Modular transformation methods for generalized Petri nets and their application to automated manufacturing systems, IEEE Trans. Syst., Man, Cybern., SMC-26, No. 6, 1991, pp. 1512–1522. 28. Jeng, M. D. and F. DiCesare, A review of synthesis techniques for Petri nets with applications to automated manufacturing systems, IEEE Trans. Syst., Man, Cybern., SMC-23, No. 1, 1993, pp. 301–312.
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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
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
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: • Programming logic and VLSI arra
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
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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