ComputerAided_Design_Engineering_amp_Manufactur.pdf

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TT. 3 must be used upon the generation [t16 p20 t12] from Component II to I, to generate another TTpath [t11 p21 t17] from Component I to II. In Figure 8.15(b), the message box tells us that it is an exclusive TT-generation and we should pick a brown node and a purple node for the generation point and joint, respectively. In Figure 8.15(c), the message box tells us that we are in the midst of the exclusive TT generation and a cycle has not been formed. In Figure 8.15(d), the message box tells us that we reach a cycle and we should enter tokens in it. When we generate the first exclusive TT-path, the firing ratio between tg (t4) and tj (t1) is 1/1, and so too is the next TT-generation between t2 and t6. Because of the exclusive TT-generations, the lesat home ratios at this step must be expressed relative to t4 rather than to the home place p1. Afterwards, we enter 2 tokens to p9 since its upper variable is 2 via the “Modify” button. In the last exclusive TT-generation, the arc weight between p8 and t8 is 2, the least home ratio at t8 is 1/2, which implies that in order to fire t8 once, t4 must fire twice. Now the next arc weight between t8 and p9 is 2; hence, the least home ratio at p1 is 2/2, implying that after t4 fires twice, p9 will get two tokens. Finally, the last arc weight between p9 and t3 is 1; hence, the least home ratio at t3 is 2/2, as well as at t4. Since we insert tokens at the new home place, p9, whose least home ratio is 2/2, we need to insert at least two tokens; i.e., n � 2. Figure 8.15(f) shows the least home ratios for all nodes in the cycle in reference to t4. After entering two tokens at p9, the least home ratio will be recomputed in reference to p9 rather than to t4 (Figure 8.15(g)). Similar statements apply to the synthesis of Component II. We insert 3 tokens at p18 (Figure 8.15(k)) whose “upper” variable equals 3; hence, m � 3. Note that the requirement in Rule ARR.1.a (i.e., equal prime ratio along any paths between two nodes) does not hold for exclusive TT-generations. There are two different paths from p15 to t13 [p15 t13] and [p15 t17 p17 t18 p18 t13] with different prime ratios of 1/1 and 3/1, respectively. As a matter of fact, there may be two different least-home-ratios for all tg and tj that are involved in an exclusive-TT generation. In this case, the tool will display the one that is relevant to the current generation. In Figure 8.15(h), we generate a PP-cycle [p8 t9 p10 t10 p11 t12 p12 t11 p8] followed by a backward TT-generation [t10 p13 t8]. The least ratios in reference to p8 are displayed for nodes in the PP-cycle. Note that the new ratio for p8 in reference to itself is 2/2 indicating that p8 must have at least two tokens in order to complete the firings of all transitions in the PP-cycle. This, in turn, implies that t3 must fire at least twice. However, we do not need to update the ratio at t8 since its lower is no smaller than 2, which implies that the least amount of firings of t3 (the reference node) for t8 to fire at least once remains at 2. In Figure 8.15(k), we perform two successive exclusive TT-generations and generate another TT-path between two separated components; a message is shown in the bottom window to warn us about the potential problem of unboundedness and remind us that we can create another path from t12 to t16. In the next step (Figure 8.15(1)), we generate another TT-path to synchronize the two components (see the message in the bottom window) and complete the cycle for the exclusive TT-generations. 8.8 Other Features of the Tool The tool can apply to many fields as Petri nets are a powerful modeling and analysis tool for • Distributed operating systems, • Distributed data base systems, • Concurrent and parallel processes, • Flexible manufacturing/industrial control processes, • Discrete event systems, • Multiprocessor systems, • Data flow computing systems, • Fault-tolerant systems,
• Programming logic and VLSI arrays, • Communication networks and protocols, • Neural networks, • Digital filters, and • Decision models. However, in most of these applications, a different graphical model is used instead, such as data flow for digital signal processing and state diagrams for communication protocols. As a result, it is desired that the tool can also draw and analyze these graphical models. The tool has been enhanced in this respect: for rapid development, the tool converts these graphs into Petri nets internally for analysis. Therefore, there is no need to develop new algorithms and codes for each type of graph. Features of the tool include: A. Data Communication: We have developed a very powerful CAD tool for designing protocols and Petri nets. 11 Currently, the tool is able to draw Petri nets, state diagrams, data flow graphs, finite state machines, and general graphical objects. Once the graph is drawn, the tool can analyze, simulate, reduce, and synthesize it. Few existing tools are capable of such an integration. The tool has been enhanced to synthesize error-recovery protocols with great time-complexity reduction, simulate extended finite state machines, hierarchically model and simulate Petri nets, automatically generate “C” codes, and generate unique I/O (UIO) conformance test patterns. We are extending the tool to • Simulate queuing networks, • Software engineering for protocol design implementation and documentation, • Advanced synthesis and reduction of communication protocols using PN, • Implementation of synthesis of local entities, • Complexity reduction in synthesizing multiparty protocols, and • Animation of protocols with real objects. B. Network Simulation: We66 have enhanced our protocol design tool for object-oriented simulations. After drawing network objects and interconnecting them, we can perform simulation. The “Step” mode allows easy debugging and detailed trace of network behavior, which is useful for computer-aided education. To illustrate, we have applied the tool to the bitonic sorting part of the Batcher-bayan network. Automatic code generation helps produce efficient “C” code for non-X-Window environments after verification via simulation. C. Parallel Processing: The above tool has been extended65 to analyze and simulate performance of DFGs. It incorporates a unique, efficient algorithm that we developed to do rate-optimal steady state scheduling without initial transients. We have extended the tool to draw multiple rate DFGs and simulate. It can find critical and subcritical loops and perform rate-optimal scheduling. The user can randomly pick a node to check its input and output values against its functional type after the simulation. The critical loops, scheduling ranges, and processor assignments can be displayed in a graphical fashion. It can also display critical paths and Gann charts for DFGs without any loops. Few tools are capable of such integration and ease of use. The final matrix theory developed is the first of its kind and is used throughout the design. It calculates the iteration bound, finds critical loops, derives formulas for scheduling ranges, and performs a fast processor assignment with rate-optimal scheduling. This eliminates the need for inequality charts for finding the scheduling ranges by Heemstra et al. 67 Most approaches repetitively update scheduling ranges (which is very time consuming), and our theory can eliminate many of these updates. Benchmark testing indicates remarkable (thousandfolds) speedup of scheduling, especially for large DFGs that take less than 1 second compared with other approaches that take several hundred seconds. In addition, the resulting scheduling needs fewer numbers of processors than other approaches. The theory has been updated to include the case of resource constraints and iteration periods greater than iteration bounds.
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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
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
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: t j than the lower at , it indicate
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
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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