ComputerAided_Design_Engineering_amp_Manufactur.pdf

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cycle time and identifies bottlenecks. Because FMS operations may be distributed over a large area, it is difficult to have a global view of the complete system. To simplify the design, debugging, and maintenance, it is necessary to visualize the operations in a central location; there is an urgent need for the graphical modeling and animation of FMS. Our tool XPN-FMS4 integrates modeling, simulation, animation, analysis, and synthesis in one software package. It can model and analyze the performance of an FMS cell based on Petri net theory. Using X-window graphical interface and animation, this software allows modeling and analysis visualization and is easy to understand and manipulate. It lets a user draw the factory layout of an arbitrary FMS cell on screen using the tool. A corresponding Petri net model is deduced (not automatically) from the FMS cell and can be displayed on the screen. It can also display the animated overall operating process of the FMS corresponding to the Petri net model. By experimenting with different inputs and comparing the output in a timed period, a user can quickly determine how to improve the efficiency, reduce the cost, and pin down where the bottleneck is. This software is of practical value for industrial engineers and manufacturing managers. For the PN models of FMS that are decision-free, we exend the theory and algorithm of a unique matrix-based method to search for subcritical loops and to support scheduling and dealing with transition periods. This has been applied to find the optimal input sequence control. Recently, we have simplified the tool to eliminate the codes for animation with slight modifications. A designer can design factory layout using regular “graph” buttons and perform animation and simulations. This helps reduce the effort necessary for the designer to learn to use the tool. Various synthesis approaches1,2,6,8–16,18–22,27–32,34,36,40,41,47,48,50,51,54,55,58–64 have been proposed. According to Jeng, 28 two dominant synthesis approaches are bottom-up and top-down. Bottom-up approaches start with decomposition of systems into subsystems, then construct subnets for subsystems and merge these subnets to reach a final PN by sharing places, 1,42 transitions, 29,31,52 and elementary paths31,32,51 or by linking subnets. 19 Top-down approaches begin with a first-level PN and refine it to satisfy system specifications until a certain level is reached. The stepwise refinement technique by Vallette51 is a top-town approach where transitions are replaced by well-formed blocks. Suzuki and Murata50 generalized this technique, but with the disadvantage of the need to analyze the blocks. Our knitting technique supplements this approach by synthesizing the blocks without analysis. To automate the synthesis, rules must be developed as in Esparza and Silva22 and Datta and Ghosh18,19 to synthesize free-choice (FC) and extended FC (EFC). But they are unable to synthesize asymmetricchoice nets (AC), and one needs to analyze whether the subnet is reducible. 19 Futhermore, they do not have explicit algorithms and the associated complexity. Thus, most techniques do not deal with CAD explicitly. We have devised some simple and yet effective rules to guide synthesis, e.g., for communication protocols58 and automated manufacturing systems. 3,46,48,58 They required no analysis and the synthesized nets constitute an new class of nets that are more general than FC, EFC, and AC. 6 This new class of nets is referred to as the Synchronized-Choice (SC) nets. SC nets possess some interesting properties as they satisfy the following two requirements: 1. If a circuit � has a PT-handle �, � is bridged to � through a TP-bridge B. 2. If a circuit contains a TP-handle, then this TP-handle is bridged to the circuit through a PT-bridge. The knitting technique by the author6,8–15 is a rule-based interactive approach. A net is expanded to N by inserting new paths bearing some physical meaning such as increasing concurrency, alternatives, etc. The generations are performed in such a fashion that all reachable markings in remain unaffected in hence all transitions and places in stay live and bounded, respectively. is live and bounded by making the new paths (NP) live and bounded. This notion is novel compared with other approaches because it aims to find the fundamental constructions for building any PNs. There are two advantages: (1) reduction of the complexity of synthesis as an interactive tool, and (2) providing the knowledge from which the construction of the class of nets may be built. It therefore opens a novel avenue to PN analysis. Due to the simplicity of the rules, it is easily adapted to computer implementation for allowing the synthesis of PNs to be performed in a user-friendly fashion. 2 N 1 N 2 ; N 1 N 2 N 1
A temporal matrix (T-Matrix) is proposed in this chapter to record the relationships (concurrent, exclusive, sequential, … etc.) among the modeled processes. Tracking all the processes and the relationships among processes in large PNs is a difficult task and thus makes the automatic tracking of rule applicability upon generation and the automatic updating of the T-Matrix desirable. The knitting rules are useful for analysis and reduction. For a given PN, we construct its T-Matrix and check mutual relationships among processes against the rules. Any violation spots potential bad designs. The reverse process of removing processes (reduction), according to the rules, should preserve the properties of the PN. Rather than reducing modules to transitions, we remove paths to reduce the PN. We have implemented a reduction algorithm based on the rules; the code is very simple, containing less than 100 lines. In an earlier paper, 6 we proved that the synthesized nets are bounded and conservative based on a linear-algebra technique. This chapter will show that the structural relationships among processes in a PN are identical to the temporal ones. Based on this, we are able to prove the properties of live, reversible, and marking monotonic, but will omit the proof for boundedness. This chapter develops such an algorithm and its X-Window implementation. In addition, the T-Matrix can record self-loops and find maximum concurrency with linear time complexity, which helps for processor assignments. The T-Matrix, however, cannot synthesize certain classes of nets. For instance, there are no ordering of firings among a set of transitions that are exclusive to each other. Sometimes, these transitions must execute one by one. In addition, if the synthesized net is initially safe, it stays safe for any reachable marking. It is marking monotonic, i.e., it will not evolve into a deadlock by adding more tokens. The synchronic distance between any two transitions in a synthesized net is either one or infinite. Certain classes of net will evolve to become unsafe, marking nonmonotonic, and to allow any positive synchronic distance. The above limitation springs from the fact that some generations are forbidden. Allowing the forbidden generations would produce34 new classes of nets. To maintain well-behavedness, new generations must accompany the forbidden generations. Based on this, this chapter develops a set of new rules to generate new classes of nets. First, we remove the restriction of forbidding the generation of new TT-path between two exclusive transitions. We add another new TT-path such that the above two exclusive transitions are sequentialized with synchronic distance of one. These two transitions are both exclusive and sequential to each other—a new temporal relationship, sequentially exclusive, denoted as “SX” or ↑. Second, we extend the rules to general Petri nets where arcs may carry multiple weights. 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 (DSP), 5,7,11,65 etc. We have enhanced the tool to include not only PNs but also 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, and others by just clicking a button. 5,7,11 Section 8.3 formalizes the TT rule and PP rule after the preliminaries in Section 8.2. Section 8.4 deals with the T-Matrix for PNs. Section 8.5 outlines the algorithm for updating the matrix and its time complexity. Section 8.6 discusses the X-Window implementation. Section 8.7 extends the rules to allow forbidden generations between exclusive transitions and GPNs. Its application to an FMS is presented. This section also briefly summarizes other features of the CAD tool. Section 8.8 concludes the approaches presented in this chapter. Notations are provided in the Appendix. 8.2 Preliminaries Terminology A Petri net38–39,43 is a directed bipartite graph consisting of two types of nodes: places (represented by circles) and transitions (represented by bars). Places represent conditions or the presence of raw materials, and transitions represent events. Each transition has a certain number of input and output places
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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.
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 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: include the once forbidden generati
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
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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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