ComputerAided_Design_Engineering_amp_Manufactur.pdf

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FIGURE 9.1 ProMod. functions that modify model geometry in order to meet constraints issued from connectivity design; it also allows designers to create new geometry or modify the existing geometry manually. Module and detail design are the application of conventional CAD modeling techniques. Module design uses CAD to develop an initial design. Detail design uses CAD to modify the initial design in order to satisfy connectivity constraints. We will have a general discussion of CAD modeling techniques, followed by the introduction of methods to modify geometry. 9.3 Computer-Aided Design and Revision Computer-aided design has taken the place of drafting boards, design analysis tools, and prototyping. It has been designed to replace each single module in the design processes. The integration of CAD modules faces the same problem as bridging the communication gap between design and process engineers: a common language is required to represent CAD data and to constrain the data to satisfy all the engineering requirements. In this section, we will introduce modeling techniques that are used to build, as well as to modify, in order to satisfy the design constraints. The least design and revision requirement is ‘‘undo process.’’ Primitive operations are adopted by modern CAD modeling systems to construct a design; they use Eular operator to build topology, which is a reversible process. Primitive operation can be applied to modeling methods ranging from boundary construction, Boolean, sweeping, rounding, etc. A design can be modified locally without changing topology, such as lifting of a vertex, edge, face, or feature. Any change made by Boolean operation will cause change in both geometry and topology, e.g., using a cutting plan to cut away geometry, adding/removing material from Boolean of two bodies. These alteration methods may achieve design requirements, but cannot be uniquely represented and thus cause difficulty in automation. © 2001 by CRC Press LLC
In dimension driven or parametric design systems (Lin, 1983; Serrano, 1984), dimensions are registered along with modeling operations. The design revision process is to override existing dimension value, and then remodel by repeating modeling operations with the new dimension value. This revision method requires recorded modeling history. Dimensions and parameters in parametric design are determined by designers during the component construction stage. These dimensions or parameters may not meet design constraints, so the modeling construction dimensions will be different from the dimensions shown on final drawings. This is also a burden for automatic revision, which requires manual interpretation of the relation between design constraints and model construction dimensions and parameters. In the next section, we will explain how design with spatial relationships can be used for connectivity design and followed by 3-D variational geometry, an assembly-based, constraints-modeling system. In this system, the parametric dimensions used for geometry revision are derived from design specifications so that the revision processes are independent of modeling history. This will allow design or manufacturing engineers to add constraints with specific considerations to the product, to modify design without violating existing constraints, and, thus, to communicate the designer’s intent through constraints. 9.4 Design with Spatial Relationships Today, researchers focus on bridging the gap between product design and manufacturing. The major obstacle to this is the lack of communication among designers, process planners, and inspectors. It is impractical to require that designers possess knowledge of both design and manufacturing. Design engineers tend to ignore the manufacturing and other product life-cycle requirements. Manufacturing engineers are sometimes forced into modifying a design or the manufacturing environment because their requirements were not captured as constraints in the design. In order to link design and manufacturing processes automatically, a common product’s specifications must be carried from the beginning of design to the final stage of inspection. For example, Figure 9.2(a) shows a product with two parts: one is a plate P, with two holes, and the other one is a bent shaft, S. Figure 9.2(b) shows the features of the two parts in Figure 9.2(a). The features of part P are extracted and classified as a Cvex_block_base, C_hole1, C_hole2, Fillet1, and Fillet2. We have C_shaft1, C_shaft2, and Elbow features for part S. In Figure 9.2(c) and (d), the product is made by snapping C_shaft1 of S into the C_hole1 of P. Traditionally, these mating criteria are annotated in engineering drawings, but this requires trained humans to create and interpret the notes. Also, certain questions arise here, such as 1. How are the specifications of components precisely determined from the product specifications? 2. Can these specifications be represented efficiently? 3. Can existing design procedures be simplified and automated? In Figure 9.2(c), the plate and bent shaft are assembled with the geometric constraint that the shaft is inserted, not completely, but with Da � ta offset from the tip of the shaft to the bottom of the plate and with the other side of the shaft having Db � tb offset with the plate. There are three general stumbling blocks to assembly evident in this assembly process that involve snapping two components together: 1. It is difficult to specify how deep the C_shaft1 should go along the length of C_hole1 during individual part modeling. 2. The tolerance specification of �tb has to be manually distributed to tolerance of �tc of part P and �td of part S as shown in Figure 9.2(d). 3. The resultant tolerance �tc and �td should be equal to �tb. These issues are the drawbacks of conventional modeling systems that are made for design and machining of individual parts and do not consider the general specifications of a product. In this chapter, we apply the fact that an assembly model can represent more information than an individual part model and product specifications can be captured during the stage of assembly. Once © 2001 by CRC Press LLC
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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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Note if the pair of nodes are both
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TABLE 8.1 Summary of the Rules Cond
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The correctness of these rules is e
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Page 263 and 264: Π1 Π3 Π4 FIGURE 8.8(a) After add
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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
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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: geometric modeling, engineering ana
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
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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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