ComputerAided_Design_Engineering_amp_Manufactur.pdf

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Bart O. Nnaji University of Pittsburgh Hsu Chang Liu Solid Works 9.1 Introduction © 2001 by CRC Press LLC 9 Computer-Aided Design Techniques for Development of Automated Product Assembly Systems in Manufacturing Systems 9.1 Introduction 9.2 ProMod: A Concurrent Conceptual and Product Design System for Mechanical Assemblies2 9.3 Computer-Aided Design and Revision 9.4 Design with Saptial Relationships Types of Spatial Relationships • Geometric Interpretation of Spatial Relationships • Product Specification Attributes • Tolerance Propagation and Control 9.5 3-D Variational Geometry Completeness of Dimensions • 3-D Variational Geometry Constraints • Systems of Equations 9.6 Other Researches and Developments Stability Analysis of Assembly • Feasible Approach Directions and Precedence Constraints • Kinematic Modeling with Spatial Relationships 9.7 Conclusion Most CAD modules are developed independently on their applications and run on a specific platform. The complexity of integrating all design modules into an all directions CAD system requires a big investment in both software and hardware and has long been the burden of small-scale companies trying to move from computer-aided drafting to computer-aided design. Recent growth in computer technology development means that computers with higher performance and lower costs have been designed and have become more affordable. Also, by applying network technologies, more and more centralized systems have been broken down into cheaper distributed units. This shared schema has improved the computation speed, increased the memory storage size, and increased communication among end users. The CAD development has also extended its vision from
geometric modeling, engineering analysis, and manufacturing to the design of the life cycle of the product. The life cycle includes, for example, the stages of functional specifications development, conceptual design (Kang, 1996), component design, assembly modeling, and, finally, manufacturing. In most cases, assembly is the most complex process in manufacturing, occupying approximately 50% of total manufacturing cost (Boothroyd, 1995). In order to reduce assembly cost, a designer has to come up with a design that has a minimun number of assembly processes; each assembly process has to be simple so that it can be easily achieved by manual or automatic assembly systems. This requires a great deal of communication between design engineers and manufacturing engineers. The requirements for design engineers have to agree with manufacturing methods. Evaluations have to be iterated between these two systems until an optimal design solution has been reached. In general, design criteria mainly are product specifications and manufacturing methods that can be carried by geometric constraints (Anantha, 1996; Liu, 1991). This information has to be uniformly interpreted and represented throughout the product life cycle. In this chapter, we will introduce spatial relationships (Liu, 1991), a structural representation scheme embedded with geometric information, and nongeometric constraints that carry design criteria. Spatial relationships compose the common language that communicates between design engineers and manufacturing in design considerations. Also in this chapter, we will begin with the introduction of Product Modeler (ProMod) (Nnaji, 1993), a modeling system that applies design with spatial relationships and is able to capture and represent the design evaluation criteria through assembly modeling processes (Nnaji, 1994). This is followed by discussion of subsequent developments in automatic assembly that are listed as follows: • Stability analysis of assembly (Vishnu, 1992) • Feasible approach directions and precedence constraints (Yeh, 1992) • Kinematic modeling (Aguwa, 1997; Prinz, 1994). 9.2 ProMod: A Concurrent Conceptual and Product Design System for Mechanical Assemblies Design process is a refinement of abstract representations where the product functionality, manufacturability, and all other life cycle issues are optimized. Existing computer-aided design systems focus on the design and analysis of components in isolation. Since these design systems are unable to support early conceptual design, a designer’s intentions (i.e., functional and geometric constraints) cannot be captured, represented, and propagated to down-stream activities. The consequence of this inability is that existing design systems are not capable of optimizing the product against life-cycle constraints, thus rendering the effort to integrate design and manufacturing unlikely to bear fruit. In this section, we introduce a new type of mechanical product modeling system, ProMod, (Nnaji, 1993; Rembold, 1991-1; Rembold, 1991-2) which is not only capable of capturing and integrating the designer’s intent at conceptual-design level, but also is capable of propagating these intentions as constraints to guide the development and detailing of product design. Thus early conceptual design and product design are merged in the same computational environment (Kang and Nnaji, 1993). In ProMod, the design process begins with modeling of the abstract representation of the components. While connecting these abstract components, the designer uses spatial relationships as the peg on which to hang the representation of the designer’s intentions. In the initial realization of form, the constraints may be violated. In this case, a refinement process is applied to change the topology and geometry of the components so as to satisfy these constraints. Three subsystems, module design, connectivity design, and detailed design, as shown in Figure 9.1, are the kernel of the ProMod system. The designer uses module design to create an initial design, which may be unique or standardized, and is saved in part library. The connectivity design defines the functional and geometric constraints upon the refinement and configuration of components to meet product specifications. The detailed design contains modeling © 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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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 283 and 284: FIGURE 8.15(f) After entering the a
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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 and 304: 7. Chao, D. Y. and D. T. Wang, Appl
Page 305 and 306: 53. Villaroel, J. L., J. Martinez,
Page 307: q u : the numerator of the least ra
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
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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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