ComputerAided_Design_Engineering_amp_Manufactur.pdf

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FIGURE 5.6 Interaction of various elements in computer-aided process planning (CAPP). MRIR: manufacturing resources internal representation; PDIR: part design internal representation; PPIR: process plan internal representation. 5.6 Part Modeling for CAPP One of the problems concerning the automation of the process planning function is that of high input effort needed to describe a part. The reason can be attributed to the fact that the experience and knowledge of humans play a prominent role in interpreting and communicating the part data in a manufacturing system. The translation of the part data from human-interpretable format to computer-interpretable format is complex, but mandatory input for CAPP. Part modeling, through which a complete and unambiguous definition that captures the design content of the part is to be achieved, has become one of the key research issues since the inception of CAPP. There exist three basic sets of data which completely describe the design content of a part: • Geometrical data: The geometrical data give the basic description of the shape. For ex<strong>amp</strong>le, diameter of a hole, depth of a groove, width of a keyway, etc. constitute this type of data. • Technological data: The information pertaining to tolerances and surface finish can be referred to as technological data, e.g., circularity, diametrical tolerance, runout, etc. • General (or global) data: Certain global characteristics that are applicable to the part as a whole are often added to the design specification. These global attributes include quantity to be produced, work material, design number, part name, and other task-dependent details which normally appear on the drawing and the process plan. Representation of Geometrical Details There are many methods followed for part modeling as a part of CAPP system development. These can be categorized as (1) non-CAD models, (2) CAD models, and (3) feature-based models. Non-CAD Models These modeling methods are characterized by the absence of CAD systems. These can be classified as • Group technology (GT) coding which is based on GT coding schemes for the retrieval of existing process plans. Detailed process plans for several part families are developed and stored in the system’s data base. The major characteristics of the new part are matched with a similar part and
the previously stored process plan is retrieved. The retrieved process plan can then easily be modified to suit the new part. • Interactive/menu driven models which pose a series of questions (or menus) and interactively gather the part data from the user. Studying the product range and variation is essential before designing system-user interaction. Although it seems to be simple to answer such questions, the user may not have control over the way in which the system interacts with him, and hence he is compelled to navigate through a series of redundant questions to define even a simple part. This approach is limited to only simple parts and is characterized by the absence of graphic interface. • Keywords/description languages which can provide detailed information for CAPP systems. The output format of the part data can be designed such that the process planning function can easily accomplish its task. This approach offers limited flexibility to the user in the sense that the user can exercise some control over the system, but, because of its specialized nature, it is limited to simple parts. For complex parts, the translation of the original design to input language can be very tedious. Sometimes the resultant model may not be unique and the sequence with which a part is modeled may affect the planning logic. CAD Models Although the modeling methods discussed so far provide alternate solutions for linking design to manufacture, the main problem of generating the part data from a CAD data base is still largely unresolved. The increased use of CAD and the need to integrate it with CAM has led to the use of the internal CAD model as a means of driving the process planning function. Much of the information needed in the design and manufacturing functions is directly related to the geometric shape of the part. This observation has led to the interest in geometric modeling, with the hope that a solution for the geometrical aspects of product modeling will form the basis for producing effective CAD/CAM systems. Present CAD/CAM Systems can be regarded as the logical outcome of this approach. Unfortunately, the information stored in the CAD models is in terms of points, lines, arcs, and solids; as such it is not structured to facilitate CAPP. The gap in the abstraction levels of CAD and CAM domains needs to be bridged to obtain integrated CAD/CAM systems (Wright and Hannam, 1989). CAD systems also lack suitable facilities to associate tolerance information and other applicationbased data (non-geometrical) to the part model. The information in these models is incomplete and low level in nature (Shah and Rogers, 1988b). Hence such models cannot be used directly without further processing for manufacturing applications like CAPP. Another major problem with these modelers is that they allow a very restricted set of operations on the model. All operations must be expressed as Boolean operations. The primitives customarily supported in solid models do not easily lend themselves to the specification of user-definable features. This is particularly true for compound features such as stepped holes, pockets, etc. The steps involved in describing such features may be quite complex. Sometimes the model created by the solid models may not be unique because a part constructed by subtraction of operations can also be created using the corresponding union operations (Joshi et al., 1986). Absence of such uniqueness in part representation may severely affect the subsequent process planning logic. Sometimes, a part represented in a CAD system may not be manufacturable. Hence, it is essential to have modeling systems that can check the design for manufacturability (DFM) and geometrical validity of the parts. Feature-Based Models In order to overcome the above limitations, the concept of using form features (shape elements) for part modeling received the attention of researchers. It is perhaps fair to state that the concept of features was first introduced by researchers in the process of linking design, and manufacturing.
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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
Page 89 and 90: FIGURE 3.8 The vertical support fix
Page 91 and 92: and moments about the contact point
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Page 95 and 96: one of choosing the variables: such
Page 97 and 98: Fixture Module Location An importan
Page 99 and 100: FIGURE 3.15 Illustration of functio
Page 101 and 102: FIGURE 3.18 Minimum separation test
Page 103 and 104: direction) the face, respectively.
Page 105 and 106: FIGURE 3.21 Software structure for
Page 107 and 108: 3.8 Conclusion A reconfigurable fix
Page 109 and 110: Heui Jae Pahk Seoul National Univer
Page 111 and 112: FIGURE 4.1(b) Conceptual framework
Page 113 and 114: 4.3 Measurement Points Sampling and
Page 115 and 116: Surface S2 Measurement Path FIGURE
Page 117 and 118: FIGURE 4.4 Rough phase alignment ba
Page 119 and 120: deviation between the nominal CAD d
Page 121 and 122: FIGURE 4.6(a) Sum of squares distan
Page 123 and 124: FIGURE 4.7(c) Trailing edge. (c) th
Page 125 and 126: FIGURE 4.8(a) Profile tolerance of
Page 127 and 128: The calculated minimum form error i
Page 129 and 130: FIGURE 4.11(a) A typical mold havin
Page 131 and 132: FIGURE 4.11(d) Inspection results f
Page 133 and 134: FIGURE 4.12(c) Maximum deviation (p
Page 135 and 136: 5.1 Introduction Developments in th
Page 137 and 138: process plan for a part (Figure 5.3
Page 139: FIGURE 5.5 leading to the developme
Page 143 and 144: FIGURE 5.7 Techniques of defining a
Page 145 and 146: Feature Recognition and Extraction
Page 147 and 148: in relation to another feature (e.g
Page 149 and 150: FIGURE 5.9 Framework for building a
Page 151 and 152: FIGURE 5.10 Process plan content.
Page 153 and 154: FIGURE 5.12 Schematic sketch of the
Page 155 and 156: Several techniques of defining a fe
Page 157 and 158: TABLE 5.1 Data Structure for Repres
Page 159 and 160: FIGURE 5.16 Classification of the t
Page 161 and 162: system to ensure that the part bein
Page 163 and 164: FIGURE 5.19 Graphical model of the
Page 165 and 166: TABLE 5.4 Data Structure for Repres
Page 167 and 168: FIGURE 5.20 Mapping between machini
Page 169 and 170: algorithms. (Some details of the pr
Page 171 and 172: FIGURE 5.24 An example rotational p
Page 173 and 174: FIGURE 5.26 Down_face-turn-up_face
Page 175 and 176: FIGURE 5.27 Procedure for machine t
Page 177 and 178: FIGURE 5.28 Determining the number
Page 179 and 180: DL is needed to be set only if the
Page 181 and 182: FIGURE 5.31 Operation sequencing co
Page 183 and 184: Cutting Tool Selection Selection of
Page 185 and 186: 1. A tool is searched for in the da
Page 187 and 188: FIGURE 5.32 Inputs to optimization
Page 189 and 190: 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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needs to show that after each full
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ule is violated, a warning should b
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Π1 Π3 Π4 FIGURE 8.8(a) After add
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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
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A ik � ‘U’ and is in a cycle
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FIGURE 8.12(a) Add [p2 t7 p7 t8 p4]
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FIGURE 8.12(c) Add a token to p8 vi
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FIGURE 8.12(e) Add [p8 t9 p14 t10 p
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FIGURE 8.13 An example of rule TT.0
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FIGURE 8.14 A GPN model of a machin
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FIGURE 8.15(b) The first exclusive
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FIGURE 8.15(d) The last exclusive T
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FIGURE 8.15(f) After entering the a
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FIGURE 8.15(h) Completion of Compon
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FIGURE 8.15(j) Two PP-generations:
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FIGURE 8.15(l) The last exclusive T
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t1 t5 p1 p5 t6 (a) t2 t3 t4 2 2 p2
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FIGURE 8.17 An example of partial f
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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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