ComputerAided_Design_Engineering_amp_Manufactur.pdf

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FIGURE 5.17 Interfeature and intrafeature tolerances. 1. Modeling the global data: Defining this type of data is simple. On issuing a command GLOBAL, the system poses a series of questions with default values enclosed. A set of commonly applied global data is always kept in a system file. If the global data are not specified during a modeling session, then the default values stored in the system file are attributed to the part. So, it is at the user’s discretion whether to define these data or not. 2. Modeling the geometrical data: First, the user has to specify the overall length and diameter of the part. Based on these dimensions, the system automatically scans the blank data base for selecting the blank dimensions. Then the external features are defined, starting from left to right, followed by the internal features. Defining the geometrical data of a feature involves the execution of a related command. Simple commands like TURN, GROOVE, etc. are provided to get the geometry of the feature (in terms of length, diameter, width, depth, etc.). A macro, which invokes the system-user interaction to gather the necessary data, is provided for each command. The details given by the user are then stored in the part file. 3. Modeling the technological data: Technological attributes like surface finish, form tolerances, and relational tolerances can be defined at any time, wherever necessary, for the completion of the part modeling. 4. Intrafeature data: A set of commands (such as DIATOL, FINISH, etc.) for attributing intrafeature data to various features are invoked only on the user’s request. The execution of any of these commands involves the selection of a feature and the specification of the attribute. The selected feature is then located in the part file and the attribute is stored in a proper field of the feature record. 5. Interfeature data: Several commands like LENTOL, RUNOUT, etc. are provided to define interfeature data. The execution of these commands essentially involves the selection of two features. The primitive features of the selected form feature will then be indexed based on the proximity of the primitives to the selection point. Once the definition of interfeature data is complete, the relationship will be appended to the file in which information pertaining to relational tolerances is stored. 6. On-line validation of the modeling process: The primary requirement of a part modeling system is to provide a valid model to the downstream CAPP system. Some procedures are built into the
system to ensure that the part being modeled is sensible, geometrically feasible and within the scope of the manufacturing system. Some of these are • Feature configuration file (FCF): For each feature, the extreme limits in geometric attributes are recorded in a feature configuration file. This file is referred to by the system during its run time to ensure that the features being defined are within limits. • Interference checking: Care is taken to ensure that only feasible components can be modeled in the environment. For example, at any instant of the modeling, (a) the external envelope of the component must not exceed the blank envelope; (b) the internal envelope must be contained within the external envelope; and (c) the internal-left and the internal-right features must not cross each other (or overlap). • Geometrical feasibility: While modeling a part, the features and their combination must be geometrically feasible. For example, (a) some features cannot be repeated successively (a “turn” followed by a “turn” feature is not allowed); (b) an external groove cannot be the first feature; (c) a groove or face must exist between the features turn and thread; and (d) the external contour must be continuous and closed. These restrictions also lead to the compact process planning algorithms. Each time the user tries to make a feature, the system examines whether previously defined features satisfy the pre-conditions. To demonstrate the modeling capabilities of Turbo-Model, an example part shown in Figure 5.18 is considered. The graphical modeling of the part is shown in Figure 5.19. The PDIR of the part is given in Table 5.3. 5.11 Data-GIFTS: Modeling Manufacturing Resources in GIFTS Earlier it was explained why the information pertaining to the manufacturing resources must be maintained as a separate data base external to the main CAPP system. The preparation of the data bases (MRIR) is one of the most time consuming tasks. The data structures for machine tools, cutting tools, inspection gauges, jigs, fixtures, materials, etc. are formulated after several consultations with a few manufacturing industries. The data structure for representing the machine tools is shown in Table 5.4. Along similar lines, representation schema for other manufacturing resources are designed. Data-GIFTS is then developed for managing these resources through a menu-driven interface. The execution of Data-GIFTS is essentially required when installing the CAPP system for the first time. Afterwards, it is required to run this module only when there is a change in status of the manufacturing resources such as addition/deletion of machine tools, cutting tools, etc. Once Data-GIFTS is installed, all the data bases of MRIR will be ready for subsequent use by the other modules of GIFTS and will be frequently referred to in various stages of planning such as selection of machines, tools, setups, operations and sequences, etc. 5.12 Modeling of Process Plan in GIFTS In Section 5.8, the model for PPIR is explained. This section discusses how the elements of PPIR set comprising machine, setup, pocket and parameters are represented in GIFTS. Machine Once the machine is selected, it can be referred to by its number/code used on the shop floor. Some details of the machine such as power, permissible range of speeds and feeds, etc. are necessary for making subsequent planning decisions. Since the manufacturing resources are separately modeled
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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
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 and 140: FIGURE 5.5 leading to the developme
Page 141 and 142: the previously stored process plan
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: FIGURE 5.16 Classification of the t
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,
Page 191 and 192: Usually, maximum and minimum speed
Page 193 and 194: 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
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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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