ComputerAided_Design_Engineering_amp_Manufactur.pdf

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The machining sequence derived from these guidelines is stored in a list, which is referenced while sorting the pockets belonging to the same setup. 3. Pocket level: At this level, the pockets belonging to the same setup and same operation are sorted based on their relative position to each other. It may happen that a pocket can be accessed only after machining a pocket lying above (or below, in the case of internal pockets). The relative position of the pockets can be measured with respect to the blank surface or the central axis of the rotational part. In this way, it is ensured that the top pockets are machined before the hidden pockets are made available for the subsequent machining (Figure 5.31c). Pocket Sorting Procedure An operation sequencing procedure is developed to sort the pockets as explained above. This procedure, which makes use of the setups, operations_list and pocket details, is presented below: setup_no � 1; repeat {setup loop} i � 1; repeat {operation loop} j � 1; open the pocket_file repeat {pocket loop} read pocket; if pocket.setup � setup_no and pocket.operation � operation_sequence[i] then begin partial_list[j] � pocket; j � j � 1; end; until end of the pockets; {end pocket} sort partial_list on pocket position store partial_list in the sort_file i � i � 1; until operation_sequence[i] � null; {end operation} setup_no � setup_no � 1; until end of setups {end setup} pocket_file � sort_file. {PPIR is sorted} Thus, the pocket sorting at these levels is applied until all setups are covered. The execution of this procedure yields an ordered sequence of pockets in PPIR. At this stage, PPIR consists of the details of machining operation, pockets, machine, and setups. 5.14 Micro-GIFTS: Micro-Planning Module Micro-GIFTS, the micro-planning module of GIFTS, is responsible for • Selection of cutting tools • Selection of optimized process parameters • Calculation of cutting times and costs.
Cutting Tool Selection Selection of the best cutting tool for a given operation is one of the complex tasks to be performed by the process planner. When developing a generative process planning system, it is necessary to incorporate mechanisms for automatic tool selection in the system without user intervention. Many CAPP systems contain a tool selection module with varying degrees of sophistication which gets the required data from other modules of the system. Since a large variety of cutting tools are available, the tool selection problem often becomes complex. It is further complicated by the large number of factors to be considered for tool selection. However, some general guidelines for selecting a cutting tool can be established based on production practices (Chen et al., 1989; Metropoulos and Hinduja, 1991; Yeo et al., 1990; Opitz, 1970; Halevi, G. and Weill, R.D., 1995). Tool selection essentially involves the specification of tool material, tool holder, and insert (shape, geometry, and grade). The main variables that control the selection process are • The operation • The work material and its condition • The component geometry • The machine tool • The production rate • The manufacturing quality. Each of the above variables would not only have its independent influence on the selection process but also sometimes be linked with the other variables. Therefore, it is necessary to develop a number of rules, based on the experience on the shop floor, as to how the tool selection is to be carried out. To make the selection process, it is necessary to store the details of the cutting tools as resources. A typical data structure that could be adopted for this is given in Table 5.5 in the appendix. The tool data base contains information about turning tools, grooving tools, threading tools, boring tools, etc. A separate data base can be made for form tools which can store the features produced by each of these form tools in that data base. The availability of a particular cutting tool on the shop floor can be indicated by changing the field “tool.available.” Selection of Turning Tools The selection of tools involves the determination of the key parameters and searching the tool data base, based on those key parameters. The guidelines in the tool selection module are based on the practices followed in the participating industry and a tool manufacturer’s handbook (Widia, 1989). The inputs coming from the models of the CAPP system such as PDIR, MRIR and PPIR are shown in parentheses below: 1. Based on the operation and nature of cutting (pocket.operation, pocket.nature from PPIR), select the cl<strong>amp</strong>ing system. 2. Based on the work material (global data from PDIR), nature of cutting, and the cl<strong>amp</strong>ing system, decide the insert shape and insert clearance angle. 3. Find the tool-access and tool-out directions based on the geometry of the pocket (pocket shape and dimensions from PPIR). 4. Based on the tool-access, tool-out, and feed directions, select the holder style. 5. Based on the pocket dimensions and tool holder style, select the insert size. The steps involved are (a) determine the largest depth of cut from the pocket dimension; (b) based on the approach angle, find the theoretical cutting edge; and (c) find the exact cutting edge based on the insert shape. 6. Find the maximum shank diameter on the machine tool selected. This parameter is obtained by searching the machine tool data base (from MRIR) with the help of machine tool code (from PPIR).
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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
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 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: FIGURE 5.31 Operation sequencing co
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
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
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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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