ComputerAided_Design_Engineering_amp_Manufactur.pdf

More documents

Recommendations

Info

Side Carrier In cases where a center carrying scheme cannot be used, a side carrier approach can be used. Here, the workpiece will be carried by scrap webs at one or both sides of the strip. When a side carrier scheme is used, the punch decomposition process will generate punch strips such that thin strips of web are provided at the sides of the strip to carry the workpiece. The parting punches will be selected from the scrap sections which satisfy these conditions: 1. Scrap areas that connect the edge of the strip to the workpiece 2. Scrap areas that are not adjacent to folded portions of the workpiece 3. Scrap areas with sizes greater than a minimal value to provide sufficient strength to carry the workpieces. 7.7 Spatial Planning Techniques for Staging the Die Operations The final planning task in the development of the strip layout is the staging of the die operations such that when all the stamping operations have been completed on the strip in the progressive die, the required part is produced in the last stage. To automate the staging process, it is necessary to estimate the amount of die area each of the stamping operations requires. This can be achieved by developing rules and functions to derive the envelope area required to mount the respective tools in the die. For example, the amount of die area required by a punch will depend on the following factors: 1. The size and shape of the punch 2. The type of mounting arrangement at the punch plate 3. The minimum distance between holes on the punch plate required to maintain structural strength and also to provide room for the operator to access the punch during assembly and replace the punch during operation. This can be represented by a user-defined die area expansion factor used to expand the envelope area derived using the first two factors. The functions to calculate the envelope areas for the stamping operations can be stored as monitors in the object representation of the features in the knowledge base. When the staging task is performed, these monitors will be fired and the envelope areas calculated when needed. The strip layout can be derived automatically by staging the die operations in the following order: 1. Piercing operations on pilot holes are staged first. 2. Piercing operations on other internal holes are staged next. 3. Notching operations of external profiles are staged next. 4. Notching operations of external profiles used to accommodate indirect pilot holes (if any) are staged next. 5. Bending operations are staged next. 6. Cam operations (on precise holes on bend features of the workpiece) are staged next. 7. Finally, the cut-off operations and internal holes used as semi-piloting holes (if any) are staged. During the staging process, the die operations are represented by their envelope areas and laid on the strip according to their priority. For envelope areas having the same priority, they are ordered according to their relative distance from the center of the strip. Those envelope areas further away from the center will be laid ahead of those nearer to the center. If an envelope area overlaps an existing one on the station, it will be carried to the next station. The staging process will continue until the envelope areas of all the die operations are laid on the strip. To reduce the time taken by the computer to check for the interference of envelope areas, the shapes of envelope areas are simplified to either rectangular or circular. The strip layout produced using the above heuristics will always attempt to achieve the smallest die area possible. The system can provide facilities for the user to control the final strip layout. First, the tightness of the die can be controlled by changing the die area expansion factor. If the factor is
a larger value, the die operations will be spaced further apart. Second, interactive commands can be provided to allow the user to insert idle stations and to move a die operation from one station to another. 7.8 Iterative Feedback Approach for Operations Planning We have described the intelligent techniques that can be used to assist in the various tasks involved in the operations planning in progressive die design. These tasks are interdependent and decisions made in one task will affect the outcome in the others. For example, the actual punch shapes selected will depend on the piloting schemes used. On the other hand, the actual pilot holes (for an indirect piloting scheme) cannot be selected until the shapes of the notching punches are known. In other words, an effective computer aid must provide the following facilities for the user to manage the iterative feedback design process: 1. Generate a ‘‘first-guess’’ solution for each of the subtasks quickly. 2. Provide interactive aids to modify the solution. 3. Use the modified solution as a starting point to generate the solutions for the other subtasks. 4. At any time, move from one subtask to another to study how the solutions affect each other, and, if necessary, modify them to ensure that the constraints in all the subtasks are satisfied. The iterative feedback design procedure can be achieved by integrating an interactive graphics user interface (preferably in the form of a CAD system) with a knowledge-based system. The CAD system will provide interactive graphics aids for the user to visualize and manipulate the plan as it is developed and stored in the knowledge base. Commands can also be provided via the CAD interface to let the user define break points in a task and to step from one task to another. Using the techniques described so far, a prototype design system can be developed to generate the strip layout from the feature-based description of a product. As an illustration, the staging and strip layout required to manufacture the product shown in Figure 7.2 is shown in Figure 7.8. In addition, Cheok et al. (1995) described how these techniques are used to generate the plans to manufacture a different workpiece using a prototype progressive die design system developed at the National University of Singapore. 7.9 A Model-Based Reasoning (MBR) Approach for Die Synthesis The operations planning process converts the features of a product into a plan model describing the stamping operations at each station required to manufacture the product. The next stage in progressive die design is to generate the engineering description of the die from the plan model. Once the engineering model is described in the knowledge base, a 3-D solid modeling description of the die can be produced in the CAD system for visual inspection and verification and down-stream manufacturing. The symbolic relationships between entities in the CAD data base, the feature tree, the plan model and the engineering model are shown in Figure 7.9. Dym and Levitt (1991) have described an architecture and some methodological ideas for building knowledge-based engineering systems using the model-based reasoning (MBR) approach. The MBR approach can be used as the framework to automate the synthesis of a progressive die from strip layout. The features of the MBR approach for die synthesis are as follow: 1. The die structure is represented by a hierarchy of its components classified into branches of subassemblies and by topological links which are automatically deduced using spatial reasoning techniques. The generic hierarchy of die components represented in the knowledge base is shown in Figure 7.10. 2. The die components can be classified into two synthesis models: a. Components or subassemblies whose descriptions are directly dependent on the product features and the strip layout—The rules and formulation to describe these components are specially coded and stored in a library of standard components in a component hierarchy based upon standard naming conventions given in Figure 7.10. Rules or procedures that reference additional attributes of named components then generate multiple abstraction links for components. Examples of
Page 1 and 2:
COMPUTER-AIDED DESIGN, ENGINEERING,
Page 3 and 4:
Library of Congress Cataloging-in-P
Page 5 and 6:
Editor Cornelius T. Leondes, B.S.,
Page 7 and 8:
Chapter 1 Chapter 2 Chapter 3 Chapt
Page 9 and 10:
the implementation of the IPD syste
Page 11 and 12:
In our IPD system implementations,
Page 13 and 14:
2. Specification of analysis-specif
Page 15 and 16:
FIGURE 1.2 base or the design insta
Page 17 and 18:
FIGURE 1.4 System architecture of t
Page 19 and 20:
of a beam is considered for FEA. Th
Page 21 and 22:
FIGURE 1.7 through the control expe
Page 23 and 24:
2. machining facility (e.g., gang m
Page 25 and 26:
from the FBDS. The user also specif
Page 27 and 28:
Depending on the type of feature to
Page 29 and 30:
TABLE 1.6 Tolerance synthesis is de
Page 31 and 32:
FIGURE 1.12 Display of the NC tool
Page 33 and 34:
component geometric entities and va
Page 35 and 36:
FIGURE 1.14 The system architecture
Page 37 and 38:
TABLE 1.10 User Input for the Toler
Page 39 and 40:
TABLE 1.11 Tolerance Specifications
Page 41 and 42:
7. Z. Young and I. R. Groose. A rul
Page 43 and 44:
FIGURE 2.1 Tool paths generated for
Page 45 and 46:
FIGURE 2.2 sented by instances of f
Page 47 and 48:
TABLE 2.1 A CAD-Generated Hole Conf
Page 49 and 50:
FIGURE 2.6 mounted on the rotary ta
Page 51 and 52:
FIGURE 2.8 fixture for the machinin
Page 53 and 54:
FIGURE 2.10 or best-fit, or the cur
Page 55 and 56:
FIGURE 2.11 Linear approximation of
Page 57 and 58:
FIGURE 2.13 Circular approximation
Page 59 and 60:
FIGURE 2.14(b) Circular approximati
Page 61 and 62:
FIGURE 2.16 Types of biarcs. FIGURE
Page 63 and 64:
FIGURE 2.18 Approximation of scanne
Page 65 and 66:
FIGURE 2.20 A touch trigger probe c
Page 67 and 68:
TABLE 2.4 Substitute Elements in CM
Page 69 and 70:
FIGURE 2.21 CMM planning requiremen
Page 71 and 72:
Product Model Representation for Co
Page 73 and 74:
© 2001 by CRC Press LLC TABLE 2.5
Page 75 and 76:
TABLE 2.7 Partial Listing of Dimens
Page 77 and 78:
24. Makinouchi, S., Okamoto, M., an
Page 79 and 80:
Bijan Shirinzadeh Monash University
Page 81 and 82:
FIGURE 3.1 Trends in flexible manuf
Page 83 and 84:
FIGURE 3.3 and constrain different
Page 85 and 86:
Other Fixturing Techniques There ar
Page 87 and 88:
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
Page 93 and 94:
een identified, the normals are use
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 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 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
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: Semi-Direct Piloting In cases where
Page 233 and 234: FIGURE 7.9 Symbolic relationship be
Page 235 and 236: FIGURE 7.11 The shape of the envelo
Page 237 and 238: TABLE 7.1 Schema for the Generation
Page 239 and 240: strong reasons to support a move to
Page 241 and 242: FIGURE 7.16 3-D CAD model of a part
Page 243 and 244: References Cheok, B.T. et al. (1994
Page 245 and 246: include the once forbidden generati
Page 247 and 248: A temporal matrix (T-Matrix) is pro
Page 249 and 250: FIGURE 8.1 A basic process. (From R
Page 251 and 252: FIGURE 8.4(a) Generate a new IG usi
Page 253 and 254: Note if the pair of nodes are both
Page 255 and 256: TABLE 8.1 Summary of the Rules Cond
Page 257 and 258: The correctness of these rules is e
Page 259 and 260: needs to show that after each full
Page 261 and 262: ule is violated, a warning should b
Page 263 and 264: Π1 Π3 Π4 FIGURE 8.8(a) After add
Page 265 and 266: 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
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
Page 277 and 278: FIGURE 8.14 A GPN model of a machin
Page 279 and 280: FIGURE 8.15(b) The first exclusive
Page 281 and 282:
FIGURE 8.15(d) The last exclusive T
Page 283 and 284:
FIGURE 8.15(f) After entering the a
Page 285 and 286:
FIGURE 8.15(h) Completion of Compon
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 and 308:
q u : the numerator of the least ra
Page 309 and 310:
geometric modeling, engineering ana
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
Page 319 and 320:
will introduce a way to propagate p
Page 321 and 322:
Completeness of Dimensions Complete
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
show all

ComputerAided_Design_Engineering_amp_Manufactur.pdf

Create successful ePaper yourself

Delete template?

Save as template?