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CLA value of the geometric surface finish obtained during turning operation with a tool-of-nose radius r is given as SF � 1000 � -------------- 18 3r Based on the surface finish, SF max, specified on the turned surface, the constraint on feed can be expressed as C sf 2 � SFmax, Cs In tolerance constraints, the machining complex, comprising the machine tool, workpiece, work holding device, and cutting tool, will be subjected to deflection under the action of cutting forces. This in turn causes inaccuracies on the diameter of component. The radial component of cutting force is dominant in causing the deflections in the machining complex (Kovan, 1959). The deflections produced in a plain cylindrical component can be calculated based on the theory of elasticity. However, in the case of stepped components, calculation of deflections becomes difficult. Hence, finite element method (FEM) procedures are used in the present work to compute the radial deflection of the component. The given component can be converted into a stepped component. In case of taper feature, a step with the mean diameter can be created. Grooves can be considered turn features with diameter as the starting diameter of the groove. The stepped component can then be modeled as an elastic beam with two-noded elements. Unit cutting force is applied on the surface being machined and the corresponding deflections in the component are calculated at different nodes using FEM procedures (Chandrupatla and Belegundu, 1991; Hinduja et al., 1985). The work-holding devices such as the head stock, tail stock, and carriage are assumed to be flexible, since they cannot have an infinite stiffness value (Prasad, 1994). The maximum deflection, � max, produced in the component due to the radial component of the cutting force can be expressed in terms of the cutting variables as Twice this radial deflection should not exceed the diametral tolerance specified on the turned surface, D tol. Thus, � max The above expression can also be used to check for cylindricity constraint. In this case, maximum deflection, � max, is equal to the difference between the maximum and minimum deflections produced in the surface being machined. In rough machining operations, workpiece rigidity constraint exists because, due to higher depths of cut and feed rates used, high cutting forces are developed, leading to significant deflections in the component. Hence, the maximum deflection � rm produced in the machined length of the component during rough machining, due to the radial component of cutting force, should not exceed a preset value, � max. This type of check can be made to prevent the incidence of chatter (Hinduja et al., 1985). The final form of the constraint can then be expressed as f 2 1000 � -------------- 18 3r �max Fr � �u Cf v af bf cf � � f d �u � 0.5 Dtol _ Cf v af bf cf � f d �u � 0.5 � Dtol Cf v af bf cf f d �rm � �max
Usually, maximum and minimum speed constraints are imposed by the machine tool. However, in the case of carbide and ceramic tools, certain minimum cutting speeds need to be maintained to avoid the failure of these cutting tools due to burring formation or micro-chipping. Hence, the minimum speed constraint is determined as the larger of the values of minimum cutting speed from machine tool and minimum cutting speed due to cutting tool (V min). Thus, the speed constraint can be expressed as max �DN ⎧ min ⎫ �DNmax ⎨------------------ , Vmin ⎩ 1000 ⎬� v � ------------------- 1000 ⎭ The maximum feed constraint for the cutting tool (f tmax) is set per the recommendations given by the cutting tool manufacturer (Widia, 1989). According to these recommendations, f tmax should not exceed 0.4–0.5 times the insert corner radius for triangular inserts and 0.6–0.7 times the corner nose radius for square inserts. The minimum feed constraint value is set to the smallest feed rate available on the machine tool. This constraint checks the feed rate during finishing operation from becoming too small. Thus the feed constraints can be expressed as fmin � f � min{ fmin, ft max} The maximum depth of cut constraint has relevance in roughing operations, while the minimum depth of cut constraint should be considered in finishing operations. The maximum limit on depth of cut due to cutting tool (d t max) is set to half the cutting edge length for inserts with included angle of 55° or 60° and for inserts with included angle of 80°–100°, d t max is set to two-thirds of the cutting edge length (Widia, 1989). Minimum limit on depth of cut (d min) is set to 0.5 mm for finishing operations, and 1 mm or depth of pocket, whichever is lower, for roughing operations. The depth of cut constraints can thus be expressed as dmin � d� dmax Another important constraint in case of multipass machining is total depth constraint. The sum of depths of cut in individual passes, both roughing and finishing, must be equal to the total depth of material to be removed. m �d i i�1 � dt This constraint may not be relevant if equal depths of cut are used for all passes. Solution Methodology In the case of multipass optimization, the parameters to be determined are the number of passes, cutting speed, feed, and depth of cut to be used in each pass. As the number of passes is not known a priori, the number of variables becomes unknown. This makes a complex problem to solve. When the total depth of material has to be removed in more than one pass and there is surface finish or diametral tolerance or both specified on the machined surface, the machining of this pocket needs both roughing and finishing passes. As the governing constraints for rough and finish turning operations are different, these two operations are treated separately. If rigorous optimization has to be carried out for each individual pass, the solution obtained will be computationally expensive. In any case, the cost of employing different depths of cut does not appear to
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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
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: When these values are substituted,
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
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
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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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