ComputerAided_Design_Engineering_amp_Manufactur.pdf

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FIGURE 3.2 and CAD/CAM, which are essential ingredients of modern manufacturing. Figure 3.2 shows a schematic diagram highlighting the approaches that have received significant attention in the past decade. 6 These approaches are briefly described in this section. Sensory-Based Workholding Techniques In order to reduce the accuracy requirements for workholding, sensory-based information may be used to compensate for positioning errors in an assembly setup. Machine vision techniques have been applied to manufacturing processes to create a “visual fixture.” Visual fixturing utilizes triangulation-based formulations and computer control to generate a workpiece “offset matrix” for use by a robot controller. The matrix effectively defines the location of the workpiece in six degrees of freedom. This technique has been applied to the fixturing problem encountered for insertion of windshields onto automobile bodies. It must be noted that this is a method to correct for location errors on parts for which traditional fixtures have already provided adequate clamping. Modular and Reconfigurable Fixtures Modular fixturing employs a number of elements such as V-blocks, rectangular blocks, and clamps to construct a fixture layout. 7 These pieces are bolted down to a T-slotted plate or a base plate with plain and tapped holes. The plate is usually part of the machine bed. The elements are aligned precisely with the aid of measuring devices (e.g., height gauge). Toggle clamps are often used to allow for rapid changing of the workpiece. The clamps push the workpiece against the V-blocks and rectangular blocks, thus constraining the workpiece. The accurate alignment of the workpiece requires great care. Modular fixturing kits are based on the traditional machinist’s approach of developing a variety of fixtures by assembling primitive elements. 8 Research efforts in modular fixturing have focused on the development of strategies for automatic setup of these elements using robots. Efforts have also been aimed at developing computer-assisted design techniques and geometric reasoning for assembly of the elements. 9–14 The concept of reconfigurable fixtures has received considerable attention. 6 This approach uses a number of modules or mechanisms that are reconfigured or rearranged to form layouts that position © 2001 by CRC Press LLC Flexible workholding strategies. (Reprinted from Reference 5, with permission from Elsevier Science.)
FIGURE 3.3 and constrain different workpieces within a family. 15 The reconfiguration or arrangement is generally performed by a robot or dedicated device built into the system. The fixture modules are retrieved from the storage magazines and placed on a fixture platform by a robot which then proceeds to perform adjustment operations on these modules. 15–17 The workpiece is placed on this configuration and the modules will be in contact with the workpiece at the desired locations (see Figure 3.3). The fixture modules are generally suitable for applications with low-to-medium force, and torque conditions such as light flexible assembly and finishing operations. Adaptable Fixtures A set of clamps has been designed to use shape memory alloy (SMA) wires to exert motive force. 3 The clamps consist of a 4 � 4 array of fingers. The fingers are normally locked by the squeezing action of heavy duty belleville springs. When current is applied to a SMA wire, the wire is heated; the temperature increase induces a martensite phase transformation in the material, which then attempts to assume its “trained” position. The resulting force releases the fingers so they conform to irregular workpiece surfaces. A second set of SMA wires is then used to apply the horizontal clamping force. This class of fixtures was originally developed to be used as end-effectors on robot manipulators, but they may also be utilized in other applications. Programmable Conformable Clamps Programmable conformable clamps are workholding devices employed specifically for the machining of titanium forgings for the turbine blades of large power generating equipment. 1 The clamps consist of octagonal frames that are hinged so that they may be opened to accommodate a blade and then be closed. The clamps may be located at almost any position along the blade; generally, two or three clamps will hold a blade rigidly enough for machining purposes. These clamps are light and compact enough to travel with the blade and they can accommodate a large number of different blade configurations. However, the initial accurate positioning of the workpiece within the clamps requires a great deal of care, and a different reference surface for each workpiece at the clamping station must be built. Other © 2001 by CRC Press LLC Reconfigurable fixture.
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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
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: FIGURE 3.1 Trends in flexible manuf
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
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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
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FIGURE 5.5 leading to the developme
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the previously stored process plan
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FIGURE 5.7 Techniques of defining a
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Feature Recognition and Extraction
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in relation to another feature (e.g
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FIGURE 5.9 Framework for building a
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FIGURE 5.10 Process plan content.
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FIGURE 5.12 Schematic sketch of the
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Several techniques of defining a fe
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TABLE 5.1 Data Structure for Repres
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FIGURE 5.16 Classification of the t
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system to ensure that the part bein
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FIGURE 5.19 Graphical model of the
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TABLE 5.4 Data Structure for Repres
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FIGURE 5.20 Mapping between machini
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algorithms. (Some details of the pr
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FIGURE 5.24 An example rotational p
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FIGURE 5.26 Down_face-turn-up_face
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FIGURE 5.27 Procedure for machine t
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FIGURE 5.28 Determining the number
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DL is needed to be set only if the
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FIGURE 5.31 Operation sequencing co
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Cutting Tool Selection Selection of
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1. A tool is searched for in the da
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FIGURE 5.32 Inputs to optimization
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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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