ComputerAided_Design_Engineering_amp_Manufactur.pdf

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14. Chou, Y. C., Geometric reasoning for layout design of machining fixtures, Int. J. of Computer Integrated Manufacturing, Vol. 7, No. 3, 175–185, 1994. 15. Asada, H. and By, A. B., Kinematic analysis and design for automatic workpart fixturing in flexible assembly. Proc. of the 2nd Int’l. Symp. of Robotics Research, Kyoto, Japan, 50–56, 1984. 16. Shirinzadeh, B., A flexible automatic fixturing system. Third National Conference on Robotics, 317–328, Melbourne, Australia, June 1990. 17. Bausch, J. J. and Youcef-Toumi, K., Kinematic methods for automated fixture reconfiguration planning. Proc. of IEEE Robotics and Automation Conference, Cincinatti, Ohio, May 1990. 18. Gandhi, M. V. and Thompson, B. S., Phase-change fixturing for FMS. Manufacturing Engineering Systems, Vol. 93, No. 6, 79–80, 1984. 19. Abou-Hanna, J. and Okamura, K., Finite element approach to modelling particulate bed fixtures. Journal of Manufacturing Systems, Vol. 11, No. 1, pp. 1–12, 1992. 20. Trappey, J. C. and Liu, C. R., A literature survey of fixture-design automation. International Journal of Advanced Manufacturing Technology, Vol. 5, 240–255, 1990. 21. Shirinzadeh, B., Issues in the design of the reconfigurable fixture modules for robotic assembly. Journal of Manufacturing Systems, Vol. 12, No. 1, 1–14, 1993. 22. Bausch, J. J. and Youcef-Toumi, K., Automated reconfiguration planning for sheet metal fixturing systems. Proc. of Japan-USA Symposium on Flexible Automation, Kyoto, Japan, July 1990. 23. Chan, K. C., Benhabib, B., and Dai, M. Q., A reconfigurable fixturing system for robotic assembly. Journal of Manufacturing Systems, Vol. 9, No. 3, 206–221, 1990. 24. Shirinzadeh, B., A CAD-based design and analysis system for reconfigurable fixtures in robotic assembly. Computing & Control Engineering Journal, Vol. 5, No. 1, 41–46, 1994. 25. Nnaji, B. O. and Lyu, P., Rules for an expert fixturing system on a CAD screen using flexible fixtures. Journal of Intelligent Manufacturing, Vol. 1, 31–48, 1990. 26. Trappey, A. J. C. and Matrubhutam, S., Fixture configuration using projective geometry. Journal of Manufacturing Systems, Vol. 12, No. 6, pp. 486–495, 1993. 27. Foley, J. D. and Dam, S. K., Computer Graphics, Principles and Practice. Addison-Wesley, Reading, MA, 1989. 28. Trappey, A. J. C. and Liu, C. R., An automatic workholding verification system. Journal of Robotics & Computer-Integrated Manufacturing, Vol. 9, No. 4/5, 321–326, 1992. 29. Ohwovoriole, M. S. and Roth, B., An extension of screw theory. Journal of Mechanical Design, Vol. 103, 725–734, 1981. 30. Fanghella, P., Galleti, C., and Giannotti, E., Computer-aided modelling and simulation of mechanics and manipulators, Computer-Aided Design, Vol. 21, No. 9, pp. 577–583, 1989. 31. Shiller, Z. and Dubowsky, S., Robot path planning with obstacles, actuators, grippers, and payload. The International Journal of Robotics Research, Vol. 8, No. 6, 3–18, 1989. 32. Owens, J., Robot simulation—seeing the whole picture. Industrial Robot, Vol. 18, No. 4, 10–12, 1991. 33. Thangaraj, A. R. and Doelfs, M., Reduce downtime with off-line programming. Robotics Today, Society of Manufacturing Engineers, Vol. 4, No. 2, pp. 1–3, 1991. 34. Steiner, K. V., Keefe, M., and Wolff, A., Interactive graphics simulation with multi-level collision algorithm. Journal of Manufacturing Systems, Vol 11, No. 6, 462–469, 1992. 35. Sorenti, P., GRASP for simulation and off-line programming of robots in industrial applications. Proc. of Welding Engineering Software, DVS 156, 55–58, Essex, 1993. 36. Beaumont, R. G. and Crowder, R. M., Real-time collision avoidance in two-armed robotic systems. Computer-Aided Engineering Journal, Vol. 8, 233–240, December 1991. 37. Shirinzadeh, B., A CAD-based hierarchical approach to interference detection among fixture modules in a reconfigurable fixturing system. Journal of Robotics & Computer-Integrated Manufacturing, Vol. 12, No. 1, 41–53, 1996. 38. Brost, R. C., and Goldberg, K. Y., A complete algorithm for designing planar fixtures using modular components. IEEE Trans. on Robotics and Automation, Vol. 12, No. 1, 31–46, 1996. © 2001 by CRC Press LLC
Heui Jae Pahk Seoul National University 4.1 Introduction 4 Integrated Precision Inspection System for Manufacturing Based on CAD/CAM/CAI Environment 4.1 Introduction 4.2 Geometric Features and Tolerances for Inspection Features and Tolerances Defined by ISO • Sculptured Surfaces: Mathematical Description 4.3 Measurement Points Sampling and Path Planning Measurement Points Sampling and Path Plan for Sculptured Surfaces • Measurement Points Sampling and Path Plan for Basic Features 4.4 Alignment of Coordinate Systems, DMIS Code Generation, and Measurement Operation Rough Phase Alignment Procedure • Fine Alignment Procedure Based on Iterative Least Squares Technique • CNC Code in DMIS Format 4.5 Error Evaluation ISO Profile Tolerance • Determination of Actual Measurement Points Considering Probe Radius • Profile Tolerance (Form Error) Evaluation • Error Evaluation for Basic Features 4.6 Practical Application to Real Products and Discussion A Mold Having a Bicubic B-Spline Surface with Some Basic Features • A Turbine Blade Having Very Thin Features 4.7 Conluding Remarks The development of CAD/CAM (computer-aided design/computer-aided manufacturing) technologies has had a revolutionary effect on the manufacturing industry in that it has pursued optimization in the design and manufacturing of products. The computer-aided inspection (CAI) technique has emerged after the computer controlled coordinate measuring machines (CMMs) have been widely introduced. In this chapter, an integrated precision inspection system for manufacturing parts having CAD-defined features is demonstrated. The techniques of precision measurement are demonstrated around CAD/CAI
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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
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: 3.8 Conclusion A reconfigurable fix
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
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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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