Further information pertaining to the inspection features has to be built up based on planning methodologies for setup planning, PCS selection, and surface data points extraction based on the number of s<strong>amp</strong>ling points and accessibility analysis of the probe. This ex<strong>amp</strong>le shows an approach of extracting information from a product model for computer-aided measurement and organizing this information into inspection features. The inspection features will form the basic building blocks which will help to facilitate the generation of the CMM part program. References 1. Chia, A. P. H., An Integrated CAD/CAM Approach for the <strong>Manufactur</strong>e of Wind-Tunnel Models, B. Eng. Thesis, National University of Singapore, 1994. 2. Giam, K. Y., <strong>Manufactur</strong>e of Wind-Tunnel Model Using CAD/CAM Technique, B.Eng. Thesis, National University of Singapore, 1993. 3. Tan, L. B., <strong>Manufactur</strong>e of Models Employing Integrated CAD/CAM Techniques, B.Eng. Thesis, National University of Singapore, 1995. 4. Alting and Zhang, H. C., Computer-aided process planning: the state-of-the-art survey, International Journal of Production Research, Vol. 27, No. 4, 1989, 553–585. 5. Nolen, Computer-automated Process Planning for World-class <strong>Manufactur</strong>ing, Marcel Dekker, Inc., NY, 1989, 65–70. 6. Eversheim W. and Schneewind, J., Computer-aided process planning—state of the art and future development, Robotics and Computer Integrated <strong>Manufactur</strong>ing, Vol. 10, No. 1/2, 1993, 65–70. 7. Elmaraghy, H. A., Evolution and future perspectives of CAPP, Annals of the CIRP, Vol. 42, No. 2, 1993, 1–13. 8. Yeo, S. H., Wong, Y. S., and Rahman, M., Integrated knowledge-based machining system for rotational parts, International Journal of Production Research, Vol. 29, No. 7, 1991, 1325–1337. 9. Yeo, S. H., An integrated knowledge-based machining system for rotationally symmetric parts, Ph.D. Thesis, National University of Singapore, 1992. 10. Wong, Y. S. and Wang, Z., Automated process planning for CNC machining of spherical spaceframe nodes, Journal of <strong>Manufactur</strong>ing Systems, Vol. 14, 1995, 369–377. 11. Eade, R., For flexibility, you can’t beat them, <strong>Manufactur</strong>ing <strong>Engineering</strong>, May 1989, 49–52. 12. Coleman, J. R., Machining centers cut it in job shops, <strong>Manufactur</strong>ing <strong>Engineering</strong>, March 1990, 41–45. 13. Hines, F., Specialized CAM: a success story, <strong>Manufactur</strong>ing <strong>Engineering</strong>, May 1989, 88–89. 14. Bolton, K. M., Biarc curves, Computer-Aided <strong>Design</strong>, Vol. 7, No. 2, 1975, 89–92. 15. Su, B. Q. and Liu, D. Y., Computational Geometry—Curve and Surface Modeling, Academic Press, NY, 1989. 16. Moreton, D. N. and Parkinson, D. B., The application of a biarc technique in CNC machining, Computer-Aided <strong>Engineering</strong> <strong>Design</strong>, 8, 1991, 54–60. 17. Schonherr, J., Smooth biarc curves, Computer-Aided <strong>Design</strong>, Vol. 25, No. 6, 1993, 365–370. 18. Sharrock, N., Biarcs in three dimensions, in Martin, R.R., Ed., Mathematics of Surfaces �, Oxford University Press, UK, 1986. 19. Parkinson, D. B., Optimized biarc curves with tension, Computer-Aided Geometric <strong>Design</strong>, Vol. 9, 1992, 207–218. 20. Piegl, L., Curve fitting algorithm for rough cutting, Computer-Aided <strong>Design</strong>, Vol. 18, No. 6, 1986, 79–82. 21. Meek, D. S. and Walton, D. J., Approximation of discrete data by G arc splines, Computer-Aided <strong>Design</strong>, Vol. 23, No. 6, 1991, 411–419. 22. Meek, D. S. and Walton, D. J., Approximating quadratic NURBS curves by arc splines, Computer- Aided <strong>Design</strong>, Vol. 25, No. 6, 1993, 371–376. 23. Nutbourne, A. W. and Martin, R. R., Differential Geometry Applied to Curve and Surface <strong>Design</strong>, Volume I: Foundations, Ellis Horwood, NY 1988. 1 © 2001 by CRC Press LLC
24. Makinouchi, S., Okamoto, M., and Yamagata, K., Optimal curve fitting for NC machining by dynamic programming technology, Reports of the Osaka University, Vol. 16, No. 2, 1976. 25. Cantoni, A., Optimal curve fitting with piecewise linear functions, IEEE Transactions on Computers, C-20, No.1, 1971, 59–67. 26. Faux, I. D. and Pratt M. J., Computational Geometry for <strong>Design</strong> and <strong>Manufactur</strong>e, Ellis Horwood Limited, N.Y., 1985. 27. Ding, Q. and Davies, B. J., Surface <strong>Engineering</strong> for Computer-Aided <strong>Design</strong>, Halsted Press, Chichester, England, 1987. 28. Vickers, G. W., Ly, M. H., and Oetter, Numerically Controlled Machine Tools, Ellis Horwood, N.Y. 29. Teng, C. S., Loh, H. T., and Wong, Y. S., A study of the deviation of best-fitted lower-order curves for the cubic Bezier curve, Internal Report, Mechanical and Production <strong>Engineering</strong> Department, National University of Singapore, 1993. 30. Wong, Y. S., Loh, H. T., and C. S. Teng, An optimal piecewise curve-fitting approach for CNC machining, Transactions of NAMRC, Vol. 23, 1995, 157–162. 31. Papalambros, P. Y. and Wilde, J. W., Principles of Optimal <strong>Design</strong>: Modeling and Computation, Cambridge University Press, 1988. 32. Jasbir, S. A., Introduction to Optimum <strong>Design</strong>, McGraw Hill, NY, 1989. 33. Hoschek, J., Circular splines, Computer-Aided <strong>Design</strong>, Vol. 24, 1992, 611–618. 34. Parkinson, D. B. and Moreton, D. N., Optimal biarc curve fitting, Computer-Aided <strong>Design</strong>, Vol. 23, 1991, 411–419. 35. Ong, C. J., Wong, Y. S., Loh, H. T., and Hong, X. G., An optimization approach for biarc curverfitting of B-spline, Computer-Aided <strong>Design</strong>, Vol. 28, No. 12, 1996. 36. Kao, J. H., Loh, H. T., and Prinz, F., Least-square biarc curve fitting for CNC machining, Proceedings of 17th Computers in <strong>Engineering</strong> Conference, 1997. 37. Evershiem, W. and Auge, J., Automatic generation of part program for CNC-coordinate measuring machine linked to CAD/CAM systems, Annals of the CIRP, Vol. 35, No.1, 1986. 38. DMIS, “Dimensional Measuring Interface Specification,” Version 2.1, Computer-Aided <strong>Manufactur</strong>ing International Inc., 1989. 39. Intergraph/Mechanical Probe CMM Option, Intergraph Corporation, Huntsville, Alabama. 40. Pro/CMM, ProEngineer CMM Option, Parametric Technology Corporation, 128 Technology Drive, Waltham, MA 02154, USA. 41. ANSI Y14.5M-1982, Dimensioning and Tolerancing, American Society of Mechanical Engineers, USA, 1983. 42. Yau, H. T. and Menq, C. H., An automated dimensional inspection environment for manufactured parts using coordinate measuring machines, International Journal of Production Research, Vol. 30, No. 7, 1992, 1517–1536. 43. Zhang, Y. F., Nee, A. Y. C., Fuh, J. Y. H., Neo, K. S., and Loy, H. K., A neural network approach to determining optimal inspection s<strong>amp</strong>ling size for CMM, Journal of Computer Integrated <strong>Manufactur</strong>ing Systems, Vol. 9, No. 3, 1996, 161–169. 44. Neo, K. S. and Wong, Y. S., Link between a CAD system and a computer-controlled CMM via the dimensional measuring interface specifications (DMIS), Proceedings of the Industrial Automation ’92 Conference, 20–23 May 1992, World Trade Centre, Singapore, 179–188. 45. Pao, Y. H., Komeyli, K., Shei, D., Leclair, S., and Winn, A., The episodal associative memory: managing manufacturing information on the basis of similarity and associativity, Journal of Intelligent Manfacturing., Vol. 4, 1993, 23–32. 46. Elmaraghy, H. A. and Gu, P. H., Expert system for inspection planning, Annals of CIRP, Vol. 36, No.1, 1987, 85–89. 47. Merat, F. L., Radack, G. M., Roumina, K., and Ruegsegger, S., Automated inspection planning within the rapid design system, IEEE International Conference on Systems <strong>Engineering</strong>, 1991, 42–48. 48. Merat, F. L. and Radack, G. M., Automatic inspection planning with a feature based CAD system, Robotics & Computer Integrated <strong>Manufactur</strong>ing, Vol. 9, No. 1, 1992, 61–69. © 2001 by CRC Press LLC
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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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- Page 61 and 62: FIGURE 2.16 Types of biarcs. FIGURE
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- Page 81 and 82: FIGURE 3.1 Trends in flexible manuf
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- Page 107 and 108: 3.8 Conclusion A reconfigurable fix
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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
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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