ComputerAided_Design_Engineering_amp_Manufactur.pdf

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typically can only direct a tool to move along linear and circular paths. However, geometric profiles of CAD-generated parts are usually defined by third- or higher-order curves and surfaces. Hence, it is necessary to fit lines and circular arcs, or their combination, to these CAD-defined curves to produce the CNC tool paths to some desired tolerance. To check and verify that the complex surfaces are generated to the desired accuracy, computer-controlled coordinate measurement machines (CMMs) are used. A logical approach is to use the same CAD-represented part to generate the NC program for the measurement of the part by the CMM. Setup, processing and data analysis requirements are quite different from those for machining operations. These are discussed in the last section. 2.2 Automation of Process Planning for Computer-Generated NC Programs Process planning provides the necessary link between design and manufacture. Various computerautomated or computer-aided process planning (CAPP) systems have been developed and reported. 4–7 The recent trend is towards integrating CAPP with CAD and production planning and control activities. 6–7 Some systems aim to cater to the processing of a large variety of parts. Others are product- or geometryspecific, catering to a few specific families of parts, such as rotational parts. The applications of CAPP systems in industrial environment are somewhat limited and their full potentials have yet to be realized. 7 In general, a fully automated (generative) process planning system performs satisfactorily for well-defined families of parts with established process plans. 5 Even for a family of parts with pre-determined sequence of operations and finite variation in geometry, much development effort is still required to ensure that all possible permutations and combinations are considered and an efficient plan generated. The following two sections present CAPP for part families of more specific geometry where the parts are processed by machining and all processing requirements are completed on a single CNC machine: • CAPP for NC turning8,9 • CAPP for NC milling of spherical parts: space frame nodes10 The outputs obtained from a CAPP system are used for job scheduling, NC programming and other manufacturing tasks. Prior to the generation of the NC programs, it is necessary to decide on the machining operations, select the cutting tools, and determine the cutter paths and cutting conditions. For a given machine tool, the activities involved in a typical machining operation planning include the following steps: • Interpretation of part geometry or feature extraction • Determination of cutting operations and boundaries • Selection of setups and clampings • Selection of tool types • Determination of cut distribution and cut paths • Determination of cutting parameters • Determination of operation sequence and routing CAPP for Turning One approach to automating the decision making is to apply artificial intelligence (AI) techniques, such as expert system techniques. Using expert system techniques to provide a machining knowledge-based model, an integrated machining system (IMS) has been developed for the manufacture of rotational parts. 9 It aims to integrate and automate the feature extraction, operation planning, machinability data selection and NC program generation. The architecture of this system is illustrated in Figure 2.2. This PC-based system comprises a user interface for interaction, a feature recognizer, a knowledge base of facts and rules. A software tool called GOLDWORKS (III) with COMMON LISP as the programming platform is employed in the knowledge building. With this frame-based knowledge building tool, the information being manipulated is repre- © 2001 by CRC Press LLC
FIGURE 2.2 sented by instances of frames, and the problem solving knowledge that manipulates the instances is represented by production rules. The software allows for easy modification, addition, or updating of information and production rules by an expert user. The system is designed to integrate knowledge in a modular form and incorporate heuristics so as to minimize human intervention when used. The IMS first interprets a given CAD-represented part (AutoCAD DXF drawing file) and extracts the machining features. It assigns appropriate operations to all features identified, automatically selects the tools and determines the required machining conditions. Finally, tool paths are generated. Figure 2.3 shows the flow chart of the steps taken by the IMS to generate a process sheet and a set of CNC codes for a given setup. Fixture planning is not included in the IMS. It is assumed that component setups with suitable workholding are provided so that the solution generated by the IMS can be implemented. The inferential strategy, the feature extraction, and the knowledge base of facts and rules of the IMS are detailed in Reference 9. A sample part drawing of a component created using the CAD software AutoCAD is shown in Figure 2.4. The first setup is used to machine to largest outer diameter feature, the left-most vertical feature and the two left-most internal features of the component. In the second setup the largest outer diameter of the component is clamped in the chuck. Based on this setup, the extracted features are shown in Figure 2.5. The process sheet and CNC program generated by the IMS are shown in Figures 2.6. © 2001 by CRC Press LLC Architecture of the integrated machining system for turning.
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: FIGURE 2.1 Tool paths generated for
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
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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
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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]
Page 271 and 272:
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
Page 329 and 330:
Quantity analysis methods have the
Page 331 and 332:
y a revolute joint. By selecting al
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