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TABLE 6.1 Pre-Adoption Issues Issues of CAD Adoption Stage Question Issues Pre-Adoption 1. What is the feasibility of training? 2. How to gain expected benefits? 3. How will it impact work flow? What is an estimation of cost? When to give training? Where to get training? Who needs training? Are funds available? Worker attitudes Worker morale Worker skills Implementation 1. What type of training? Formal or informal training? Off- or on-site? Vendor or consultant? Customized or generic? 2. Who is to be trained? Skilled or semi-skilled workers? 3. Will management be Supervisors or higher-level trained? managers? 4. Is training included in What type of training can the budget? be afforded? Pre-adoption training issues often center around the tradeoffs between the anticipated out-of-pocket costs and the associated benefits of CAD. One of the primary managerial challenges is to assess accurately the training needs associated with the proposed CAD system and to convert them into a budget of cash expenditures. Some of the major factors that affect training costs are discussed in this section. They include: (1) determining the types and number of workers to be trained; (2) the technological aptitude or “trainability” of the workers; (3) the training method to be employed; and (4) the loss of productivity during the learning period. The benefits of CAD often include the expected cost savings or additional revenues accrued when the current methods are replaced by the proposed system. However, some anticipated benefits may be difficult to quantify accurately. For instance, dynamic market conditions can present a compelling justification for the need for a CAD system; the benefit may be survival through sustained competitiveness of the firm. On the other hand, problems with worker attitudes and morale can jeopardize the success of the implementation of the CAD system and create an opportunity cost with respect to unrealized benefits from the technology. These issues are discussed below. One major issue in the adoption decision is whether it is possible to re-train the present workforce to perform the tasks required under the new CAD system. This question involves examining both the “person” and “task” components of the training decision. 21 It is possible that the tasks and procedures used in the CAD system are so high level that some of the potential users may not possess the necessary skills and education to learn the new system within a reasonable time period. Worker receptivity may also be a problem if the existing workers exhibit non-adoptive behavior and decide that they are not interested in learning or using the new technology. Beatty and Gordon7 found evidence of such non-adoptive behavior in certain instances of CAD implementation. Lack of worker support can jeopardize any hope of success in implementing the new CAD technology. It is critical, therefore, that the company accurately inventory its workers’ skills and abilities and assess workers’ attitudes toward using the new system. A company considering the adoption of a CAD system must also include an estimate of the total expense of educating the workforce. For example, the acquisition cost of a CAD system is much more than just the price of the computer hardware and software. A more complete estimate of expenses includes both training program expenses and a “cushion” for the loss of productivity experienced as employees
learn to master the new system. An acquisition budget that does not include these “soft” costs can cause financial problems for an adopter firm that hasn’t anticipated these expenses. Research has found that the underestimation of training and education expenses is a major reason for failure in CAD systems implementation. 3 The underestimation of CAD costs has created situations in which the firm was overextended to the point it could no longer remain competitive; in some instances, the result was the demise of the business. A related issue is the extent to which training is offered throughout the firm. It is often critical to train employees besides those who are involved in design in order for the firm to truly understand and use the technology to its full potential. Examples of such employees may include CAD supervisors, secretarial staff, and manufacturing employees. Sometimes a new system may be so radically different from the existing one that any employee who has the slightest contact with CAD should receive training. A recent survey of firms using CAD systems showed that 50% of all companies with CAD/CAM training provided training to a wide range of occupational groups, including all shop-floor staff and managers, materials management, repair and maintenance, manufacturing engineering, and, of course, design engineering. 29 CAD systems were found to be so different from traditional design methods that workers who did not receive any CAD training were at a tremendous disadvantage when they came into contact with the system. Thus, the need for CAD training across many different work groups cannot be underestimated. It is critical that management accurately assess these needs and calculate the associated training costs before choosing to adopt a CAD system. Managers also need to factor training needs into the cost-benefit tradeoff. If the firm considers adopting a new CAD system that promises relatively modest benefits yet requires a great deal of employee training, it may be difficult to justify the new system. When the combined expense of the system and the training provides only incremental gains, managers may be wise to invest the money in more traditional manual methods. 36,42 On the other hand, firms experiencing market pressures such as changes in government or industrial standards, or customer demand for one-off products might need the system (and the associated training program) for survival. Thus, in such instances, the cost-benefit tradeoff is moot. Small firms provide special cases for each of the issues raised above. Because of the limited resource availability in smaller companies, the issues often represent tighter constraints than those placed upon larger companies. For example, smaller firms frequently do not have the slack resources to provide a “buffer” for employees to learn the new technologies. As a result, the loss of productivity and the required training period that frequently accompany switching to a new technology create a loss of revenue that small firms may find difficult to overcome. 16,29,42 Small firms are also hurt by the high price of CAD equipment, which may consume a significant portion of their available funds, and limit their ability to develop an appropriate training program. These problems would seem to imply that the size of the firm determines of successful CAD use and should be considered in the pre-adoption decision. However, there are multitudes of small firms that have successfully implemented CAD systems and are doing very well financially. Implementation Issues Implementation issues are those confronted by the firm after it is already committed to the new technology. The main concern of training issues associated with the implementation process is how to most efficiently and effectively develop the workforce so that the system achieves its maximum potential. Some of the training issues associated with implementation are similar to the pre-adoption issues discussed above, while many issues are completely different. In the implementation phase, training issues involve not only the financial cost implied by a particular training strategy but also consideration of the effectiveness of the training methods, the development of desired skill sets, and the extent to which the value of design work has been enhanced through de-skilling. The training strategy involves a pattern of decisions regarding: (1) identity of the workers to be trained; (2) extent to which management will be trained; (3) location of the training sessions; (4) selection of the trainer; (5) timing of the training relative to installation; and (6) training methods employed. The issues inherent in a training strategy are discussed below.
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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
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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.
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 and 190: When these values are substituted,
Page 191 and 192: Usually, maximum and minimum speed
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: CAD systems. The sample consists of
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
Page 241 and 242: FIGURE 7.16 3-D CAD model of a part
Page 243 and 244: References Cheok, B.T. et al. (1994
Page 245 and 246: include the once forbidden generati
Page 247 and 248: A temporal matrix (T-Matrix) is pro
Page 249 and 250: FIGURE 8.1 A basic process. (From R
Page 251 and 252: FIGURE 8.4(a) Generate a new IG usi
Page 253 and 254: 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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