Fuzzy Sets in Engineering Design and Configuration

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Hans-Jürgen Sebastian, Erik K. Antonsson
Springer Science & Business Media, 06/12/2012 - 282 páginas
As understanding of the engineering design and configuration processes grows, the recognition that these processes intrinsically involve imprecise information is also growing. This book collects some of the most recent work in the area of representation and manipulation of imprecise information during the syn thesis of new designs and selection of configurations. These authors all utilize the mathematics of fuzzy sets to represent information that has not-yet been reduced to precise descriptions, and in most cases also use the mathematics of probability to represent more traditional stochastic uncertainties such as un controlled manufacturing variations, etc. These advances form the nucleus of new formal methods to solve design, configuration, and concurrent engineering problems. Hans-Jurgen Sebastian Aachen, Germany Erik K. Antonsson Pasadena, California ACKNOWLEDGMENTS We wish to thank H.-J. Zimmermann for inviting us to write this book. We are also grateful to him for many discussions about this new field Fuzzy Engineering Design which have been very stimulating. We wish to thank our collaborators in particular: B. Funke, M. Tharigen, K. Miiller, S. Jarvinen, T. Goudarzi-Pour, and T. Kriese in Aachen who worked in the PROKON project and who elaborated some of the results presented in the book. We also wish to thank Michael J. Scott for providing invaluable editorial assis tance. Finally, the book would not have been possible without the many contributions and suggestions of Alex Greene of Kluwer Academic Publishers. 1 MODELING IMPRECISION IN ENGINEERING DESIGN Erik K. Antonsson, Ph.D., P.E.

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Índice

Representation of objects by frames
160
Representation of Concepts by SlotFiller notation to repre sent the attributes
161
Example of a specialization chain
162
47
169
Problems and Solvers
171
Linguistic variable Style of object car
174
Linguistic variable sizeengine of object car
175
Chen and Huangs scale to represent imprecise linguistic terms
180

Design Variable Probability Distributions
22
Applied Pressure Possibility
24
Preferences for the Flat and Hemi Head Tanks
28
Drum Brake System
30
Disk Brake System
31
Induced Preferences
37
Torque Performance Specification Tr
38
Induced Preferences Force and Torque
40
Induced Preferences Temperature
42
Chapter 2
48
MULTIPLE OBJECTIVE DESIGN
53
Path generating planar fourbar mechanism
73
Driving torque as a function of input link orientation
75
An ACOSSFOUR flexible space structure
80
LOS error versus time for minimum weight design
83
LOS error versus time for minimum control effort design
84
LOS error for case a of fuzzy game theory formulation
85
INTELLIGENT SYSTEMS
89
Areas of Application of IDSS
90
Relevant Methods for IDSS
91
Simple illustrative example of a configuration problem
92
An Architecture of an IDSS
94
Conceptual Hierarchy Car
97
Conceptual Hierarchy a general view
98
Conceptual Hierarchy an example
99
Conceptual Hierarchies Hierarchies of Objects described by Attributes
101
Classes Subclasses
102
Example FRAME TUBE
103
Specialization of a Class
104
Fuzzy Sets for specific linguistic terms
108
Fuzzy Set FastCar
110
Example for an Aggregation
112
Crisp Approaches for MultiQbjective Optimization
114
Algorithm to specify a Fuzzy MultiCriteria Design Model
115
optimizationdirected perspective
117
10
120
Optimization in the case of Fuzziness multicriteria several realization of SPEC
121
Two Substitute Criteria in the MADM Case
122
Modifications of DECON1
126
Basic Algorithm of Sequential Configuration
132
A particular Branch and Bound Strategy
139
Cabin Layout that was configured with XKL
142
26
143
Customers Requirement for a certain Seat Pitch
144
A selection of existing space launch systems
145
Specialization Hierarchy of Space Launch Systems
146
Partof Hierarchy for STSObjects
148
Example Logistic Layout
150
Transportation of letters an example
151
Graphical User Interface
152
Subgraph to represent a PC
154
Europe
158
The Conceptual Hierarchy of the RAINSmodel incomplete because of the complexity
159
Fuzzy Set ComfortableDistance
181
Fuzzy Set LargeSeatNumber related to a business class
182
Illustration of the BestFirstSearch Part of the BaB Algo
188
rithm
191
An algorithm to estimate the start mass
192
Part of the goal hierarchy and alternatives STSs
195
Linguistic Variable Noise Intensity
197
Specialization Hierarchy of Logisit Objects
198
Simplified Compositional Hierarchy
199
Membership function of a fuzzy set preferredservicetime mailbox
201
53
210
Costfunction fix for a sourceregion k
211
Membership function for AcceptableGridDeposition
212
Membership function for AcceptableCost
213
Fuzzy Sets to model EmissionlevelofSourceregionk
214
Membership function to model an objective as fuzzy constraint
216
Architecture of the Overall Modelling Approach
219
A special requirement model
222
Fuzzy constraint Desired Cost Level
224
Aggregation tree
225
Chapter 4
227
MANAGEMENT OF UNCERTAIN
233
Aspects for Modeling Uncertain Information
235
73
237
Presentation of uncertainties on a contents level described in EXPRESSG
238
Determining the informationmaturity
239
EXPRESSG Model for structuring information using an object oriented schema
245
First step for the use of informationmaturity in Simultaneous Engineering
246
Second and third step for the use of informationmaturity in Simultaneous Engineering
247
APPLICATION OF THE FUZZY AHP METHOD FOR ASSESSING ALTERNATIVE PRODUCTION CYCLES M Weck F Klocke H Schell and E Ri...
251
Introduction
252
Selecting which Assessment Method to Apply
253
Structuring the decisionmaking problem and deriving a suit able method of assessment
254
Extract of the hierarchy in a decisionmaking problem
255
Methods of Weighting and Assessing Stages of Production
256
Determining Kv the number relating to a specific process
258
Assessing Production Cycles
259
Example of an Assessment Process
260
Cycles for manufacturing a gear shaft
261
Result of the assessment of the alternatives
263
A METHOD FOR PERSONNEL SELECTION IN CONCURRENT ENGINEERING USING FUZZY SETS J Stahl
265
Introduction
266
Integrated Personnel Planning in CE
267
Hierarchical Structure of KSAOs
268
Hierarchical Structure of KSAOs
269
Example for Membership Functions of Ordinal Criteria
271
Derivation of the Membership Functions for the Linguistic Description
272
Nominal Criteria
273
Metric Criteria
274
Conclusion
275
INDEX
277
166
278
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