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45
Engineering Design Calculations with Fuzzy Parameters. Fuzzy Sets and Systems
, 1992
"... Uncertainty in engineering analysis usually pertains to stochastic uncertainty, i.e.,variance in product or process parameters characterized by probability (uncertainty in truth). Methods for calculating under stochastic uncertainty are well documented. It has been proposed by the authors that other ..."
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Cited by 34 (13 self)
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Uncertainty in engineering analysis usually pertains to stochastic uncertainty, i.e.,variance in product or process parameters characterized by probability (uncertainty in truth). Methods for calculating under stochastic uncertainty are well documented. It has been proposed by the authors that other forms of uncertainty exist in engineering design. Imprecision, or the concept of uncertainty in choice, is one such form. This paper considers realtime techniques for calculating with imprecise parameters. These techniques utilize interval mathematics and the notion of αcuts from the fuzzy calculus. The extremes or anomalies of the techniques are also investigated, particularly the evaluation of singular or multivalued functions. It will be shown that realistic engineering functions can be used in imprecision calculations, with reasonable computational performance.
Imprecision in Engineering Design
 ASME JOURNAL OF MECHANICAL DESIGN
, 1995
"... Methods for incorporating imprecision in engineering design decisionmaking are briefly reviewed and compared. A tutorial is presented on the Method of Imprecision (MoI), a formal method, based on the mathematics of fuzzy sets, for representing and manipulating imprecision in engineering design. The ..."
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Cited by 33 (6 self)
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Methods for incorporating imprecision in engineering design decisionmaking are briefly reviewed and compared. A tutorial is presented on the Method of Imprecision (MoI), a formal method, based on the mathematics of fuzzy sets, for representing and manipulating imprecision in engineering design. The results of a design cost estimation example, utilizing a new informal cost specification, are presented. The MoI can provide formal information upon which to base decisions during preliminary engineering design and can facilitate setbased concurrent design.
Aggregation Functions for Engineering Design Tradeoffs
, 1998
"... The choice of an aggregation function is a common problem in Multi Attribute Decision Making (MADM) systems. The Method of Imprecision (MoI) is a formal theory for the manipulation of preliminary design information that represents preferences among design alternatives with the mathematics of fuzzy s ..."
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Cited by 25 (14 self)
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The choice of an aggregation function is a common problem in Multi Attribute Decision Making (MADM) systems. The Method of Imprecision (MoI) is a formal theory for the manipulation of preliminary design information that represents preferences among design alternatives with the mathematics of fuzzy sets. The MoI formulates the preliminary design problem as a MADM problem. To date, two aggregation functions have been developed for the MoI, one representing a compensating strategy and one a noncompensating strategy. Much of the prior fuzzy sets research on aggregation functions has been inappropriate for application to engineering design. In this paper, the selection of an aggregation function for MADM schemes is discussed within the context of the MoI. The general restrictions on designappropriate aggregation functions are outlined, and a family of functions, modeling a range of tradeoff strategies, is presented. The results are illustrated with an example.
TUNING PARAMETERS IN ENGINEERING DESIGN
, 1993
"... In the design and manufacture of mechanical devices, there are parameters whose values are determined by the manufacturing process in response to errors introduced in the device’s manufacture or operating environment. Such parameters are termed tuning parameters, and are distinct from design paramet ..."
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Cited by 20 (9 self)
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In the design and manufacture of mechanical devices, there are parameters whose values are determined by the manufacturing process in response to errors introduced in the device’s manufacture or operating environment. Such parameters are termed tuning parameters, and are distinct from design parameters which the designer selects values for as a part of the design process. This paper introduces tuning parameters into the design methods of: optimization, Taguchi’s method, and the method of imprecision [10]. The details of the mathematical formulation, along with a design example, are presented and discussed. Including tuning parameters in the design process can result in designs that are more tolerant of variational noise.
The method of imprecision compared to utility theory for design selection problems
 In Proceedings of the 1993 ASME Design Theory and Methodology Conference
, 1993
"... Two methods have been proposed for manipulating uncertainty reflecting designer choice: utility theory and the method of imprecision. Both methods represent this uncertainty across decision making attributes with zero to one ranks, higher preference modeled with a higher rank. The two methods can di ..."
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Cited by 20 (5 self)
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Two methods have been proposed for manipulating uncertainty reflecting designer choice: utility theory and the method of imprecision. Both methods represent this uncertainty across decision making attributes with zero to one ranks, higher preference modeled with a higher rank. The two methods can differ, however, in the combination metrics used to combine the ranks of the incommensurate design attributes. Utility theory resolves the multiattributes using various well proven additive metrics. In contrast, the method of imprecision resolves by also considering nonadditive metrics, such as ranking by the worst case performance or by multiplicative metrics. The axioms of utility theory are appropriate for designs where it is deemed the attributes can always be traded off, even to the point of achieving zero preference in some attributes. In the case of a design with attributes which cannot have zero preference, such as stress limits or maximum allowed cost, the method of imprecision is more appropriate: it trades off attribute levels without permitting any of them to be traded off to zero performance. 1
FORMALISMS FOR NEGOTIATION IN ENGINEERING DESIGN
, 1996
"... Engineering projects often undergo several design iterations before being completed. Information received from other groups working on a project (analysis, manufacturing, marketing, sales) will often necessitate changes in a design. The interaction between different groups associated with a design p ..."
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Cited by 20 (5 self)
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Engineering projects often undergo several design iterations before being completed. Information received from other groups working on a project (analysis, manufacturing, marketing, sales) will often necessitate changes in a design. The interaction between different groups associated with a design project often takes the form of informal “negotiation. ” This form of interaction commonly arises when engineering information is imprecise. The Method of Imprecision (MoI) is a formal method for the representation and manipulation of preliminary and imprecise design information. It provides a mechanism for the formalization of these informal negotiations. The nature and scope of informal negotiation in engineering is explored and discussed, and application of the MoI is illustrated with an example.
Extensions to the Taguchi Method of Product Design
, 1991
"... The Taguchi method of product design is an experimental approximation to minimizing the expected value of target variance for certain classes of problems. Taguchi’s method is extended to designs which involve variables each of which has a range of values all of which must be satisfied (necessity), a ..."
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Cited by 20 (6 self)
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The Taguchi method of product design is an experimental approximation to minimizing the expected value of target variance for certain classes of problems. Taguchi’s method is extended to designs which involve variables each of which has a range of values all of which must be satisfied (necessity), and designs which involve variables each of which has a range of values any of which might be used (possibility). Tuning parameters, as a part of the design process, are also demonstrated within Taguchi’s method. The method is also extended to solve design problems with constraints, invoking the methods of constrained optimization. Finally, the Taguchi method uses a factorial method to search the design space, with a confined definition of an optimal solution. This is compared with other methods of searching the design space and their definitions of an optimal solution.
Antonsson, “TradeOff strategies in engineering design
 Res. Eng. Design
, 1991
"... A formal method to allow designers to explicitly make tradeoff decisions is presented. The methodology can be used when an engineer wishes to rate the design by the weakest aspect, or by cooperatively considering the overall performance, or a combination of these strategies. The design problem is f ..."
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Cited by 16 (11 self)
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A formal method to allow designers to explicitly make tradeoff decisions is presented. The methodology can be used when an engineer wishes to rate the design by the weakest aspect, or by cooperatively considering the overall performance, or a combination of these strategies. The design problem is formulated with preference rankings, similar to a utility theory or fuzzy sets approach. This approach separates the design tradeoff strategy from the performance expressions. The details of the mathematical formulation are presented and discussed, along with two design examples: one from the preliminary design domain, and one from the parameter design domain. 1
Integrated Modeling, FiniteElement Analysis, and Engineering Design for ThinShell Structures using Subdivision
 ComputerAided Design
, 2002
"... Many engineering des98 applications require geometric modeling and mechanical s imulation of thin flexibles tructures ,s uchas thos e found in the automotive and aerosH ce indus ries Traditionally, geometric modeling, mechanical s mulation, and engineering des ign are treated as s eparate modules re ..."
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Cited by 14 (2 self)
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Many engineering des98 applications require geometric modeling and mechanical s imulation of thin flexibles tructures ,s uchas thos e found in the automotive and aerosH ce indus ries Traditionally, geometric modeling, mechanical s mulation, and engineering des ign are treated as s eparate modules requiring di#erent methods and represR tations Due to the incompatibility of the involved repres9 tations the trans ition from geometric modeling to mechanicals imulation,as wellas in the oppos ite direction, requires s ubs tantial e#ort. However, for engineering des ign purpos es e# cient trans ition between geometric modeling and mechanicalsa ulationis esio tial. We propos e the us ofs ubdivis ons5AP ces as a common foundation for modeling, s mulation, and des gn in a unified framework. Subdivis ons686 ces provide a flexible and e#cient tool for arbitrary topology freeforms urface modeling, avoiding many of the problems inherent in traditionals pline patch bas d approaches The underlying bass functions are als ideallys5 ted for a finiteelement treatment of thes ocalled thins hell equations , which des cribe the mechanical behavior of the modeleds tructures The res ulting s lvers are highly s alable, providing an e#cient computational foundation for des ign exploration and optimization. We demons rate our claims withs everal des5R examples s howing the versH6P64 y and high accuracy of the propos d method. Key words: Subdivis on Surfaces FiniteElements Shells ; 1
Quantitative Inference in a Mechanical Design "Compiler"
 Massachusetts Institute of Technology
, 1989
"... or hydraulic power transmission system, plus specifications and a utility function, and returns catalog numbers from predefined catalogs for the optimal selection of components implementing the design. Unlike programs for designing single components or systems, this program provides the designer wit ..."
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Cited by 13 (2 self)
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or hydraulic power transmission system, plus specifications and a utility function, and returns catalog numbers from predefined catalogs for the optimal selection of components implementing the design. Unlike programs for designing single components or systems, this program provides the designer with a high level "language" in which to compose new designs. It then performs some of the detailed design process for him. The process of "compilation", or transformation from a high to a low level description, is based on a formalization of quantitative inferences about hierarchically organized sets of artifacts and operating conditions. This allows design compilation without the exhaustive enumeration of alternatives. The paper introduces the formalism, illustrating its use with examples. It then outlines some differences from previous work, and summarizes early tests and conclusions.