A Fuzzy Sets Approach to Computational Tools for Preliminary Engineering Design

1987 ◽  
Author(s):  
K. L. Wood ◽  
E. K. Antonsson
Keyword(s):  
Fuzzy Sets ◽  
Engineering Design ◽  
Data Driven ◽  
Preliminary Design ◽  
Engineering Structures ◽  
Design Decisions ◽  
Computational Tools ◽  
Alternative Technologies ◽  
Imprecise Parameters ◽  
Preliminary Phase

Abstract The primary goal of this research is to provide computational tools, or aids, to engineering designers, particularly for the preliminary phase of design. Such aids will be particularly useful in choosing between alternative technologies. Design choices of this nature are perhaps the most critical, and likely to be the most costly if in error. Our approach has been to aid preliminary design decisions with analysis tools developed for computations on imprecise parameters. Contemporary computers and algorithms are not well suited for manipulating imprecise descriptions of objects. To provide these basic tools, we are applying the mathematics of fuzzy sets. This approach (along with “data-driven programming”) appears to be well suited to our problem and has been applied to similar problems in analyzing civil engineering structures and failures.

A First Class of Computational Tools for Preliminary Engineering Design

1988 ◽  
Author(s):  
K. L. Wood ◽  
E. K. Antonsson
Keyword(s):  
Fuzzy Sets ◽  
Engineering Design ◽  
Preliminary Design ◽  
Functional Requirement ◽  
Computational Tool ◽  
Computational Tools ◽  
Input Parameters ◽  
Implementation Scheme ◽  
Design Calculations ◽  
Fuzzy Parameters

Abstract Preliminary engineering design intrinsically consists of imprecise descriptions of the input parameters. We present new conceptual and algorithmic procedures for dealing with such imprecise descriptions. Specifically, a two-part method is outlined for performing design calculations on these “fuzzy” parameters, as well as determining a measure for the parameters’ coupling. By interpreting the input set of variables for preliminary design in terms of fuzzy sets, we demonstrate how the engineer may associate his subjective meaning with the input parameters and the output functional requirement, leading to the foundation of our approach. An example of the method highlights the primary issues and the implementation scheme as a computational tool.

Data-driven design paradigm in engineering problems

2016 ◽  
Vol 231 (8) ◽  
pp. 1522-1534 ◽  
Author(s):  
Changqing Liu ◽  
Xiaoqian Chen
Keyword(s):  
Engineering Design ◽  
Data Driven ◽  
Decision Strategy ◽  
Design Problems ◽  
Design Decisions ◽  
Uncertainty Factors ◽  
Satellite Design ◽  
Engineering Design Problems ◽  
Engineering Problems ◽  
Design Paradigm

Engineering design problems can, in general, be discussed under the framework of decision making, namely engineering design decisions. Inherently, accounting for uncertainty factors is an indispensable part in these decision processes. In a sense, the goal of design decisions is to control or reduce the variational effect in decision consequences induced by many uncertainty factors, by optimizing an expected utility objective or other preference functions. In this paper, the value of data in facilitating making engineering design decisions is highlighted, and a data-driven design paradigm for practical engineering problems is proposed. The definition of data in this paradigm is elaborated first. Then the data involvement in a whole stage-based design process is investigated. An overall decision strategy for design problems under the data-driven paradigm is proposed. By a concrete satellite design example, the key ideas of the proposed data-driven design paradigm are demonstrated. Future work is also advised.

Aggregation Functions for Engineering Design Trade-Offs

1995 ◽  
Author(s):  
Michael J. Scott ◽  
Erik K. Antonsson
Keyword(s):  
Fuzzy Sets ◽  
Engineering Design ◽  
Formal Theory ◽  
Preliminary Design ◽  
Design Information ◽  
Trade Offs ◽  
Aggregation Functions ◽  
Design Alternatives

Abstract 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. Using the MoI, different design tradeoff strategies can be applied. To date, two aggregation functions have been developed for the MoI, one representing a compensating strategy and one a non-compensating strategy. Other research on aggregation functions on fuzzy sets has focused on two classes of functions that are not suitable for engineering design. The general restrictions on design-appropriate aggregation functions are discussed, and a family of functions ranging from the non-compensating min to the compensating product of powers is presented. An application to preliminary engineering design is given.

Computations with Imprecise Parameters in Engineering Design: Background and Theory

1989 ◽  
Vol 111 (4) ◽  
pp. 616-625 ◽  
Author(s):  
K. L. Wood ◽  
E. K. Antonsson
Keyword(s):  
Engineering Design ◽  
Weighted Average ◽  
Design Parameters ◽  
Average Technique ◽  
Design Elements ◽  
Input Design ◽  
Fuzzy Calculus ◽  
Design Calculations ◽  
Imprecise Parameters ◽  
Preliminary Phase

A technique to perform design calculations on imprecise representations of parameters has been developed and is presented. The level of imprecision in the description of design elements is typically high in the preliminary phase of engineering design. This imprecision is represented using the fuzzy calculus. Calculations can be performed using this method, to produce (imprecise) performance parameters from imprecise (input) design parameters. The Fuzzy Weighted Average technique is used to perform these calculations. A new metric, called the γ-level measure, is introduced to determine the relative coupling between imprecise inputs and outputs. The background and theory supporting this approach are presented, along with one example.

Optimization Methods for Calculating Design Imprecision

1995 ◽  
Author(s):  
William S. Law ◽  
Erik K. Antonsson
Keyword(s):  
Fuzzy Sets ◽  
Design Process ◽  
Optimization Methods ◽  
Experiment Design ◽  
Design Evaluation ◽  
Preliminary Design ◽  
New Methods ◽  
Evaluation Functions ◽  
Incomplete Design ◽  
Alternative Designs

Abstract The preliminary design process is characterized by imprecision: the vagueness of an incomplete design description. The Method of Imprecision uses the mathematics of fuzzy sets to explicitly represent and manipulate imprecise preliminary design information, enabling the designer to explore the space of alternative designs in the context of the designer and customer’s preferences among alternatives. This paper introduces new methods to perform Method of Imprecision calculations for general non-monotonic design evaluation functions that address the practical necessity to minimize the number of function evaluations. These methods utilize optimization and experiment design.

scholarly journals A conceptual simulation workflow to guide design decisions regarding the effects of daylight on occupants’ alertness

2021 ◽  
Vol 2042 (1) ◽  
pp. 012116
Author(s):  
Pierson Clotilde ◽  
Soto Magán Victoria Eugenia ◽  
Aarts Mariëlle ◽  
Andersen Marilyne
Keyword(s):  
Light Exposure ◽  
Well Being ◽  
Research Field ◽  
Decision Makers ◽  
Spectral Simulation ◽  
Design Decisions ◽  
Computational Tools ◽  
Recent Developments ◽  
The Impact

Abstract Recent developments in the lighting research field have demonstrated the importance of a proper exposure to light to mediate several of our behavioral and physiological responses. However, we spend nowadays around 90% of our time indoors with an often quite limited access to bright daylight. To be able to anticipate how much the built environment actually influences our light exposure, and how much it may ultimately impact our health, well-being, and productivity, new computational tools are needed. In this paper, we present a first attempt at a simulation workflow that integrates a spectral simulation tool with a light-driven prediction model of alertness. The goal is to optimize the effects of light on building occupants, by informing the decision makers about the impact of different design choices. The workflow is applied to a case study to provide an example of what learnings can be expected from it.

Computational Tools for the Reliability Assessment and the Engineering Design of Procedures and Devices in Bariatric Surgery

2020 ◽  
Vol 48 (10) ◽  
pp. 2466-2483 ◽  
Author(s):  
C. Salmaso ◽  
I. Toniolo ◽  
C. G. Fontanella ◽  
P. Da Roit ◽  
A. Albanese ◽  
...  
Keyword(s):  
Bariatric Surgery ◽  
Engineering Design ◽  
Reliability Assessment ◽  
Computational Tools

A Framework for Decision-Based Engineering Design

1998 ◽  
Vol 120 (4) ◽  
pp. 653-658 ◽  
Author(s):  
G. A. Hazelrigg
Keyword(s):  
Engineering Design ◽  
Operations Research ◽  
Quality Function Deployment ◽  
Value Theory ◽  
Decision Making Process ◽  
Design Decisions ◽  
Decision Sciences ◽  
Research Decision ◽  
Decision Based Design ◽  
Total Life

Engineering design is increasingly recognized as a decision-making process. This recognition brings with it the richness of many well-developed theories and methods from economics, operations research, decision sciences, and other disciplines. Done correctly, it forces the process of engineering design into a total systems context, and demands that design decisions account for a product’s total life cycle. It also provides a theory of design that is based on a rigorous set of axioms that underlie value theory. But the rigor of decision-based design also places stringent conditions on the process of engineering design that eliminate popular approaches such as Quality Function Deployment. This paper presents the underlying notions of decision-based design, points to some of the axioms that underlie the theory of decision-based design, and discusses the consequences of the theory on engineering education.

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