Non-Intuitive Dependent Decision Making: Sub-Optimal Design Selection

2015 ◽  
Author(s):  
K. Daniel Cooksey ◽  
Dimitri Mavris
Keyword(s):  
Decision Making ◽  
Optimal Design ◽  
Robust Design ◽  
Design Methodology ◽  
Design Decision ◽  
Implicit Assumption ◽  
Optimal Selection ◽  
Traditional Design ◽  
Design Alternatives ◽  
Design Selection

This paper explores a flaw in traditional design decision making (including optimization) when uncertainty is present. It introduces the concept of the Non-Intuitive Dependent Decision Making (NIDDM) problem, where the assumption that each of the design alternatives is independent can be false due to a common underlying uncertainty. In this situation, the implicit assumption that design alternatives are independent can lead to a sub-optimal selection. This paper provides a simplified example of the NIDDM problem, and uses this to define the conditions where the NIDDM problem arises. An aerospace design toolset is then used to explore the NIDDM problem in realistic conditions, and a discussion is presented about when traditional robust design processes are appropriate or an alternative design methodology is needed.

scholarly journals Integrating Value Considerations in the Decision Making for the Design of Biorefineries

2020 ◽  
Vol 26 (6) ◽  
pp. 2927-2955
Author(s):  
Mar Palmeros Parada ◽  
Lotte Asveld ◽  
Patricia Osseweijer ◽  
John Alexander Posada
Keyword(s):  
Decision Making ◽  
Complex Systems ◽  
Research And Development ◽  
Design Process ◽  
Design Decision ◽  
Value Sensitive Design ◽  
Design Practice ◽  
Novel Approach ◽  
Design Alternatives ◽  
Biobased Production

AbstractBiobased production has been promoted as a sustainable alternative to fossil resources. However, controversies over its impact on sustainability highlight societal concerns, value tensions and uncertainties that have not been taken into account during its development. In this work, the consideration of stakeholders’ values in a biorefinery design project is investigated. Value sensitive design (VSD) is a promising approach to the design of technologies with consideration of stakeholders’ values, however, it is not directly applicable for complex systems like biorefineries. Therefore, some elements of VSD, such as the identification of relevant values and their connection to a technology’s features, are brought into biorefinery design practice. Midstream modulation (MM), an approach to promoting the consideration of societal aspects during research and development activities, is applied to promote reflection and value considerations during the design decision making. As result, it is shown that MM interventions during the design process led to new design alternatives in support of stakeholders' values, and allowed to recognize and respond to emerging value tensions within the scope of the project. In this way, the present work shows a novel approach for the technical investigation of VSD, especially for biorefineries. Also, based on this work it is argued that not only reflection, but also flexibility and openness are important for the application of VSD in the context of biorefinery design.

Mechanical design, multiple criteria decision making and Pareto optimality gap

2016 ◽  
Vol 33 (3) ◽  
Author(s):  
Ignacy Kaliszewski ◽  
Tomasz Kiczkowiak ◽  
Janusz Miroforidis
Keyword(s):  
Decision Making ◽  
Pareto Optimality ◽  
Design Methodology ◽  
Pareto Front ◽  
Mechanical Design ◽  
Pareto Optimal ◽  
Design Problems ◽  
Design Selection ◽  
Optimality Gap ◽  
Practical Implications

Purpose We present an approach to multiple criteria mechanical design problems, for cases where problem complexity precludes derivation of the whole Pareto front. For such problems we propose to limit search, and hence also derivation, of the Pareto front exclusively to regions of the direct designer’s interest, thus saving on computing efforts and gaining on tractable problem sizes. Design/methodology/approach To achieve the purpose, we frame the decision making process (design) into a combination of three specific concepts, namely decision maker's preference capture, local Pareto front search and approximate multiobjective optimization with assessments of the Pareto optimality gap. We illustrate the approach with two small design problems, namely Pareto optimal round tube beam and Pareto optimal pneumatic high speed machine drive selection. We solve these problems in a setting which can be regarded as representative for problem solving in real environment. Findings On the decision making side, the proposed approach has turned out to be a versatile tool for selecting designs from the Pareto suboptimal ones, where each such a Pareto suboptimal design has an explicit assessment of the Pareto optimality gap. On the technical (optimization) side, it has been demonstrated that the approach seamlessly works with evolutionary computations, structured to the specific needs of the approach. Research limitations/implications It has been shown that the navigation over the Pareto front can be achieved with limited effort, both on the cognitive and the computing side. Moreover, navigation over the Pareto front can be focused from the very beginning of the design selection process on the regions of the Pareto front which are of the direct designer’s interest. This eliminates the need to derive (or only approximate) the whole Pareto front, a tangible asset as the derivation of that set is the main factor precluding scalability of design selection problems to higher dimensions (to higher problem sizes). Practical implications Because of the general formulation of the Pareto optimal design selection problem considered in the paper, the absence of any assumptions on its form and easiness of implementation of the underlying procedure of the proposed approach, the paper offers a clear option to approaches based on classical optimization computations. Originality/value The approach offers derivation of Pareto suboptimal designs with assessments of the Pareto optimality gap, whereas currently available multiobjective evolutionary optimization algorithms which derive Pareto suboptimal designs as well, offer no such assessments. Thus, the approach provides a firm ground to valuate designs resulting from approximate multiobjective optimization computations.

Risk-Based Decision-Making for Managing Resources During the Design of Complex Space Exploration Systems

2006 ◽  
Vol 128 (4) ◽  
pp. 1014-1022 ◽  
Author(s):  
Ali Farhang Mehr ◽  
Irem Y. Tumer
Keyword(s):  
Decision Making ◽  
Resource Management ◽  
Design Methodology ◽  
Complex Space ◽  
Risk Mitigation ◽  
Space Exploration ◽  
Integrated Design ◽  
System Level ◽  
Design Decision ◽  
Risk Elements

Complex space exploration systems are often designed in collaborative engineering environments where requirements and design decisions by various subsystem engineers have a great impact on the overall risk of the mission. As a result, the system-level management should allocate risk mitigation resources (e.g., capital to place additional sensors or to improve the current technology) among various risk elements such that the main objectives of the system are achieved as closely as possible. Minimizing risk has been long accepted as one of the major drivers for system-level decisions and particularly resource management. In this context, Risk-Based Decision Making refers to a process that allocates resources in such a way that the expected risk of the overall system is minimized. This paper presents a new risk-based design decision-making method, referred to as Risk and Uncertainty Based Concurrent Integrated Design Methodology or RUBIC Design Methodology for short. The new approach is based on concepts from portfolio optimization theory and continuous resource management, extended to provide a mathematical rigor for risk-based decision-making during the design of complex space exploration systems. The RUBIC design method is based on the idea that a unit of resource, allocated to mitigate a certain risk in the system, contributes to the overall system risk reduction in the following two ways: (1) by mitigating that particular risk; and (2) by impacting other risk elements in the system (i.e., the correlation among various risk elements). RUBIC then provides a probabilistic framework for reducing the expected risk of the final system via optimal allocation of available risk-mitigation resources. The application of the proposed approach is demonstrated using a satellite reaction wheel example.

Aiding Design Decision Making: Adapting Mathematical Paradigms to Fit Designers’ Actual Needs

2008 ◽  
Author(s):  
C. C. Hayes ◽  
F. Akhavi
Keyword(s):  
Decision Making ◽  
Mathematical Models ◽  
Ethnographic Study ◽  
Design Decision ◽  
Quality Cost ◽  
Design Alternatives ◽  
Selection Decisions ◽  
Product Decision ◽  
Further Development

When designing products, designers compare complex alternatives and select one or more for further development. The quality of these selection decisions directly impacts the quality, cost and safety of the final product. Decision theoretic approaches for making systematic comparisons might help in this process, yet designers do not tend to use them. The goals of this work are to begin understanding why, and to identify future questions that may lead to solutions. This paper summarizes the results of two studies, 1) an ethnographic study of working designers in which their actual practices and needs were observed during decision making, and 2) a laboratory study in which designers were asked to use mathematical models to compare and select design alternatives. Based on these studies, we conclude that the mathematical models, as formulated, are not well suited to designers’ needs. We propose a research agenda that may lead to new approaches combining decision theoretic and user-centered methods to create tools that the average designer will be willing to use.

Preference Inconsistency in Multidisciplinary Design Decision Making

2009 ◽  
Vol 131 (3) ◽  
Author(s):  
Erin F. MacDonald ◽  
Richard Gonzalez ◽  
Panos Y. Papalambros
Keyword(s):  
Decision Making ◽  
A Priori ◽  
User Preferences ◽  
Revealed Preferences ◽  
Design Decision ◽  
Implicit Assumption ◽  
Product Attributes ◽  
Choice Analysis ◽  
Market Opportunities ◽  
Perceived Relationships

A common implicit assumption in engineering design is that user preferences exist a priori. However, research from behavioral psychology and experimental economics suggests that individuals construct preferences on a case-by-case basis when called to make a decision rather than referring to an existing preference structure. Thus, across different contexts, preference elicitation methods used in design decision making can lead to preference inconsistencies. This paper offers a framework for understanding preference inconsistencies, giving three examples of preference inconsistencies that demonstrate the implications of unnoticed inconsistencies, and also discusses the design benefits of testing for inconsistencies. Three common engineering and marketing design methods are discussed: discrete choice analysis, modeling stated versus revealed preferences, and the Kano method. In these examples, we discuss perceived relationships between product attributes, identify market opportunities for a “green” product, and show how people find it is easier to imagine delight rather than necessity of product attributes. Understanding preference inconsistencies offers new insights into the relationship between user and product design.

Preference Inconsistency in Multidisciplinary Design Decision Making

2007 ◽  
Author(s):  
Erin MacDonald ◽  
Richard Gonzalez ◽  
Panos Papalambros
Keyword(s):  
Decision Making ◽  
A Priori ◽  
User Preferences ◽  
Revealed Preferences ◽  
Design Decision ◽  
Implicit Assumption ◽  
Preference Construction ◽  
Choice Analysis ◽  
The Impact ◽  
The Relationship

Research from behavioral psychology and experimental economics asserts that individuals construct preferences on a case-by-case basis when called to make a decision. A common, implicit assumption in engineering design is that user preferences exist a priori. Thus, preference elicitation methods used in design decision making can lead to preference inconsistencies across elicitation scenarios. This paper offers a framework for understanding preference inconsistencies, within and across individual users. We give examples of three components of this new framework: comparative, internal, and external inconsistencies across users. The examples demonstrate the impact of inconsistent preference construction on common engineering and marketing design methods, including discrete choice analysis, modeling stated vs. revealed preferences, and the Kano method and thus QFD. Exploring and explaining preference inconsistencies produces new understandings of the relationship between user and product.

A Shape Optimal Design Methodology for Packaging Design

1992 ◽  
Vol 114 (4) ◽  
pp. 461-466 ◽  
Author(s):  
S. D. Rajan ◽  
Ben Nagaraj ◽  
Mali Mahalingam
Keyword(s):  
Finite Element ◽  
Optimal Design ◽  
Design Methodology ◽  
Design Tool ◽  
Nonlinear Finite Element ◽  
Finite Element Analyses ◽  
Design Problems ◽  
Packaging Design ◽  
Optimal Shapes ◽  
Design Alternatives

Shape optimal design methodology has been used as a design tool in the automotive and aerospace industries for quite some time now. In the present work the hybrid natural shape optimal design approach is used along with a nonlinear programming (NLP) technique to find the optimal shapes of electronic packaging components. The design problems are formulated as min-max problems and linear and materially nonlinear finite element analyses provide the function values. The applicability of the developed methodology is illustrated using a design example that deals with the packaging design of a plastic pad array carrier digital package. The results indicate that the methodology can be used either as an effective way of evaluating different design alternatives or refining existing designs.

Performance Estimation and Robust Design Decisions

2000 ◽  
Author(s):  
Xiao Tang ◽  
Sundar Krishnamurty
Keyword(s):  
Decision Making ◽  
Engineering Design ◽  
Robust Design ◽  
Estimation Method ◽  
Performance Estimation ◽  
Accurate Estimation ◽  
Design Decision ◽  
Computationally Efficient ◽  
Design Variables ◽  
Highly Nonlinear

Abstract This paper deals with two major issues critical to the development and implementation of a decision-based robust design, namely, representation of design performance under conditions of uncertainty and the development of a robust design decision model. Specifically, this paper presents a computationally efficient procedure for accurate estimation of performance variance using a novel Surround Point Method (SPM) and discusses its incorporation into a decision-based robust design framework. Results indicate that by mimicking effects from Monte-Carlo Simulation (MCS), SPM-based uncertainty estimation method appears to offer the best promise in achieving an optimal balance between computational complexity and design-scenario independence. It can be expected to be a viable and applicable probability estimation tool in generic engineering design, and particularly useful in highly nonlinear configuration design with many design variables. Furthermore, to explicitly incorporate robustness criteria, this paper introduces the concept of design evaluation level as a means for decision-making in an evolving design process. Using this concept, this paper introduces a robust decision-based design methodology that can methodically handle multiple performance attributes, system constraints, and robustness issues in engineering design. These issues are discussed in the context of engineering design decision-making with the aid of a simple case study and the results are discussed.

Fuzzing Ratings for Multiattribute Design Decision-Making

1994 ◽  
Vol 116 (2) ◽  
pp. 511-521 ◽  
Author(s):  
J. V. Carnahan ◽  
D. L. Thurston ◽  
T. Liu
Keyword(s):  
Decision Making ◽  
Line Segment ◽  
Relative Weight ◽  
Design Decision ◽  
Analytic Hierarchy ◽  
Fuzzy Distance ◽  
Attribute Weights ◽  
Design Alternatives ◽  
Small Set ◽  
Universe Of Discourse

Early in the design process, problems can arise when information is incomplete and goals are not known precisely. When preliminary design evaluation is approached as a multiattribute decision-making problem, both the levels of attributes and their relative importance can be treated as fuzzy numbers elicited from the designer. However, information regarding estimated attribute levels might be lost in limiting the designer to the standard universe of discourse. Another problem is that the attribute weights might be difficult for the designer to determine. A methodology is demonstrated for ranking alternatives based on the fuzzy distance from a fuzzy goal. The concept of a fuzzy line segment is introduced in order to make the universe of discourse continuous, thus not restricting the designer to a small set of fuzzy inputs. The fuzzy line segment makes it possible to more closely reflect the designer’s estimates of performance of design alternatives and the relative weight assigned to each attribute. It facilitates more accurate and precise linguistic input, and also provides a way to “fuzzify” numeric input. As a result, Saaty’s Analytic Hierarchy Process (AHP) can be employed to assist the designer in more accurately determining attribute weights.

Momentum exchange impact damper design methodology for object-wall-collision problems

2017 ◽  
Vol 24 (14) ◽  
pp. 3206-3218
Author(s):  
Yohei Kushida ◽  
Hiroaki Umehara ◽  
Susumu Hara ◽  
Keisuke Yamada
Keyword(s):  
Optimal Design ◽  
Design Methodology ◽  
Design Parameters ◽  
Momentum Exchange ◽  
Impact Damper ◽  
One Dimensional ◽  
Practical Design ◽  
Wall Collision ◽  
Damper Design ◽  
And Control

Momentum exchange impact dampers (MEIDs) were proposed to control the shock responses of mechanical structures. They were applied to reduce floor shock vibrations and control lunar/planetary exploration spacecraft landings. MEIDs are required to control an object’s velocity and displacement, especially for applications involving spacecraft landing. Previous studies verified numerous MEID performances through various types of simulations and experiments. However, previous studies discussing the optimal design methodology for MEIDs are limited. This study explicitly derived the optimal design parameters of MEIDs, which control the controlled object’s displacement and velocity to zero in one-dimensional motion. In addition, the study derived sub-optimal design parameters to control the controlled object’s velocity within a reasonable approximation to derive a practical design methodology for MEIDs. The derived sub-optimal design methodology could also be applied to MEIDs in two-dimensional motion. Furthermore, simulations conducted in the study verified the performances of MEIDs with optimal/sub-optimal design parameters.

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