On Validating Engineering Design Decision Support Tools

Olewnik, Andrew; Lewis, Kemper

doi:10.1177/1063293x05053796

Cited by 59 publications

(49 citation statements)

References 15 publications

(19 reference statements)

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“…The working group recommended additional research regarding the theory and practice underlying decision making in AA to improve the effect of various analytical tools and decision approaches and support tools for the deliberative process (Malloy et al 2017a). Normative standards such as fairness, accountability, and legitimacy can be drawn from the social science and regulatory literature (Olewnik and Lewis 2005;Malloy et al 2015). There is a need for standards of practice for addressing transparency in AA decision making.…”

Section: Decision Making and Decision Analysis: Priority Research Needsmentioning

confidence: 99%

Advancing Alternatives Assessment for Safer Chemical Substitution: A Research and Practice Agenda

Tickner

Jacobs

Malloy

et al. 2018

Integr Envir Assess & Manag

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Alternatives assessment has emerged as a science policy field that supports the evaluation and adoption of safer chemistries in manufacturing processes and consumer products. The recent surge in the development and practice of alternatives assessment has revealed notable methodological challenges. Spurred by this need, we convened an informal community of practice comprising industry experts, academics, and scientists within government and nongovernmental organizations to prioritize a research and practice agenda for the next 5 years that, if implemented, would significantly advance the field of alternatives assessment. With input from over 40 experts, the agenda outlines specific needs to advance methods, tools, and guidance in 5 critical areas: hazard assessment, comparative exposure characterization, life cycle considerations, decision making, and professional practice. Fifteen research and practice needs were identified, ranging from relatively simple efforts to define a minimum hazard data set to the development of more complex performance and decision-analytic methods and data integration tools. Some research needs involve adapting existing approaches to the alternatives assessment context, while others will require the development of entirely new methods and tools. The proposed research and practice agenda is ambitious. Implementing it will require expanding the current network of researchers from academia, government, and industry, as well as increased funding for methodological, application, and evaluation research. Integr Environ Assess Manag 2018;00:000-000. © 2018 SETAC.

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Section: Decision Making and Decision Analysis: Priority Research Needsmentioning

confidence: 99%

Advancing Alternatives Assessment for Safer Chemical Substitution: A Research and Practice Agenda

Tickner

Jacobs

Malloy

et al. 2018

Integr Envir Assess & Manag

View full text Add to dashboard Cite

show abstract

“…We agree with Hazelrigg that many attention-directing tools are mathematically flawed and produce inherently inconsistent results. We also concur that there is a fundamental need for substantiating any method from a theoretical or mathematical standpoint (see, e.g., [1,21]). However, we assert that validation is not complete without considering the subjective or practical aspects of a method (see, e.g., [22]) and that effective use of a method is contingent upon a fundamental understanding of underlying assumptions and inherent limitations that is often missing.…”

Section: Resultsmentioning

confidence: 99%

Decision Support in Concurrent Engineering – The Utility-Based Selection Decision Support Problem

Fernández

Seepersad²,

Rosen

et al. 2005

Concurrent Engineering

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Decisions are an important part of Concurrent Engineering and engineering design in general. Accordingly, more attention should be paid to the means and methods for making these decisions. In this article, a utility-based decision support method for the selection of an engineering design is presented. The utility-based selection decision support problem (u-sDSP) is a synthesized construct that facilitates selection decisions involving trade-offs among multiple, conflicting attributes and mitigation of risk associated with uncertain performance with respect to the attributes considered. The negative impact of unnecessary iterations on the product development cycle is reduced via the assurance of preference-consistent outcomes. Specifically, utility theory provides a mathematically rigorous means of clarifying and capturing designer preferences as well as identifying a preferred alternative in the context of stochastic uncertainty, while the selection decision support problem (DSP) -the construct within which utility theory is employed -facilitates the effective use of engineering judgment for (1) formulating and bounding decisions and (2) establishing a proper context. Application of the u-sDSP is illustrated with an example from rapid prototyping (RP), in which the goal is to select the appropriate technology and material combinations for testing the snap-fit design of a light switch cover plate assembly.

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“…This approach bears some similarity to that employed by Olewnik and Lewis (2005;2008) to study design decision support tools. First, individual preferences for different variations of a parameterized drinking mug were measured through experiential conjoint methodology.…”

Section: Methodsmentioning

confidence: 99%

Impossible by design? Fairness, strategy, and Arrow’s impossibility theorem

McComb¹,

Cagan²,

Goucher-Lambert³

2018

Preprint

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The design process often requires work by teams, rather than individuals. During teambased design it is likely that situations will arise in which individual members of the team have different opinions, yet a group decision must still be made. Unfortunately, Arrow's Impossibility Theorem indicates that there is no method for aggregating group preferences that will always satisfy a small number of "fair" conditions. This work seeks to identify methods of combining individual preferences that can come close to satisfying Arrow's conditions, enabling decisions that are fairer in practice. First, experiential conjoint analysis was used to obtain individual empirical utility functions for drinking mug designs. Each empirical utility function represented individual members who were part of a design team. Then, a number of functions for constructing group preference were analysed using both randomly generated preferences and empirical preferences derived from the experiential conjoint survey. The analysis involved checking each of Arrow's conditions, as well as assessing the potential impact of strategic voting.Based on the results, methods that should be used to aggregate group preference within a design team in practice were identified and recommended.2

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On Validating Engineering Design Decision Support Tools

Cited by 59 publications

References 15 publications

Advancing Alternatives Assessment for Safer Chemical Substitution: A Research and Practice Agenda

Advancing Alternatives Assessment for Safer Chemical Substitution: A Research and Practice Agenda

Decision Support in Concurrent Engineering – The Utility-Based Selection Decision Support Problem

Impossible by design? Fairness, strategy, and Arrow’s impossibility theorem

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