Arrow's Theorem and Engineering Design Decision Making

1999 ◽  
Vol 11 (4) ◽  
pp. 218-228 ◽  
Author(s):  
Michael J. Scott ◽  
Erik K. Antonsson
Keyword(s):  
Decision Making ◽  
Engineering Design ◽  
Design Decision ◽  
Arrow’S Theorem ◽  
Arrow's Theorem

A Preliminary Study of Novice and Expert Users’ Decision-Making Procedures During Visual Trade Space Exploration

2009 ◽  
Author(s):  
David Wolf ◽  
Timothy W. Simpson ◽  
Xiaolong Luke Zhang
Keyword(s):  
Decision Making ◽  
Engineering Design ◽  
Data Visualization ◽  
Space Exploration ◽  
Computational Thinking ◽  
Test Group ◽  
Design Decision ◽  
Ongoing Research ◽  
Trade Space Exploration ◽  
Insight Into

Thanks to recent advances in computing power and speed, designers can now generate a wealth of data on demand to support engineering design decision-making. Unfortunately, while the ability to generate and store new data continues to grow, methods and tools to support multi-dimensional data exploration have evolved at a much slower pace. Moreover, current methods and tools are often ill-equipped at accommodating evolving knowledge sources and expert-driven exploration that is being enabled by computational thinking. In this paper, we discuss ongoing research that seeks to transform decades-old decision-making paradigms rooted in operations research by considering how to effectively convert data into knowledge that enhances decision-making and leads to better designs. Specifically, we address decision-making within the area of trade space exploration by conducting human-computer interaction studies using multi-dimensional data visualization software that we have been developing. We first discuss a Pilot Study that was conducted to gain insight into expected differences between novice and expert decision-makers using a small test group. We then present the results of two Preliminary Experiments designed to gain insight into procedural differences in how novices and experts use multi-dimensional data visualization and exploration tools and to measure their ability to use these tools effectively when solving an engineering design problem. This work supports our goal of developing training protocols that support efficient and effective trade space exploration.

Manufacturing Investment and Allocation in Product Line Design Decision-Making

2005 ◽  
Author(s):  
Jeremy J. Michalek ◽  
Oben Ceryan ◽  
Panos Y. Papalambros ◽  
Yoram Koren
Keyword(s):  
Decision Making ◽  
Engineering Design ◽  
Product Line ◽  
Manufacturing Cost ◽  
Design Decision ◽  
Product Line Design ◽  
Product Decision ◽  
Market Consequences ◽  
Line Design ◽  
Is Design

An important aspect of product development is design for manufacturability (DFM) analysis that aims to incorporate manufacturing requirements into early product decision-making. Existing methods in DFM seldom quantify explicitly the tradeoffs between revenues and costs generated by making design choices that may be desirable in the market but costly to manufacture. This paper builds upon previous work coordinating models for engineering design and marketing product line decision-making by incorporating quantitative models of manufacturing investment and production allocation. The result is a methodology that considers engineering design decisions quantitatively in the context of manufacturing and market consequences in order to resolve tradeoffs, not only among performance objectives, but also between market preferences and manufacturing cost.

Imprecision in Engineering Design

1995 ◽  
Vol 117 (B) ◽  
pp. 25-32 ◽  
Author(s):  
E. K. Antonsson ◽  
K. N. Otto
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Engineering Design ◽  
Cost Estimation ◽  
Formal Method ◽  
Concurrent Design ◽  
Design Decision ◽  
Design Cost ◽  
Formal Information

Methods for incorporating imprecision in engineering design decision-making 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 set-based concurrent design.

Understanding the Utilization of Information Stimuli in Design Decision Making Using Eye Gaze Data

2015 ◽  
Author(s):  
Youyi Bi ◽  
Murtuza Shergadwala ◽  
Tahira Reid ◽  
Jitesh H. Panchal
Keyword(s):  
Decision Making ◽  
Engineering Design ◽  
Eye Gaze ◽  
Design Decision ◽  
Design Engineers ◽  
Cognitive Decision ◽  
Improved Design ◽  
Student Subjects ◽  
Types Of Information ◽  
Normative Models

Research on decision making in engineering design has focused primarily on how to make decisions using normative models given certain information. However, there exists a research gap on how diverse information stimuli are combined by designers in decision making. In this paper, we address the following question: how do designers weigh different information stimuli to make decisions in engineering design contexts? The answer to this question can provide insights on diverse cognitive models for decision making used by different individuals. We investigate the information gathering behavior of individuals using eye gaze data from a simulated engineering design task. The task involves optimizing an unknown function using an interface which provides two types of information stimuli, including a graph and a list area. These correspond to the graphical stimulus and numerical stimulus, respectively. The study was carried out using a set of student subjects. The results suggest that individuals weigh different forms of information stimuli differently. It is observed that graphical information stimulus assists the participants in optimizing the function with a higher accuracy. This study contributes to our understanding of how diverse information stimuli are utilized by design engineers to make decisions. The improved understanding of cognitive decision making models would also aid in improved design of decision support tools.

Streamlining ‘environment in design' decision-making – from concept to operations in major development projects

2018 ◽  
Vol 58 (2) ◽  
pp. 679
Author(s):  
Janine M. Barrow
Keyword(s):  
Decision Making ◽  
Engineering Design ◽  
Design Process ◽  
Practical Experience ◽  
Development Project ◽  
Hazard Identification ◽  
Design Decision ◽  
Engineering Design Process ◽  
Start Up ◽  
Major Development

As the engineering design process for a major development project advances from concept through to ready for start up, many key decisions are made and controls formulated that ultimately influence environmental, social (and safety) outcomes. These decisions are often made based on sound technical grounds with key decision logs, hazard identification or hazard and operability studies or similar used to record the process, but with limited recognition of environmental outcomes. Many of the onshore and offshore regulations in Australia (most notably, the Offshore Petroleum and Greenhouse Gas (Environment) Regulations 2009) require environmental risks and impacts to be reduced to a level that is as low as reasonably practicable (ALARP). Additionally, justifiable assessment of controls and decisions are presented in the environment plans (EP) that are typically prepared later on in the design process. Challenges can often arise when geographically disparate design contractors lack ALARP assessment processes to evaluate decisions and controls from an environmental perspective and record outcomes for future use in regulatory documentation. This can be particularly pronounced for operations EPs. Janine shares her practical experience in environmental integration in engineering design to showcase methods that tangibly demonstrate robust decision-making, inclusive of delivering environmental outcomes, to regulators.

Computationally Efficient Imprecise Uncertainty Propagation in Engineering Design and Decision Making

2012 ◽  
Author(s):  
Dipanjan D. Ghosh ◽  
Andrew Olewnik
Keyword(s):  
Decision Making ◽  
Engineering Design ◽  
Computational Efficiency ◽  
Design Problem ◽  
Uncertainty Propagation ◽  
Future Research ◽  
Parameter Estimates ◽  
Design Decision ◽  
Computationally Efficient ◽  
Imprecise Uncertainty

Modeling uncertainty through probabilistic representation in engineering design is common and important to decision making that considers risk. However, representations of uncertainty often ignore elements of “imprecision” that may limit the robustness of decisions. Further, current approaches that incorporate imprecision suffer from computational expense and relatively high solution error. This work presents the Computationally Efficient Imprecise Uncertainty Propagation (CEIUP) method which draws on existing approaches for propagation of imprecision and integrates sparse grid numerical integration to provide computational efficiency and low solution error for uncertainty propagation. The first part of the paper details the methodology and demonstrates improvements in both computational efficiency and solution accuracy as compared to the Optimized Parameter Sampling (OPS) approach for a set of numerical case studies. The second half of the paper is focused on estimation of non-dominated design parameter spaces using decision policies of Interval Dominance and Maximality Criterion in the context of set-based sequential design-decision making. A gear box design problem is presented and compared with OPS, demonstrating that CEIUP provides improved estimates of the non-dominated parameter range for satisfactory performance with faster solution times. Parameter estimates obtained for different risk attitudes are presented and analyzed from the perspective of Choice Theory leading to questions for future research. The paper concludes with an overview of design problem scenarios in which CEIUP is the preferred method and offers opportunities for extending the method.

Imprecision in Engineering Design

1995 ◽  
Vol 117 (B) ◽  
pp. 25-32 ◽  
Author(s):  
E. K. Antonsson ◽  
K. N. Otto
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Engineering Design ◽  
Cost Estimation ◽  
Formal Method ◽  
Concurrent Design ◽  
Design Decision ◽  
Design Cost ◽  
Formal Information

Methods for incorporating imprecision in engineering design decision-making 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 set-based concurrent design.

Preliminary Design Support System Based on a Generic Under-Constraint Solving Technique

2000 ◽  
Author(s):  
Hiroyuki Sawada ◽  
Xiu-Tian Yan
Keyword(s):  
Decision Making ◽  
Product Design ◽  
Engineering Design ◽  
Design Problem ◽  
Design Parameters ◽  
Problem Solver ◽  
Decision Making Process ◽  
Design Decision ◽  
Novel Approach ◽  
Design Support System

Abstract Engineering design is an intensive decision making process. A designer with an informative and insightful decision making support can usually produce high quality product design solutions with less or no rework. However, with current support designers very often face challenge or even difficulties as more and more design parameters come into design decision making process when a design progresses. This paper proposes a novel approach to providing designers with such a decision support by using under-constraint design problem solver. It is argued that design requirements represented in the form of Product Design Specifications (PDSs) can be converted into a set of related constraint expressions. These PDS constraint sets, which are usually incomplete, i.e., under-constrained, can then be solved by the solver to provide a designer with guided solutions for each design parameter, thus support a designer to make an informative and insightful design decision. A case study is finally presented in the paper to demonstrate how this approach is used to solve a real engineering design problem — a robotic finger system design.

A Context-Based Approach to Engineering Design Negotiation

2005 ◽  
Author(s):  
Mathieu Geslin ◽  
Yan Jin
Keyword(s):  
Decision Making ◽  
Engineering Design ◽  
Collaborative Design ◽  
Large Scale ◽  
Research Direction ◽  
Distributed Artificial Intelligence ◽  
Future Research ◽  
Design Decision ◽  
Context Model ◽  
Engineering Design Problems

Complex and large-scale engineering design problems require a collaborative approach in order to be completed in a timely manner. Designers involved in such work are making collaborative design decision, and often have to negotiate to address intricate problems and resolve their discrepancies while exploring the design space, generating new ideas and compromising for agreement. Advances in negotiation research have been made in social psychology, distributed artificial intelligence, and decision theory, but few have been applied to design. We advocate that design context information is of paramount importance in the decision-making process. In this paper, an argumentation-based negotiation model is introduced to support collaborative design decision-making. This model relies on clear design context model, argument model, negotiation protocol and strategies. In this paper, we successively detail each of these components and conclude with a discussion on a real-world case example and our future research direction.

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