Engineering design teams: Considering the forests and the trees

Although insights uncovered by design cognition are often utilized to develop the methods used by human designers, using such insights to inform computational methodologies also has the potential to improve the performance of design algorithms. This paper uses insights from research on design cognition and design teams to inform a better simulated annealing search algorithm. Simulated annealing has already been established as a model of individual problem solving. This paper introduces the Heterogeneous Simulated Annealing Team (HSAT) algorithm, a multi-agent simulated annealing algorithm. Each agent controls an adaptive annealing schedule, allowing the team develop heterogeneous search strategies. Such diversity is a natural part of engineering design, and boosts performance in other multi-agent algorithms. Further, interaction between agents in HSAT is structured to mimic interaction between members of a design team. Performance is compared to several other simulated annealing algorithms, a random search algorithm, and a gradient-based algorithm. Compared to other algorithms, the team-based HSAT algorithm returns better average results with lower variance.

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Iteration in Engineering Design: Inherent and Unavoidable or Product of Choices Made?

Volume 3a: 8th Design for Manufacturing Conference ◽

10.1115/detc2003/dtm-48662 ◽

2003 ◽

Cited By ~ 8

Author(s):

Ramon Costa ◽

Durward K. Sobek

Keyword(s):

Engineering Design ◽

Design Process ◽

Task Repetition ◽

Design Teams ◽

Simple Task ◽

Heuristic Reasoning ◽

Abstraction Levels

Iteration in design has different meanings, ranging from simple task repetition to heuristic reasoning processes. Determining the need to iterate is important to improve the design process on cost, time, and quality, but currently there is no categorization of iterations conducive to this goal. After exploring the possible causes and attempts to address them, we propose to classify iterations as rework, design, or behavioral. This framework suggests that design teams should try to eliminate rework iterations, perform design iterations without skipping abstraction levels, and do behavioral iterations in parallel.

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Effects of Locus of Control Personality Trait on Team Performance in Cooperative Engineering Design Tasks

Volume 8: 32nd International Conference on Design Theory and Methodology (DTM) ◽

10.1115/detc2020-22641 ◽

2020 ◽

Author(s):

Alkım Z. Avşar ◽

Paul T. Grogan

Keyword(s):

Locus Of Control ◽

Engineering Design ◽

Team Performance ◽

Personality Trait ◽

Performance Outcomes ◽

Design Teams ◽

Support Design ◽

Explanatory Hypothesis ◽

Total Data ◽

Data Points

Abstract Teams in engineering design tackle problems that exceed the abilities of individuals. Improved understanding of how personality traits influence human behaviors and interaction may help create new methods and tools to support design teams. This paper seeks to understand how the Locus of Control (LOC) personality trait influences designer behaviors and team performance. A designer experiment studies 12 participant pairs controlled for categorical LOC pairing factors (internal-internal, external-external, and internal-external). Each design team completes six simplified cooperative parameter design tasks to minimize completion time, yielding 72 total data points. Regression analysis shows LOC pairing affects team efficiency in agreement with literature outside engineering design: diverse LOC traits reduce design efficiency while similarity increases team effectiveness. Results contribute to an explanatory hypothesis that LOC pairing influences designer behaviors related to action effectiveness which, subsequently, affects team performance outcomes.

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Drawing Inspiration From Human Design Teams for Better Search and Optimization: The Heterogeneous Simulated Annealing Teams Algorithm

Journal of Mechanical Design ◽

10.1115/1.4032810 ◽

2016 ◽

Vol 138 (4) ◽

Cited By ~ 9

Author(s):

Christopher McComb ◽

Jonathan Cagan ◽

Kenneth Kotovsky

Keyword(s):

Simulated Annealing ◽

Computational Model ◽

Engineering Design ◽

Search Strategies ◽

Design Teams ◽

Design Cognition ◽

Team Members ◽

Structure Interaction

Insights uncovered by research in design cognition are often utilized to develop methods used by human designers; in this work, such insights are used to inform and improve computational methodologies. This paper introduces the heterogeneous simulated annealing team (HSAT) algorithm, a multiagent simulated annealing (MSA) algorithm. HSAT is based on a validated computational model of human-based engineering design and retains characteristics of the model that structure interaction between team members and allow for heterogeneous search strategies to be employed within a team. The performance of this new algorithm is compared to several other simulated annealing (SA) based algorithms on three carefully selected benchmarking functions. The HSAT algorithm provides terminal solutions that are better on average than other algorithms explored in this work.

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AN EXPERIMENTAL MULTI-AGENT ENVIRONMENT FOR ENGINEERING DESIGN

International Journal of Cooperative Information Systems ◽

10.1142/s0218843096000063 ◽

1996 ◽

Vol 05 (02n03) ◽

pp. 131-151 ◽

Cited By ~ 23

Author(s):

WEIMING SHEN ◽

JEAN-PAUL A. BARTHES

Keyword(s):

Engineering Design ◽

Mechanical Design ◽

Multidisciplinary Design ◽

Design Teams ◽

Efficient Design ◽

Design Environment ◽

Open Design ◽

Long Time ◽

Design Activities ◽

The Individual

Real world engineering design projects require the cooperation of multidisciplinary design teams using sophisticated and powerful engineering tools. The individuals or the individual groups of the multidisciplinary design teams work in parallel and independently often for quite a long time with different tools located on various sites. In order to ensure the coordination of design activities in the different groups or the cooperation among the different tools, it is necessary to develop an efficient design environment. This paper discusses a distributed architecture for integrating such engineering tools in an open design environment, organized as a population of asynchronous cognitive agents. Before introducing the general architecture and the communication protocol, issues about an agent architecture and inter-agent communications are discussed. A prototype of such an environment with seven independent agents located in several workstations and microcomputers is then presented and demonstrated on an example of a small mechanical design.

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Speaker-centredness and participatory listening in pre-expert engineering design teams

CoDesign ◽

10.1080/15710880412331289944 ◽

2005 ◽

Vol 1 (1) ◽

pp. 39-60 ◽

Cited By ~ 6

Author(s):

FRASER J. M. REID ◽

SUSAN E. REED

Keyword(s):

Engineering Design ◽

Design Teams

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