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

2016 ◽  
Vol 138 (4) ◽  
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.

scholarly journals Drawing Inspiration From Human Design Teams For Better Search And Optimization: The Heterogeneous Simulated Annealing Teams Algorithm

2018 ◽  
Author(s):  
Christopher McComb ◽  
Jonathan Cagan ◽  
Kenneth Kotovsky
Keyword(s):  
Simulated Annealing ◽  
Computational Model ◽  
Engineering Design ◽  
Simulated Annealing Algorithm ◽  
Search Strategies ◽  
Design Teams ◽  
Team Members ◽  
Structure Interaction ◽  
Multi Agent ◽  
Annealing Algorithm

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 multi-agent simulated annealing 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 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.

scholarly journals Heterogeneous Simulated Annealing Teams: An Optimizing Search Algorithm Inspired by Engineering Design Teams

2018 ◽  
Author(s):  
Christopher McComb ◽  
Jonathan Cagan ◽  
Kenneth Kotovsky
Keyword(s):  
Simulated Annealing ◽  
Engineering Design ◽  
Simulated Annealing Algorithm ◽  
Search Algorithm ◽  
Random Search ◽  
Design Teams ◽  
Design Cognition ◽  
Gradient Based ◽  
Multi Agent ◽  
Annealing Algorithms

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.

Application of a Protocol to Observe Leadership Behaviors in Engineering Design Teams

2019 ◽  
Author(s):  
James Righter ◽  
Chase Wentzky ◽  
Joshua D. Summers
Keyword(s):  
Engineering Design ◽  
Leadership Behaviors ◽  
Informal Leadership ◽  
Design Teams ◽  
Function Model ◽  
Team Members ◽  
Undergraduate Engineering ◽  
Protocol Study ◽  
Relational Behaviors ◽  
Functional Leadership

Abstract This protocol study was conducted to increase understanding of the emergence and distribution of functional leadership behaviors in undergraduate engineering design teams. This study applies the protocol presented at the 2018 IDETC to observe design teams consisting of novice engineers constructing a function model during a video recorded session. The videos were then coded for leadership functions and analyzed to determine the distribution of informal leadership functions between the team members and the temporal emergence of the informal leadership structures within the teams. Leadership behaviors were observed to be predominantly transition and action functions with relational behaviors occurring less frequently. The behaviors were quantified by number of occurrences per quintile. The leaders observed to perform the most leadership behaviors early in the sessions often remained consistent. However, leadership functions were shared between team members as demonstrated by the leadership network graphs.

scholarly journals BEHAVIOURAL DIFFERENCES OF HIGH AND LOW PERFORMING TEAMS: A MULTI-INSTITUTIONAL STUDY OF FIRST-YEAR ENGINEERING DESIGN TEAMS

2018 ◽  
Author(s):  
Patricia K. Sheridan ◽  
Adam Goodman ◽  
Todd Murphy ◽  
Doug Reeve ◽  
Greg Evans
Keyword(s):  
Engineering Design ◽  
First Year ◽  
Design Teams ◽  
Team Members ◽  
High Performing

 Abstract – This paper compares student intra-team feedback to identify behaviours that differentiate high and low performing teams. Data from two universities’ first-year engineering design courses was analysed and demonstrated that the ways in which students discussed high and low performing teams was similar. This paper discusses some of the issues with which low performing teams struggled. Both high and low performing teams experienced a lack of quality and quantity of communication, whereas low-performing teams struggled with hoarding work, leveraging team members and supporting others. High-performing teams may have a more collective team mindset that values the skills and perspectives of all team members more.

Design Team Convergence: The Influence of Example Solution Quality

2009 ◽  
Author(s):  
Katherine Fu ◽  
Jonathan Cagan ◽  
Kenneth Kotovsky
Keyword(s):  
Problem Solving ◽  
Engineering Design ◽  
Semantic Analysis ◽  
Cognitive Engineering ◽  
Design Team ◽  
Design Teams ◽  
Solution Quality ◽  
Team Members ◽  
Common Understanding

This study examines how engineering design teams converge to a common understanding of a design problem and its solution, how that is influenced by the information given to them before problem solving and how it is correlated with quality of produced solutions. To understand convergence, a model of the team members’ representations was sought through a cognitive engineering design study, specifically examining the effect of the introduction of a poor example solution and a good example solution prior to problem solving. Latent Semantic Analysis (LSA) was used to track the teams’ convergence. Introducing a poor example solution was shown to have a slowing effect on teams’ convergence over time and quality of design, while the good example solution was not significantly different than the control (no example solution) in its effects on convergence, but did cause higher quality solutions. This may have implications for design team performance in practice.

Effective Design Team Composition Using Individual and Group Cognitive Attributes

2018 ◽  
Author(s):  
Kaitlyn Fritz ◽  
Line Deschenes ◽  
Vijitashwa Pandey
Keyword(s):  
Engineering Design ◽  
Brain Activity ◽  
Design Solution ◽  
Design Team ◽  
Design Teams ◽  
Team Members ◽  
Power Spectral ◽  
Team Interactions ◽  
Significant Area ◽  
Self Assessments

Engineering design is typically a team effort. Design teams frequently need to push technical boundaries to solve the most relevant challenges faced by our society. A significant area of research across multiple fields of investigation, including engineering, is the understanding and use of an individual’s cognitive attributes in the process of assembling productive teams. This research proposes an approach to assembling an engineering design team by first defining the desirable cognitive attributes in the team members. Subsequently, based on individual cognitive profile assessments along these attributes, an exhaustive list of possible design teams is investigated based on their cumulative attribute level. We compare the performance of two teams predicted to perform at different levels, and our results verify the differences between the observations of team interactions and the quality of designs produced. In addition to self-assessments, we also investigate the brain activity of the respondents using electroencephalography (EEG) to evaluate performance in an individual and a team setting. This analysis intends to highlight the characteristics of an individuals’ brain activity under different circumstances to reveal if these characteristics contribute to the success of a design team. EEG data revealed observations such as correlation between raw amplitude and level of team contribution, a higher variation in the channel power spectral density during individual versus team tasks, and a degradation of alpha activity moving from individual to group work. The results of this research can guide organizations to form teams with the necessary cognitive attributes to achieve the optimum design solution.

A Document Analysis Method for Characterizing Design Team Performance

2003 ◽  
Vol 126 (3) ◽  
pp. 378-385 ◽  
Author(s):  
Andy Dong ◽  
Andrew W. Hill ◽  
Alice M. Agogino
Keyword(s):  
Engineering Design ◽  
Semantic Analysis ◽  
Design Teams ◽  
Team Members ◽  
Design Performance ◽  
Design Concepts ◽  
Semantic Coherence ◽  
Design Documentation ◽  
Design Documents ◽  
The Impact

The premise of this research is that the engineering design process is partially driven by achieving consensus and reconciling points of view among team members. Characterizing the quality of the design performance by measuring the coherence of the description of related design concepts and events in design documentation is examined. Latent Semantic Analysis (LSA) was used to analyze design documentation written by self-managing, cross-functional engineering design teams. Computational measurements of document variance and textual coherence were applied to the teams’ design documents, presentation materials and e-mail communication. The levels of semantic coherence were correlated to assessments by faculty and product designers and engineers from industry of the design teams’ process and outcome quality. The results indicated a statistically significant positive correlation between design document coherence and design performance, especially for poorly performing teams. The impact of this research is to provide team managers (people who create teams and manage teams) or self-organizing teams (teams that focus on self-reflection and peer evaluation) computational tools that could be integrated with design information management technologies to assist them in the management of engineering design teams.

Power and Communication: Solving Power Problems for Collaboration in Globally Distributed Engineering Design Teams

2005 ◽  
Author(s):  
Kenneth David ◽  
John R. Lloyd ◽  
Timothy J. Hinds
Keyword(s):  
Engineering Design ◽  
Global Market ◽  
Educational Systems ◽  
Design Teams ◽  
Collaborative Activity ◽  
Collaborative Project ◽  
Team Members ◽  
Global Engineering ◽  
Globally Distributed ◽  
India And China

Because outsourcing and offshoring operations entail multi-site operations and inter-organizational alliances, they require effective boundary-spanning partnerships: inter-divisional, inter-organizational, and often, multi-country partnerships. This paper reports a multi-discipline research study—involving engineering, anthropology and telecommunications elements—on dispersed global engineering design teams. A framework involving power, culture, and collaborative activity is introduced. The focus here is on power and communications issues. Co-oriented, collaborative project activity is achieved when power issues are neutralized. When sub-team members perceive inequity, they frequently respond adversely. They may purposely create miscommunications among sub-teams, covertly subvert project goals, or otherwise act in ways that reduce project performance. Outsourcing of engineering design operations is a major challenge for the engineering profession. Outsourcing activity to India and China has increased; educational systems in these countries both improve in quality and augment the quantity of engineers produced. Traditional engineering skills are swiftly becoming a commodity in the global market.

scholarly journals EXPLORING THE ROLE OF TRANSACTIVE MEMORY SYSTEMS IN TEAM DECISION-MAKING DURING IDEATION PHASE

2021 ◽  
Vol 1 ◽  
pp. 1529-1536
Author(s):  
Mohammad Reza Dastmalchi ◽  
Bimal Balakrishnan ◽  
Danielle Oprean
Keyword(s):  
Digital Media ◽  
Memory Systems ◽  
Transactive Memory ◽  
Design Teams ◽  
Team Cognition ◽  
Team Members ◽  
Media Type ◽  
Design Collaboration ◽  
Wide Range ◽  
Communication Modes

AbstractTeam collaboration is a critical necessity of the modern-day engineering design profession. This is no surprise given that teams typically possess more task-relevant skills and knowledge than individuals (Levine & Choi, 2004). Advancements in digital media provide new opportunities for collaboration across the design lifecycle. However, early stages of the design process still pose challenges to digitally mediated design collaboration due to greater representational abstraction and the presence of multiple modalities for design ideation. Usually, design teams spend a substantial amount of time generating a broad set of ideas that can lead them to a wide range of design solutions during the ideation phase. However, sooner or later, teams should narrow down their vision for a final solution. What factors influence team members to eliminate or select an idea? Our study is an attempt to demonstrate some examples of this challenge. By drawing on research in team cognition, particularly the concept of transactive memory system (TMS) we studied a design teams' communication and media use during the ideation phase. The goal was to see if media type and communication modes can predict a team's decisions on selecting and eliminating ideas.

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