Quantitative Set-Based Design to Inform Design Teams
System designers, analysts, and engineers use various techniques to develop complex systems. A traditional design approach, point-based design (PBD), uses system decomposition and modeling, simulation, optimization, and analysis to find and compare discrete design alternatives. Set-based design (SBD...
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doaj-9db770d03e1d417d8419208770c6662c2021-01-30T00:02:48ZengMDPI AGApplied Sciences2076-34172021-01-01111239123910.3390/app11031239Quantitative Set-Based Design to Inform Design TeamsEric Specking0Nicholas Shallcross1Gregory S. Parnell2Edward Pohl3Department of Industrial Engineering, University of Arkansas, Fayetteville, NC 72701, USADepartment of Industrial Engineering, University of Arkansas, Fayetteville, NC 72701, USADepartment of Industrial Engineering, University of Arkansas, Fayetteville, NC 72701, USADepartment of Industrial Engineering, University of Arkansas, Fayetteville, NC 72701, USASystem designers, analysts, and engineers use various techniques to develop complex systems. A traditional design approach, point-based design (PBD), uses system decomposition and modeling, simulation, optimization, and analysis to find and compare discrete design alternatives. Set-based design (SBD) is a concurrent engineering technique that compares a large number of design alternatives grouped into sets. The existing SBD literature discusses the qualitative team-based characteristics of SBD, but lacks insights into how to quantitatively perform SBD in a team environment. This paper proposes a qualitative SBD conceptual framework for system design, proposes a team-based, quantitative SBD approach for early system design and analysis, and uses an unmanned aerial vehicle case study with an integrated model-based engineering framework to demonstrate the potential benefits of SBD. We found that quantitative SBD tradespace exploration can identify potential designs, assess design feasibility, inform system requirement analysis, and evaluate feasible designs. Additionally, SBD helps designers and analysts assess design decisions by providing an understanding of how each design decision affects the feasible design space. We conclude that SBD provides a more holistic tradespace exploration process since it provides an integrated examination of system requirements and design decisions.https://www.mdpi.com/2076-3417/11/3/1239decision analysistradespace explorationset-based designteam-based methodssystems engineeringmodel-based engineering |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Eric Specking Nicholas Shallcross Gregory S. Parnell Edward Pohl |
spellingShingle |
Eric Specking Nicholas Shallcross Gregory S. Parnell Edward Pohl Quantitative Set-Based Design to Inform Design Teams Applied Sciences decision analysis tradespace exploration set-based design team-based methods systems engineering model-based engineering |
author_facet |
Eric Specking Nicholas Shallcross Gregory S. Parnell Edward Pohl |
author_sort |
Eric Specking |
title |
Quantitative Set-Based Design to Inform Design Teams |
title_short |
Quantitative Set-Based Design to Inform Design Teams |
title_full |
Quantitative Set-Based Design to Inform Design Teams |
title_fullStr |
Quantitative Set-Based Design to Inform Design Teams |
title_full_unstemmed |
Quantitative Set-Based Design to Inform Design Teams |
title_sort |
quantitative set-based design to inform design teams |
publisher |
MDPI AG |
series |
Applied Sciences |
issn |
2076-3417 |
publishDate |
2021-01-01 |
description |
System designers, analysts, and engineers use various techniques to develop complex systems. A traditional design approach, point-based design (PBD), uses system decomposition and modeling, simulation, optimization, and analysis to find and compare discrete design alternatives. Set-based design (SBD) is a concurrent engineering technique that compares a large number of design alternatives grouped into sets. The existing SBD literature discusses the qualitative team-based characteristics of SBD, but lacks insights into how to quantitatively perform SBD in a team environment. This paper proposes a qualitative SBD conceptual framework for system design, proposes a team-based, quantitative SBD approach for early system design and analysis, and uses an unmanned aerial vehicle case study with an integrated model-based engineering framework to demonstrate the potential benefits of SBD. We found that quantitative SBD tradespace exploration can identify potential designs, assess design feasibility, inform system requirement analysis, and evaluate feasible designs. Additionally, SBD helps designers and analysts assess design decisions by providing an understanding of how each design decision affects the feasible design space. We conclude that SBD provides a more holistic tradespace exploration process since it provides an integrated examination of system requirements and design decisions. |
topic |
decision analysis tradespace exploration set-based design team-based methods systems engineering model-based engineering |
url |
https://www.mdpi.com/2076-3417/11/3/1239 |
work_keys_str_mv |
AT ericspecking quantitativesetbaseddesigntoinformdesignteams AT nicholasshallcross quantitativesetbaseddesigntoinformdesignteams AT gregorysparnell quantitativesetbaseddesigntoinformdesignteams AT edwardpohl quantitativesetbaseddesigntoinformdesignteams |
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