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Assessing the Risk of Space Reduction Decisions in Set-Based Design Through Fragility-Tracking of Interdependent Design Spaces
Assessing the Risk of Space Reduction Decisions in Set-Based Design Through Fragility-Trac...
Assessing the Risk of Space Reduction Decisions in Set-Based Design Through Fragility-Tracking of Interdependent Design Spaces

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자료유형  
 학위논문 서양
최종처리일시  
20260202103642
ISBN  
9798314873892
DDC  
741
저자명  
Van Houten, Joseph B.
서명/저자  
Assessing the Risk of Space Reduction Decisions in Set-Based Design Through Fragility-Tracking of Interdependent Design Spaces
발행사항  
[Sl] : University of Michigan, 2025
발행사항  
Ann Arbor : ProQuest Dissertations & Theses, 2025
형태사항  
189 p
주기사항  
Source: Dissertations Abstracts International, Volume: 86-11, Section: B.
주기사항  
Advisor: Collette, Matthew.
학위논문주기  
Thesis (Ph.D.)--University of Michigan, 2025.
초록/해제  
요약As designers execute analyses and explore potential design solutions, their understanding of a design problem grows. They begin to learn the trade-offs of pursuing certain design solutions over others, and they form preferences that are grounded in how they perceive design solutions to satisfy each discipline's requirements. Once designers start making decisions from these perceptions, they begin to limit the knowledge generation associated with their decisions. If they are not careful, their decisions will prevent new knowledge from integrating with existing knowledge, and they will incur emergent design failures. Emergent design failures incited by iterative decisions are less consequential to designers because rework cycles are naturally apart of their learning process. Emergent design failures incited by convergent decisions, on the other hand, are more consequential to designers because they expend substantial time and effort exploring design spaces before making any decisions in the first place. Without the ability to anticipate whether elimination decisions will incite emergent design failures, convergent design approaches become far less appealing. The benefits of adopting a convergent approach over an iterative one are well-documented, especially as design problems become increasingly complex, but why undertake the added effort if these decisions can be so much more detrimental to attaining a feasible outcome? To encourage designers to carry out a convergent design approach, they need a way to assess how vulnerable the perceptions of feasibility in their design spaces are to being invalidated by new information before committing to a space reduction decision. The Probabilistic Fragility Model (PFM) and Entropic Fragility Model (EFM) introduced in this work are intended to do just that. Both fragility models assess the fragility of a reduced design space relative to its non-reduced design space and quantify the risk of incurring emergent design failures when going through with a space reduction compared to delaying the space reduction. The utility of the frameworks are evaluated by executing a series of convergent, set-based design (SBD) simulations for a polynomial design problem and a bulk carrier design problem with and without them and observing the emergent design spaces. The PFM's process is a bit more straightforward and is able to reasonably delay space reductions for the polynomial design problem more than the bulk carrier design problem without significantly driving up the added cost of retaining more solutions. The EFM is able to reasonably delay space reductions for both problems without significantly driving up the added cost, but at the expense of being a more involved process than the PFM. After testing both frameworks out on the polynomial design problem, their initial versions still lacked the capability to identify design space fragilities from some more niche sources of new information. So before testing out the frameworks on the bulk carrier design problem, three extensions are proposed and incorporated to expand their reliability. The findings of this work show that making fragility checks with the frameworks is a very worthwhile precaution for designers to take to help them avoid space reduction decisions that incite emergent design failures.
일반주제명  
Design
일반주제명  
Engineering
일반주제명  
Naval engineering
일반주제명  
Ocean engineering
키워드  
Set-based design
키워드  
Space reductions
키워드  
Information
키워드  
Fragility
키워드  
Probability
키워드  
Entropy
기타저자  
University of Michigan Naval Architecture & Marine Engineering
기본자료저록  
Dissertations Abstracts International. 86-11B.
전자적 위치 및 접속  
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MARC

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■1001  ▼aVan  Houten,  Joseph  B.
■24510▼aAssessing  the  Risk  of  Space  Reduction  Decisions  in  Set-Based  Design  Through  Fragility-Tracking  of  Interdependent  Design  Spaces
■260    ▼a[Sl]▼bUniversity  of  Michigan▼c2025
■260  1▼aAnn  Arbor▼bProQuest  Dissertations  &  Theses▼c2025
■300    ▼a189  p
■500    ▼aSource:  Dissertations  Abstracts  International,  Volume:  86-11,  Section:  B.
■500    ▼aAdvisor:  Collette,  Matthew.
■5021  ▼aThesis  (Ph.D.)--University  of  Michigan,  2025.
■520    ▼aAs  designers  execute  analyses  and  explore  potential  design  solutions,  their  understanding  of  a  design  problem  grows.    They  begin  to  learn  the  trade-offs  of  pursuing  certain  design  solutions  over  others,  and  they  form  preferences  that  are  grounded  in  how  they  perceive  design  solutions  to  satisfy  each  discipline's  requirements.    Once  designers  start  making  decisions  from  these  perceptions,  they  begin  to  limit  the  knowledge  generation  associated  with  their  decisions.    If  they  are  not  careful,  their  decisions  will  prevent  new  knowledge  from  integrating  with  existing  knowledge,  and  they  will  incur  emergent  design  failures.    Emergent  design  failures  incited  by  iterative  decisions  are  less  consequential  to  designers  because  rework  cycles  are  naturally  apart  of  their  learning  process.    Emergent  design  failures  incited  by  convergent  decisions,  on  the  other  hand,  are  more  consequential  to  designers  because  they  expend  substantial  time  and  effort  exploring  design  spaces  before  making  any  decisions  in  the  first  place.  Without  the  ability  to  anticipate  whether  elimination  decisions  will  incite  emergent  design  failures,  convergent  design  approaches  become  far  less  appealing.    The  benefits  of  adopting  a  convergent  approach  over  an  iterative  one  are  well-documented,  especially  as  design  problems  become  increasingly  complex,  but  why  undertake  the  added  effort  if  these  decisions  can  be  so  much  more  detrimental  to  attaining  a  feasible  outcome?    To  encourage  designers  to  carry  out  a  convergent  design  approach,  they  need  a  way  to  assess  how  vulnerable  the  perceptions  of  feasibility  in  their  design  spaces  are  to  being  invalidated  by  new  information  before  committing  to  a  space  reduction  decision.    The  Probabilistic  Fragility  Model  (PFM)  and  Entropic  Fragility  Model  (EFM)  introduced  in  this  work  are  intended  to  do  just  that.    Both  fragility  models  assess  the  fragility  of  a  reduced  design  space  relative  to  its  non-reduced  design  space  and  quantify  the  risk  of  incurring  emergent  design  failures  when  going  through  with  a  space  reduction  compared  to  delaying  the  space  reduction.  The  utility  of  the  frameworks  are  evaluated  by  executing  a  series  of  convergent,  set-based  design  (SBD)  simulations  for  a  polynomial  design  problem  and  a  bulk  carrier  design  problem  with  and  without  them  and  observing  the  emergent  design  spaces.    The  PFM's  process  is  a  bit  more  straightforward  and  is  able  to  reasonably  delay  space  reductions  for  the  polynomial  design  problem  more  than  the  bulk  carrier  design  problem  without  significantly  driving  up  the  added  cost  of  retaining  more  solutions.    The  EFM  is  able  to  reasonably  delay  space  reductions  for  both  problems  without  significantly  driving  up  the  added  cost,  but  at  the  expense  of  being  a  more  involved  process  than  the  PFM.    After  testing  both  frameworks  out  on  the  polynomial  design  problem,  their  initial  versions  still  lacked  the  capability  to  identify  design  space  fragilities  from  some  more  niche  sources  of  new  information.    So  before  testing  out  the  frameworks  on  the  bulk  carrier  design  problem,  three  extensions  are  proposed  and  incorporated  to  expand  their  reliability.    The  findings  of  this  work  show  that  making  fragility  checks  with  the  frameworks  is  a  very  worthwhile  precaution  for  designers  to  take  to  help  them  avoid  space  reduction  decisions  that  incite  emergent  design  failures.
■590    ▼aSchool  code:  0127.
■650  4▼aDesign
■650  4▼aEngineering
■650  4▼aNaval  engineering
■650  4▼aOcean  engineering
■653    ▼aSet-based  design
■653    ▼aSpace  reductions
■653    ▼aInformation
■653    ▼aFragility
■653    ▼aProbability
■653    ▼aEntropy
■690    ▼a0537
■690    ▼a0468
■690    ▼a0389
■690    ▼a0547
■71020▼aUniversity  of  Michigan▼bNaval  Architecture  &  Marine  Engineering.
■7730  ▼tDissertations  Abstracts  International▼g86-11B.
■790    ▼a0127
■791    ▼aPh.D.
■792    ▼a2025
■793    ▼aEnglish
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T17358085▼nKERIS▼z이  자료의  원문은  한국교육학술정보원에서  제공합니다.

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