Collaborative SGER: Computational Support for Semantically Rich Design Problems - Addressing High Risk Elements

协作 SGER：对语义丰富的设计问题的计算支持 - 解决高风险元素

• 批准号: 0636407
• 负责人: Joshua Summers
• 金额: $ 5万
• 依托单位: Clemson University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-09-01 至 2007-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0636407&HistoricalAwards=false
• 关键词: Collaborative; SGER; Computational; Support; Semantically

The objective of this SGER proposal is to explore a conceptual basis and empirical justification for representing engineering semantic information in a computational framework. This is high risk, yet high reward, in that modeling semantic information has been elusive whereas facilitating reasoning on both geometric and semantic information would radically change how engineers design. This research consists of three tasks: conducting case studies on industry use of semantic information, survey of existing approaches to representing this information, and analysis of computational support for these representations. Three case studies, including a small manufacturing firm, a large automotive OEM, and senior capstone design projects, will be conducted to determine how and when engineers use, manipulate, and document the semantic information. The case studies will be conducted using standard historical and active protocol analysis techniques and will serve as the guide for surveying and evaluating appropriate semantic modeling techniques.If successful this understanding of the role of semantic information in engineering design will provide justification for developing theory of affordances, borrowed from perceptual psychology, into a computational environment as supported by exemplar technology. Furthermore, if a suitable structure for capturing semantic information were available and it could be mapped to a computational representation this would greatly impact mechanical engineering design. As CAD tools have revolutionized design, semantically rich tools have the potential to radically impact practice, providing an environment where multiple facets of a project can be considered, resulting in reduced time-to-market, fewer design iterations, fewer costly mistakes, and improved quality.

这个SGER建议的目的是探索一个概念基础和经验的理由表示工程语义信息的计算框架。 这是高风险，但高回报，因为建模语义信息一直难以捉摸，而促进几何和语义信息的推理将从根本上改变工程师的设计方式。 本研究包括三个任务：进行案例研究的行业使用的语义信息，调查现有的方法来表示这些信息，并分析这些表示的计算支持。 将进行三个案例研究，包括一个小型制造公司，一个大型汽车OEM和高级顶点设计项目，以确定工程师如何以及何时使用，操作和记录语义信息。 案例研究将进行使用标准的历史和积极的协议分析技术，并将作为指导调查和评估适当的语义建模technology.If成功的语义信息在工程设计中的作用的理解将提供合理的发展理论的启示，从感性心理学，到计算环境中的支持范例技术。 此外，如果一个合适的结构捕捉语义信息是可用的，它可以被映射到一个计算表示，这将极大地影响机械工程设计。 随着CAD工具彻底改变了设计，语义丰富的工具有可能从根本上影响实践，提供一个可以考虑项目多个方面的环境，从而缩短上市时间，减少设计迭代，减少代价高昂的错误，并提高质量。