EAGER: Theoretical Foundation for the Use of Approximations and Heuristics in Systems Engineering and Design

EAGER：在系统工程和设计中使用近似和启发式的理论基础

• 批准号: 1645316
• 负责人: Katherine Fu
• 金额: $ 29.95万
• 依托单位: Georgia Tech Research Corporation
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-08-01 至 2020-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1645316&HistoricalAwards=false
• 关键词: EAGER; Theoretical; Foundation; Use; Approximations

In practice, engineers often rely on heuristics and approximations to arrive at good system designs efficiently and effectively. Heuristics are rules of thumb that embody engineering experience. When used appropriately, they save engineering time and effort without sacrificing the quality of the system being engineered. However, the use of heuristics and approximations is poorly understood. This EArly-concept Grant for Exploratory Research (EAGER) project will enable a fundamental understanding and development of design heuristics and associated processes, guiding researchers and practitioners in advancements and use of such heuristics, and ultimately, providing a formalized foundation to design science. The research will combine mathematical foundations, such as probability theory and decision theory, with empirical observations of students and experienced engineers to develop explanatory models for the use of heuristics and approximations. The research will make strides in formalizing design heuristics from various disparate approaches, and recommend how and when heuristics are best used in design practice. In addition, it will lead to new insights regarding how to teach design better by clearly identifying the heuristic nature of design knowledge, and by coaching students to continually update their heuristics through the contextualization of the underlying foundations and through life-long learning.Systems engineering and design currently lack a strong theoretical foundation, and, in particular, the community has struggled to bridge the gap between current practice and the normative, axiomatic, mathematical theories that underlie systems engineering and design. To fill this gap in knowledge, the objective of this research is to enhance the scientific understanding of the use of approximations and heuristics in systems engineering and design. A normative theory will be derived for the use of approximations and heuristics by explicitly accounting for the value of the resources required to execute designer actions, starting from the von Neumann-Morgenstern axioms of decision theory. Heuristics found will be cataloged and analyzed by characterizing their value or 'validity.' The relationship between design heuristics and cognitive heuristics as studied in psychology will be considered, bridging the gap between descriptive and prescriptive theories, identifying gaps between the two, and deriving hypotheses regarding the improvement of design practice in situations in which the gap between normative theory and current practice appears to be large. This research will assist in enabling a fundamental understanding and development of design heuristics and associated processes, and will guide researchers and practitioners in advancements and use of such heuristics, and ultimately, provide formalized foundations to design science.

在实践中，工程师经常依靠启发式和近似来高效地达到良好的系统设计。启发式是体现工程经验的经验法则。如果使用得当，它们可以节省工程时间和精力，而不会牺牲所设计系统的质量。然而，人们对启发式和近似法的使用却知之甚少。这个探索性研究（EAGER）项目的早期概念资助将使设计启发式和相关过程的基本理解和发展成为可能，指导研究人员和实践者推进和使用这种启发式，并最终为设计科学提供形式化的基础。该研究将结合数学基础，如概率论和决策理论，与学生和经验丰富的工程师的经验观察，以开发启发式和近似方法的解释模型。该研究将在形式化各种不同方法的设计启发式方面取得进展，并建议如何以及何时最好地在设计实践中使用启发式。此外，通过清晰地识别设计知识的启发式本质，并通过指导学生通过潜在基础的情境化和终身学习不断更新他们的启发式，它将导致关于如何更好地教授设计的新见解。系统工程和设计目前缺乏强大的理论基础，特别是，社区一直在努力弥合当前实践与规范，公理，数学理论之间的差距，这些理论是系统工程和设计的基础。为了填补这一知识空白，本研究的目的是提高对系统工程和设计中近似和启发式使用的科学理解。从决策理论的冯·诺伊曼-摩根斯特恩公理开始，通过明确计算执行设计师行动所需资源的价值，将推导出使用近似和启发式的规范理论。发现的启发式将通过描述其价值或“有效性”进行编目和分析。将考虑心理学中研究的设计启发式和认知启发式之间的关系，弥合描述性理论和规定性理论之间的差距，确定两者之间的差距，并在规范理论和当前实践之间的差距似乎很大的情况下推导关于改进设计实践的假设。这项研究将有助于对设计启发式和相关过程的基本理解和发展，并将指导研究人员和实践者推进和使用这种启发式，并最终为设计科学提供形式化的基础。

项目成果

Examining the effect of design for additive manufacturing rule presentation on part redesign quality

• DOI: 10.1080/09544828.2020.1789569
• 发表时间: 2020-07-10
• 期刊: JOURNAL OF ENGINEERING DESIGN
• 影响因子: 2.7
• 作者: Fillingim, Kenton Blane;Nwaeri, Richard O.;Fu, Katherine
• 通讯作者: Fu, Katherine

Process Heuristics: Extraction, Analysis, and Repository Considerations

流程启发式：提取、分析和存储库注意事项

• DOI: 10.1109/jsyst.2019.2959538
• 发表时间: 2020
• 期刊: IEEE Systems Journal
• 影响因子: 4.4
• 作者: Fillingim, Kenton B.;Shapiro, Hannah;Paredis, Christiaan J.;Fu, Katherine
• 通讯作者: Fu, Katherine

Design Heuristics: A Conceptual Framework and Preliminary Method for Extraction

设计启发式：提取的概念框架和初步方法

• 发表时间: 2017
• 期刊: Proceedings of the ASME International Design Engineering Technical Conferences & Computers and Information in Engineering Conference
• 作者: Lee, Bumsoo;Fillingim, Kenton B.;Binder, William R.;Fu, Katherine;Paredis, Christiaan J.J.
• 通讯作者: Paredis, Christiaan J.J.

Optimization Under Uncertainty Versus Algebraic Heuristics: A Research Method for Comparing Computational Design Methods

不确定性下的优化与代数启发式：比较计算设计方法的研究方法

• 发表时间: 2017
• 期刊: Proceedings of the ASME 2017 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference
• 作者: Binder, William R.;Paredis, Christiaan J.J.
• 通讯作者: Paredis, Christiaan J.J.

Design Heuristics: Extraction and Classification Methods with Jet Propulsion Laboratory’s Architecture Team

设计启发式：喷气推进实验室架构团队的提取和分类方法

• DOI: 10.1115/1.4044160
• 发表时间: 2020
• 期刊: Journal of Mechanical Design
• 影响因子: 3.3
• 作者: Fillingim, Kenton B.;Nwaeri, Richard O.;Borja, Felipe;Fu, Katherine;Paredis, Christiaan J.
• 通讯作者: Paredis, Christiaan J.