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SBIR Phase II: Ecosystem for Learning and Team Design

SBIR 第二阶段：学习和团队设计生态系统

基本信息

批准号：
1632408
负责人：
Baldur Steingrimsson
金额：
$ 75万
依托单位：
Imagars LLC
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：
2016-09-01 至 2020-03-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1632408&HistoricalAwards=false
关键词：
SBIR Phase II Ecosystem Learning

项目摘要

This Phase II project impacts the way engineering design is taught in design courses and contributes to the training of a strong workforce in areas related to science, technology and engineering. The Ecosystem is a software tool that automatically verifies designs against the requirements, to uncover oversights early in the process, but also fosters engineering judgement and creativity, allows for assessment of designs with less subjectivity, and facilitates smooth communication among team members. This results in productivity enhancements, higher quality designs and shorter time-to-market, but also in societal benefits (safer products, less risk of catastrophic accidents and more competitive design organizations). The target market consists of (1) educational institutions teaching engineering design, and (2) design companies striving to ensure compliance with the design specifications. The core innovation is three-fold. First, it consists of an e-design assessment engine that is being developed to a high degree of sophistication. Second, design repositories are investigated and developed for integration. Third, holistic (big data) analysis of design content and metadata is implemented. The project seeks to develop an innovative design decision (learning) support system addressing problems related to the high cost of design oversights. Such oversights can result in catastrophic failures, product recalls, or simply in budget or schedule over-runs (due to rework). The Ecosystem offers a flexible, yet systematic and generic, framework, for guiding designers through the design process, and for automatically assessing design activities, from each stage in the design process, against the product design specification (PDS). At the center of the Ecosystem is the e-design assessment engine, which decomposes the PDS, correlates the design activities against individual requirements, and provides real-time advisories in case of design oversights. The assessment engine automatically configures popular development tools for engineering design, determines relevant analyses, and interprets the outputs. The Ecosystem interfaces with these development tools, but does not replace. The Ecosystem can translate qualitative customer requirements into solid engineering requirements, and verify the relevance of the design content provided through seamless interfaces with industry databases. The Ecosystem improves designers' productivity through automation of many administrative tasks (e.g., generation of project reports). Despite the automation, the learning experience is not diminished. The Ecosystem prompts for, captures, and preserves the rationale for relevant engineering decisions. It also supports accredited, generic learning objectives for engineering design.

这个第二阶段的项目影响了在设计课程中教授工程设计的方式，并有助于在与科学、技术和工程相关的领域培训一支强大的劳动力队伍。生态系统是一种软件工具，可以根据需求自动验证设计，以便在过程的早期发现疏忽，但也可以培养工程判断力和创造力，允许以较少的主观性评估设计，并促进团队成员之间的顺畅沟通。这不仅提高了生产率，提高了设计质量，缩短了上市时间，而且还带来了社会效益(更安全的产品、更低的灾难性事故风险和更具竞争力的设计组织)。目标市场包括(1)教授工程设计的教育机构，以及(2)努力确保符合设计规范的设计公司。核心创新有三个方面。首先，它由一个正在开发的高度复杂的电子设计评估引擎组成。其次，为集成而研究和开发设计存储库。第三，对设计内容和元数据进行整体(大数据)分析。该项目旨在开发一个创新的设计决策(学习)支持系统，以解决与设计疏忽的高成本有关的问题。这样的疏忽可能导致灾难性的故障、产品召回，或者仅仅是预算或进度超支(由于返工)。该生态系统提供了一个灵活、但系统和通用的框架，用于指导设计人员完成设计过程，并根据产品设计规范(PDS)从设计过程的每个阶段自动评估设计活动。生态系统的中心是电子设计评估引擎，它分解PDS，将设计活动与个人需求相关联，并在出现设计疏忽时提供实时建议。评估引擎自动配置用于工程设计的流行开发工具，确定相关分析，并解释输出。生态系统与这些开发工具对接，但不会被取代。该生态系统可以将定性的客户需求转化为坚实的工程需求，并通过与行业数据库的无缝接口来验证提供的设计内容的相关性。该生态系统通过自动执行许多管理任务(例如，生成项目报告)来提高设计人员的工作效率。尽管有自动化，但学习体验并没有减少。生态系统会提示、捕捉并保留相关工程决策的基本原理。它还支持工程设计的认可的、通用的学习目标。

项目成果

期刊论文数量（6）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Evaluation of Ecosystem for Design Assessment and Verification by the Formula and BAJA SAE Teams at Oregon Institute of Technology

俄勒冈理工学院 Formula 和 BAJA SAE 团队对设计评估和验证生态系统的评估

DOI：
发表时间：
2020
期刊：
Society of Automotive Engineers technical paper series
影响因子：
0
作者：
Collins, Ronald L;Stover Clifford, M;Moravec, Brian;Steingrimsson, Baldur
通讯作者：
Steingrimsson, Baldur

Big Data Analytics for Improving Fidelity of Engineering Design Decisions

大数据分析提高工程设计决策的保真度

DOI：
发表时间：
2018
期刊：
Society of Automotive Engineers technical paper series
影响因子：
0
作者：
Steingrimsson, Baldur;Yi, Sung;Jones, Robert;Kisialiou, Mikalai;Yi, Kwan;Rose, Zachary
通讯作者：
Rose, Zachary

Ecosystem for Engineering Design Learning: A Comparative Analysis

工程设计学习生态系统：比较分析