EAGER: A Decision Analytic Framework for Large-Scale Design and Manufacturing
EAGER: A Decision Analytic Framework for Large-Scale Design and Manufacturing
批准号:
1258482
负责人:
Ali Abbas
金额:
$29.89万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2012
资助国家:
美国
项目状态:
已结题
起止时间:
2012-09-15 至 2015-10-31
中文摘要
探索性研究早期概念资助(EAGER)奖的研究目标是为设计和制造组织导出规范性决策的多学科理论。该理论将为两类企业的规范性决策提供新的公理:利润最大化企业(如约翰迪尔)和联邦/政府设计企业(如美国宇航局兰利研究中心)。该理论将把公理转化为一致决策的数学公式,最终目的是改善美国的设计和制造决策。对于一个利润最大化的公司,一个基本公理将被研究:如果同一组织内的另一个部门在相同的信息和资源下拒绝接受一个项目,那么组织内没有一个部门会接受这个项目。这个公理将转化为公司效用功能的必要性:同一组织内的部门在做出设计决策时将以相同的风险态度进行操作。该研究将说明如何评估企业效用函数,并将探讨设计公司内部共同激励结构导致的决策行为。这项工作还将得出独特的激励结构,使激励行为与预期效用最大化行为保持一致。行为实验将验证激励结构是否可行,是否符合期望效用框架。结果的验证也将通过行业合作者来实现。一个新的贝叶斯框架的需求估计也将探讨,并将用于最大化预期效用的利润。这项研究将包括NASA Langley、John Deere和工程设计界的重要教育组成部分。如果成功,该研究将通过引入设计过程中规范决策的几个新的理论基础来推进工程设计的理论和实践。该理论将(i)使设计要求与公司的价值函数保持一致,(ii)使激励结构与预期效用最大化行为保持一致,(iii)提供设计公司内部一致决策所需的公理。该合同中的高风险因素包括与行业合作伙伴和NASA验证新方法,以及确定将决策框架纳入当前设计组织的过渡机制。改善设计企业内部的决策是美国经济的基石。通过适当地识别一致决策制定所需的过程,个人、设计工程师和各种商业企业将生产出更好的产品。除了理论和实验工作外,该奖项还将使PI能够与NASA Langley、John Deere以及设计和制造社区的其他成员合作举办两个研讨会:第一个研讨会将是“为工程设计设定基于价值的需求”,第二个研讨会将是“将激励结构与预期效用最大化相结合”。这项研究将广泛传播,该奖项将使PI能够继续与尚佩恩县少年拘留中心(JDC)联合合作,向问题青少年传播决策技能。
英文摘要
The research objective of this EArly Concept Grant for Exploratory Research (EAGER) award is to derive a multidisciplinary theory of normative decision making for design and manufacturing organizations. The theory will provide new axioms for normative decision making for two types of enterprises: profit maximizing firms (such as John Deere) and federal/governmental design enterprises (such as NASA Langley Research Center). The theory will translate the axioms into mathematical formulations for consistent decision making for the ultimate purpose of improving the design and manufacturing decisions within the United States. For a profit maximizing firm, a fundamental axiom will be investigated: that there be no division within an organization that will accept a project if another division within the same organization, and with the same information and resources, would reject. This axiom will translate into the necessity of a corporate utility function: divisions within the same organization will operate with the same risk attitude when making design decisions. The research will illustrate how to assess a corporate utility function and will explore the decision making behavior that results from common incentive structures within design firms. The work will also derive unique incentive structures that align incentivized behavior with expected utility maximizing behavior. Behavioral experiments will be conducted to verify whether the incentive structures are feasible and match the desired expected utility framework. Verification of the results will also be achieved through industry collaborators. A new Bayesian framework for demand estimation will also be explored and will be used in maximizing the expected utility of profit. The research will include a significant educational component with NASA Langley, John Deere, and the engineering design community. If successful, the research will advance the theory and practice of engineering design by introducing several new theoretical foundations for normative decision making within the design process. The theory will (i) align design requirements with the value function for the firm, (ii) align incentive structures with expected utility maximizing behavior, (iii) provide axioms needed for consistent decision making within a design firm. The high risk elements within this award include verifying the new methods with the industry partners and NASA, as well as identifying the transition mechanism to incorporate the decision framework within the current design organizations. Improving the decision making within design enterprises is a cornerstone of the U.S. economy. By appropriately identifying the processes needed for consistent decision making, individuals, design engineers, and various business enterprises will produce better products. Besides the theoretical and experimental work, this award will enable the PI to conduct two workshops in collaboration with NASA Langley, John Deere and other members of the design and manufacturing community: the first will be on "Setting Value-Based Requirements for Engineering Design" and the second will be on 'Aligning Incentive Structures with Expected Utility Maximization'. The research will be disseminated broadly and the award will enable the PI to continue a joint collaboration the Champaign County Juvenile Detention Center (JDC) spreading decision skills to troubled teens.
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
Workshop : Summer School on Decision-Making in Design and Systems Engineering; University of Southern California, Los Angeles, California; June 18-22, 2018
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批准号:1751340
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项目类别:Standard Grant
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资助金额:$5.0万
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财政年份:2017
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负责人:Ali Abbas
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依托单位:
EAGER/Collaborative Research: Lectures for Foundations in Systems Engineering
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批准号:1644991
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项目类别:Standard Grant
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资助金额:$15.0万
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财政年份:2016
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负责人:Ali Abbas
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依托单位:
EAGER: A Decision Analytic Framework for Large-Scale Design and Manufacturing
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批准号:1565168
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项目类别:Standard Grant
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资助金额:$13.5万
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财政年份:2015
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负责人:Ali Abbas
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依托单位:
Collaborative Research: Organizational and Uncertainty Impacts of Couplings in a System Design Framework
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批准号:1629752
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项目类别:Standard Grant
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资助金额:$21.17万
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财政年份:2015
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负责人:Ali Abbas
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依托单位:
Collaborative Research: Organizational and Uncertainty Impacts of Couplings in a System Design Framework
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批准号:1301150
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项目类别:Standard Grant
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资助金额:$24.0万
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财政年份:2013
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负责人:Ali Abbas
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依托单位:
I-Corps: IDecideFast - A web-based application for effective decision making for the layperson
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批准号:1157409
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项目类别:Standard Grant
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资助金额:$5.0万
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财政年份:2011
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负责人:Ali Abbas
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依托单位:
Collaborative Research: Applying Bayesian Predictive Modeling and Decision Theory to Milling Profit Optimization under Uncertainty
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批准号:0927051
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项目类别:Standard Grant
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资助金额:$18.96万
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财政年份:2009
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负责人:Ali Abbas
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依托单位:
CAREER: Decisions with Multiple and Dependent Objectives
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批准号:0846417
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项目类别:Continuing Grant
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资助金额:$24.56万
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财政年份:2009
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负责人:Ali Abbas
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依托单位:
SGER/Collaborative Research: Applying Decision Theory to Machining Optimization
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批准号:0641827
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项目类别:Standard Grant
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资助金额:$0.0万
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财政年份:2006
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负责人:Ali Abbas
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依托单位:
Assessing Joint Distributions with Isoprobability Contours
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批准号:0620008
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项目类别:Standard Grant
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资助金额:$0.0万
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财政年份:2006
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负责人:Ali Abbas
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依托单位:
国内基金
海外基金
Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis
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项目类别:合作创新研究团队
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批准年份:2024
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负责人:姚韬
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依托单位: