EAGER: Advancing the Foundations of Systems Engineering through Multiscale Decision Theory

从微芯片到宇宙飞船，工程系统的复杂性正在迅速增长。系统工程过程中使用的当前设计方法和管理工具将无法支持这种复杂性的增长。例如，预计指导设计过程的系统要求的标准做法不能确保创造最大价值，并且随着子系统数量的增加及其相互依赖性的增加，其表现会更差。通过从需求驱动转向价值驱动的设计方法，这个问题可以克服。价值驱动的设计方法关注系统在整个系统生命周期中为用户创造的价值。然而，目前尚不清楚这种价值驱动的设计方法如何在实践中运作。各组织应如何调整其管理结构、信息系统和奖励制度？该奖项支持基础研究，从组织的角度推进系统工程理论。EARLY概念探索性研究资助（EAGER）项目的洞察力将使组织和系统工程师能够在更短的时间内为客户创造更多的价值。因此，本研究的成果有可能有利于美国的经济和society.The本研究的目标是通过数学建模的影响和相互依赖的组织结构，激励，时间和信息系统的价值创造系统设计过程中获得基本的见解。数学建模方法是基于多尺度决策理论，它已经发展到捕捉多层次和多阶段的决策者在组织中的相互作用。它通过整合各种分析方法，如博弈论和马尔可夫决策过程来实现这一点。研究团队将应用多尺度决策理论来确定组织结构和激励机制，激励和引导系统工程师和管理人员实现最大价值创造。为了说明信息和通信在系统设计过程中的作用，多尺度决策理论将通过结合部分可观察的马尔可夫决策过程来推进，从而在量化通信的好处的同时对组织中的信息不确定性和不对称性进行建模。

The complexity of engineered systems, ranging from microchips to spaceships, is growing rapidly. Current design methods and management tools used during the systems engineering process will not be able to support this growth in complexity. For example, it is expected that the standard practice of system requirements guiding the design process cannot ensure maximum value creation, and performs worse as the number of subsystems grows and their interdependencies increase. By moving from a requirement-driven to a value-driven design approach, this problem may be overcome. A value-driven design approach focuses on the value the system creates for the user over the system life cycle. However, it is unclear how this value-driven design approach can be operationalized in practice. How should organizations adapt their management structures, information systems and reward systems? This award supports fundamental research to advance the theory of systems engineering from an organizational perspective. Insight from this EArly-concept Grant for Exploratory Research (EAGER) project will enable organizations and systems engineers to create more value in shorter time for their customers. The outcomes of this research thus have the potential to benefit the U.S. economy and society.The objective of this research is to derive fundamental insights into the system design process by mathematically modeling the effects and interdependencies of organizational structures, incentives, time, and information on system value creation. The mathematical modeling approach is based on multiscale decision theory, which has been developed to capture the multi-level and multi-period interactions of decision makers in organizations. It accomplishes this by integrating various analytical methods, such game theory and Markov decision processes. The research team will apply multiscale decision theory to identify organizational structures and incentive mechanisms that motivate and guide systems engineers and managers towards maximum value creation. To account for the role of information and communication in the system design process, multiscale decision theory will be advanced by incorporating partially observable Markov decision processes, enabling the modeling of information uncertainty and asymmetries in organizations while quantifying the benefits of communication.