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

Virginia Polytechnic Institute And State University, Blacksburg VA

Investigators

Abstract

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.