An MDO augmented value-based systems engineering approach to holistic design decision-making: A satellite system case study

The design of large scale complex engineered systems (LSCES) involves hundreds or thousands of designers making decisions at different levels of an organizational hierarchy. Traditionally, these LSCES are designed using systems engineering methods and processes, where the preferences of the stakeholder are flowed down the hierarchy using requirements that act as proxies for preference. Current processes do not provide a system level guidance to subsystem designers. Value-Driven Design (VDD) offers a new perspective on complex system design, where the value preferences of the stakeholder are communicated directly through a decomposable value function, thereby providing a mechanism for improved system consistency. Requirements-based systems engineering approaches do not offer a mathematically rigorous way to capture the couplings present in the system. Multidisciplinary Design Optimization (MDO) was specifically developed to address couplings in both analysis and optimization thereby enabling physics-based consistency. MDO uses an objective function with constraints but does not provide a way to formulate the objective function. Current systems engineering processes do not provide a mathematically sound way to make design decisions when designers are faced with uncertainties. Designers tend to choose designs based on their preferences towards risky/uncertain designs, and past research has shown that there needs to be a consistency in risk preferences to enable design decisions that are consistent with stakeholder’s desires. This research exploits the complimentary nature of VDD, MDO and Decision Analysis (DA) to enable consistency in communication of system preferences, consistency in physics and consistency in risk preferences. The role of VDD in this research is in formulating a value function for true preferences, whereas the role of MDO is to capture couplings and enable optimization using the value function, and the role of DA is to enable consistent design decision-making under

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