Large-scale systems engineering efforts involving multiple stakeholders often have been problematic, and there has been recent interest in understanding how to improve the systems engineering process.
A Highly-Optimized Tolerance (HOT)-Inspired Model of the Large Scale Systems Engineering Process
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Large-scale systems engineering efforts involving multiple stakeholders often have been problematic, and there has been recent interest in understanding how to improve the systems engineering process. This paper presents an approach to modeling the systems engineering process, with possible extensions to systems investment and systems operations, inspired by the highly optimized tolerance (HOT) framework for understanding complexity in designed systems. HOT is complementary to agent-based modeling (ABM) in the sense that it emphasizes the centrally planned aspect of designed systems with tradeoffs and uncertainty, rather than distributed decision making based on local knowledge and goals. To begin the exploration of models of the systems engineering process, a temporal model is presented with stakeholder interactions modeled as random events. Following the HOT approach, planning behavior is framed as stochastic optimization, which is reduced to a open-loop control problem. The initial results suggest promise for the HOT-inspired framework in helping to understand how to improve the systems engineering process, but more exploratory work is needed, including work on relating actual systems engineering experience to the models