Enhancing Early Systems R&D Capabilities with Systems —Theoretic Process Analysis

ABSTRACT Systems engineering today faces a wide array of challenges, ranging from new operational environments to disruptive technological — necessitating approaches to improve research and development (R&D) efforts. Yet, emphasizing the Aristotelian argument that the “whole is greater than the sum of its parts” seems to offer a conceptual foundation creating new R&D solutions. Invoking systems theoretic concepts of emergence and hierarchy and analytic characteristics of traceability, rigor, and comprehensiveness is potentially beneficial for guiding R&D strategy and development to bridge the gap between theoretical problem spaces and engineering‐based solutions. In response, this article describes systems–theoretic process analysis (STPA) as an example of one such approach to aid in early‐systems R&D discussions. STPA—a ‘top‐down’ process that abstracts real complex system operations into hierarchical control structures, functional control loops, and control actions—uses control loop logic to analyze how control actions (designed for desired system behaviors) may become violated and drive the complex system toward states of higher risk. By analyzing how needed controls are not provided (or out of sequence or stopped too soon) and unneeded controls are provided (or engaged too long), STPA can help early‐system R&D discussions by exploring how requirements and desired actions interact to either mitigate or potentially increase states of risk that can lead to unacceptable losses. This article will demonstrate STPA's benefit for early‐system R&D strategy and development discussion by describing such diverse use cases as cyber security, nuclear fuel transportation, and US electric grid performance. Together, the traceability, rigor, and comprehensiveness of STPA serve as useful tools for improving R&D strategy and development discussions. Leveraging STPA as well as related systems engineering techniques can be helpful in early R&D planning and strategy development to better triangulate deeper theoretical meaning or evaluate empirical results to better inform systems engineering solutions.