Insight最新文献

This first-of-its-kind meta-analysis provides unprecedented insights into systems engineering's evolution through a comprehensive examination of fourteen years of INCOSE International Symposium contributions. By analyzing over 4,000 submissions from nearly 5,000 authors, this study delivers unique value through three interconnected analyses: The Authors Analysis reveals a distinctive “hourglass network” where 10% of contributors generate 43% of intellectual output, alongside a critical 94% first-year attrition rate. This social architecture illuminates both resilience mechanisms and vulnerability points within the knowledge ecosystem, offering stakeholders targeted intervention opportunities for community development. The Topics Analysis documents the discipline's methodological transformation, quantifying the shift toward model-based systems engineering (MBSE) growing from 30% to 40% while revealing persistent knowledge gaps in theoretical foundations and empirical validation. The detailed taxonomic classification exposes high-value research frontiers at disciplinary intersections previously unidentified. The Acceptance Analysis uncovers systematic patterns in knowledge validation, demonstrating how acceptance rates have tightened year-over-year (90% to 40%) while certain submission characteristics significantly impact outcomes. This evidence-based filter mechanism provides contributors with strategic insights for knowledge dissemination. Through synthesizing these analyses, this research provides a cohesive portrait of a discipline at an inflection point—transitioning from practice-driven origins toward greater formalization. For INCOSE leadership, educators, and practitioners, these integrated insights enable data-driven strategies to strengthen community resilience, address knowledge gaps, and enhance systems engineering's capacity to tackle the increasingly complex sociotechnical challenges of the 21st century.

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.

This paper hypothesizes that a system-of-systems (SoS) that is not fit for purpose is so because it cannot implement the correct, timely, and complete transfers of material, energy, and information (MEI) between its constituents and with its external environment that are necessary to achieve a particular result. This research addresses the problem of maintaining a SoS fit for purpose after unpredictable changes in operation, composition, or external factors by creating a method, implemented as an engineering process, and supported by an analysis technique to enhance the affordance {“Features that provide the potential for interaction by affording the ability to do something” (Norman 1999)} of SoS constituents for MEI transfer and reveal potential undesirable transfers.

The introduction of automation into technical systems promises many benefits, including performance increase, improved resource economy, and fewer harmful accidents. In particular, in the automotive sector, automated driving is seen as one key element in Vision Zero by eliminating common accident causes such as driving under the influence, reckless behavior, or distracted drivers. However, this is contrasted by new failure modes and hazards from the latest technologies. In this article, we address the problems of finding common sources of criticality for specific application classes and identifying and quantitatively assessing new sources of harm within particular automated driving systems.

This article summarizes the development of a System of Systems Analytic Workbench (SoS AWB) that provides a set of computational tools to facilitate better-informed decision-making on evolving SoS architectures. The workbench motif is adopted since SoS practitioners typically generate archetypal technical queries that can be mapped to appropriate analysis methods best suited to provide outputs and insights directly relevant to posed questions. After an overview of the workbench framework, four distinct methods currently available for use are presented along with their distinctive aspects in the concept of use.

Engineered Resilient Systems (ERS) is a Department of Defense (DoD) program focusing on the effective and efficient design and development of complex engineered systems across their lifecycle. An important area of focus is the evaluation of early-stage design alternatives in terms of their modeled operational performance and characteristics. The work in this paper ties together differentiated operational needs with requirements specification and maturation of previous analytical constructs toward a more operationally relevant viewpoint. We expand on the concept of Broad Utility as a high-level aggregated measure of robustness of fielded system capabilities with respect to operational requirements. The relation to requirements is more explicit, and systems are failing to achieve threshold requirements are penalized. The impact of this approach and how it offers a foundation from which to more fully explore sensitivity to Pre-Milestone A requirements are discussed.