Arnold Reuser

AI-Supported Architectural Reasoning for High-Tech
Systems-of-Systems

Bio.

Bio: Arnold Reuser is a Systems Engineer with 20+ years of experience leading digital transformations across diverse industries, business domains, and architectural layers.  At ASML, he focuses on Systems-of-Systems Engineering for Data & Digital Platforms, with a particular emphasis on improving customer ecosystem availability. He holds a Master’s degree in Pure Mathematics (cum laude) and a Bachelor’s degree in Applied Computer Science (cum laude).

Abstract.

High-tech systems increasingly operate within Systems-of-Systems (SoS) in which independently managed systems, organizations, data platforms, and digital ecosystems jointly deliver emergent capabilities. This broadens architectural reasoning: decisions must connect technical interfaces with enterprise context, ecosystem dependencies, lifecycle evolution, stakeholder concerns, and propagating risks. In practice, however, requirements, models, decisions, evidence, and rationale remain distributed across tools and teams, while important knowledge remains tacit. This paper proposes a conceptual framework for an AI-supported architectural reasoning environment that connects engineering artefacts, an architectural knowledge layer, AI reasoning services, and a human decision workbench. The paper identifies six capabilities: knowledge extraction, cross-view consistency analysis, trade-off reasoning, design-space exploration, risk and issue detection, and explainable insight generation.  The framework is illustrated through a proposed federated, Git-based governance model, an active ARCHAR pilot with beta functionality for reviewing product- and system-level requirements specifications against INCOSE requirements-writing rules, and the proposed Product Architecture Reconstruction (PARC) capability. AI is positioned as an evidence-grounded reasoning advisor; formal decision authority and accountability remain with human architects.