From product to system network challenges in system of systems lifecycle management

TL;DR

This paper discusses the transition from traditional product lifecycle models to network-centric system of systems management, emphasizing interoperability, governance, and continuous feedback for scalable and sustainable development.

Contribution

It proposes a practical framework integrating MBSE, PLM, CAD-CAE, digital twin, and digital thread for effective SoS lifecycle management based on current literature and industry experience.

Findings

Increased change robustness and shorter throughput times.

Improved reuse and sustainability decisions.

Guidelines for transitioning to network-centric development.

Abstract

Today, products are no longer isolated artifacts, but nodes in networked systems. This means that traditional, linearly conceived life cycle models are reaching their limits: Interoperability across disciplines, variant and configuration management, traceability, and governance across organizational boundaries are becoming key factors. This collective contribution classifies the state of the art and proposes a practical frame of reference for SoS lifecycle management, model-based systems engineering (MBSE) as the semantic backbone, product lifecycle management (PLM) as the governance and configuration level, CAD-CAE as model-derived domains, and digital thread and digital twin as continuous feedback. Based on current literature and industry experience, mobility, healthcare, and the public sector, we identify four principles: (1) referenced architecture and data models, (2) end-to-end configuration sovereignty instead of tool silos, (3) curated models with clear review gates, and (4) measurable value contributions along time, quality, cost, and sustainability. A three-step roadmap shows the transition from product- to network- centric development: piloting with reference architecture, scaling across variant and supply chain spaces, organizational anchoring (roles, training, compliance). The results are increased change robustness, shorter throughput times, improved reuse, and informed sustainability decisions. This article is aimed at decision-makers and practitioners who want to make complexity manageable and design SoS value streams to be scalable.