系统化管理复杂产品网络，提升跨域协同与可持续性。
From product to system network challenges in system of systems lifecycle management
- 以MBSE为语义基础，整合PLM、数字线程与数字孪生构建闭环
- 提出四条原则：架构统一、配置主权、模型审核、价值可度量
- 适合想实现系统级可扩展研发的管理者与工程师
现代产品已非孤立实体，而是网络化系统中的节点。传统线性生命周期模型面临挑战：跨学科互操作性、变体与配置管理、追溯性及跨组织治理日益关键。本文基于文献与产业实践，聚焦交通、医疗与公共部门，提出系统工程生命周期管理框架：以模型化系统工程（MBSE）为语义基础，产品生命周期管理（PLM）为治理与配置层，CAD-CAE为模型衍生领域，数字线程与数字孪生实现持续反馈。识别出四项核心原则：（1）参考架构与数据模型统一，（2）端到端配置主权替代工具孤岛，（3）经审查的模型设置明确评审节点，（4）在时间、质量、成本与可持续性上可度量价值贡献。提出三步转型路径：以参考架构试点，拓展至变体与供应链空间，组织锚定（角色、培训、合规）。结果实现更高变更鲁棒性、更短处理周期、更好复用率与更优可持续决策。本文面向希望管控复杂性并设计可扩展系统价值流的决策者与实践者。
原文摘要 · Abstract (English)
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.
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