在工业互联网与人工智能技术深度融合的背景下，高端装备研发呈现出系统复杂、价值主体多、跨生命周期协同要求高等特征。本文聚焦高端装备研发价值链的共创生态与智能协同技术体系，从航空发动机、新能源汽车与动力电池、高端手术机器人及其系统的研发场景分析出发，剖析了高端装备研发过程的价值链结构以及高端装备研发价值链在价值创造、运行机制、调控方式与协同模式等方面呈现出的演化特征；阐述了基于价值共创的自组织管理激励、基于价值分配的自适应运行调控、面向协同研发的数据模型互操作等围绕高端装备研发价值链共创的三大类核心机制设计问题；分析了确定性与不确定性网络融合、智能感知与场景建模、生成式人工智能决策、基于模型的系统工程平台等四项关键智能协同技术；进一步提出了加强链主企业引领作用、强化平台协同基础设施建设、推动核心技术攻关和数据模型互操作标准制定等发展建议。相关研究内容可为高端装备研发价值链的协同创新提供理论基础与技术路径，为推动我国高端制造业的智能化、平台化、生态化转型提供系统支撑。

As the industrial Internet and artificial intelligence (AI) technologies further integrate, the research and development (R&D) of high-end equipment presents the characteristics of complex systems, multiple value entities, and high requirements for cross-lifecycle collaboration. Focusing on the co-creation ecology and the intelligent collaboration technology system within the R&D value chain of high-end equipment, this study analyzes the R&D scenarios of aero-engines, new energy vehicles and power batteries, as well as high-end surgical robots and their systems. It examines the value chain structure intrinsic to the high-end equipment R&D processes and delineates the evolutionary characteristics exhibited by this value chain across dimensions including value creation, operational mechanisms, regulatory approaches, and collaborative paradigms. Moreover, the study elaborates on three core mechanism design challenges regarding the co-creation along this value chain: self-organized management incentives based on value co-creation, adaptive operational regulation based on value distribution, and data‒model interoperability for collaborative R&D. Furthermore, it discusses four pivotal intelligent collaboration technologies: integration of deterministic and uncertain networks, intelligent sensing and scenario modeling, generative AI for intelligent decision-making, and intelligent Model-Based Systems Engineering (MBSE) platforms. Conclusively, four recommendations are proposed, such as strengthening the leading role of core enterprises (chain leaders), reinforcing the construction of platform-based collaborative infrastructures, and promoting the breakthroughs in core technologies alongside the establishment of standards for data‒model interoperability. This study aims to provide a theoretical basis and technical path for the collaborative innovation within the R&D value chain of high-end equipment, providing systematic support for promoting the intelligent, platform-based, and ecological transformation of the high-end manufacturing industry.