Abstract: Against the backdrop of steady upgrading of the global automotive industry, design change management is upgrading from an auxiliary function to a strategic dimension of core competitiveness for enterprises. This article focuses on the technological evolution path and systematic innovation of design change management in the automotive industry, and proposes a solution framework empowered by the collaboration of digital twins and artificial intelligence.Research has revealed that traditional management models have significant efficiency bottlenecks in responding to high-frequency change demands, while a dynamic balance mechanism based on the "cost-cycle-quality" ternary control model can systematically optimize the resource allocation capability of the entire value chain. By deconstructing multidimensional driving factors such as technological iteration, regulatory upgrades, and supply chain resilience, combined with typical cases in the aerospace and automotive industries, this paper elucidates the breakthrough value of digital twin technology in real-time simulation verification and multi physics coupling optimization, as well as the core role of artificial intelligence in change impact prediction and decision-making closed-loop. To address industry pain points, propose cross platform knowledge accumulation and multidimensional quantitative evaluation strategies, and explore the enhancement effect of intelligent management paradigm on agile response capability and sustainable competitiveness. This study provides theoretical support for the automotive industry to establish a new management system for technology-organization co-evolution in volatile, uncertain, complex, and ambiguous (VUCA) environment, pointing to practical directions for driving the leap of "new qualitative productivity" through digital intelligence integration.

Key words: design changes; process control; multi-dimensional evaluation strategy; digital twin; artificial intelligence; control model; VUCA environment

摘要： 在全球汽车产业稳步升级背景下，设计变更管理正从辅助性职能向企业核心竞争力的 战略维度升级。文章聚焦汽车行业设计变更管理的技术演进路径与体系化创新，提出以数字 孪生与人工智能协同赋能的解决方案框架。研究揭示，传统管理模式在应对高频次变更需求 时存在显著效率瓶颈，而基于“成本-周期-质量”三元控制模型的动态平衡机制，可系统性优 化全价值链资源配置能力。通过解构技术迭代、法规升级、供应链韧性等多维驱动因素，结 合航空航天与汽车行业典型案例，阐明数字孪生技术在实时仿真验证、多物理场耦合优化中的 突破性价值，以及人工智能在变更影响预测与决策闭环中的核心作用。针对行业痛点，提出 跨平台知识沉淀与多维量化评估策略，探讨智能化管理范式对敏捷响应能力与可持续竞争 力的提升效应。该研究为汽车产业在易变、不确定、复杂、模糊（VUCA）环境下构建技术- 组织协同进化的新型管理体系提供理论支撑，指明通过数字智能融合驱动“新质生产力”跃 迁的实践方向。

关键词: 设计变更；过程控制；多维评估策略；数字孪生；人工智能；控制模型；VUCA 环境