Wanyi Chu

制造业 AI 解决方案顾问 / 工业数字化售前专家。正在德国大众总部负责 AI 辅助工艺规划项目的方案设计与落地推进，具备将制造业务痛点转化为 AI 解决方案、将技术能力包装为商业价值的完整实战经验。拥有大众体系 5 年 IE、精益、效率管理经历，深刻理解汽车制造全流程，能够担任 AI 技术团队与制造业务团队之间的关键翻译角色。目标：AI 解决方案顾问 / 工业数字化售前 / 制造业数字化转型咨询。 Manufacturing AI solution consultant with hands-on delivery experience at Volkswagen AG Headquarters. Currently designing and driving an AI-assisted process planning solution — from on-the-ground pain-point diagnosis to solution architecture, business-case packaging, and eight-figure EUR funding acquisition. Brings 5 years of Volkswagen-system IE, lean, and efficiency management expertise, with deep understanding of end-to-end automotive manufacturing.

Serves as the critical translator between AI engineering teams and manufacturing business stakeholders. Seeking AI solution consulting / industrial digitalization pre-sales / manufacturing digital transformation advisory roles.

AI 工艺规划项目方案负责人 / AI Process Planning Solution Lead at 大众汽车集团德国总部 / Volkswagen AG Headquarters (2026-05 – Present)

大众整车工艺规划长期依赖 IE 工程师手动完成技术文件提取、动作描述编写和 MTM 分析，流程耗时且一致性差。在此背景下，我主导了 AI-assisted Process Planning 的方案设计与商业推进。 Volkswagen's vehicle process planning relied on IE engineers manually extracting information from technical documents, writing action descriptions, and performing MTM analysis — a time-consuming workflow with inconsistent results. In this context, I led the AI-assisted Process Planning solution design and business advancement.

• 深入制造工程和 IE 团队，识别并定义三大核心痛点——技术文件信息提取耗时、工艺动作描述依赖人工经验、MTM 分析效率低——为 AI 方案界定清晰的问题空间。
• Embedded with manufacturing engineering and IE teams to identify and define three core pain points — time-intensive document extraction, experience-dependent manual action descriptions, and low-efficiency MTM analysis — defining a clear problem space for the AI solution.
• 主导端到端解决方案设计——LLM 自动抽取技术文件关键信息 → 生成结构化人工工艺动作描述 → 输出 MTM 分析标准化数据——覆盖从需求诊断到交付的完整链路。
• Led end-to-end solution architecture — LLM-based automatic extraction of key information from vehicle documents → generation of structured manual-process action descriptions → standardized data output for MTM analysis — covering the complete requirements-to-delivery pipeline.
• 独立撰写 EU IPCEI-AI 项目资金申请核心材料，将技术方案转化为「问题 → 方案 → 收益 → 实施路径」的商业叙事，推动项目获得千万欧元级资金批准，进入实施阶段。
• Independently authored the core EU IPCEI-AI funding application, structuring the narrative as "problem → approach → benefit → roadmap" and securing eight-figure EUR funding. Project has entered implementation phase.
• 作为制造工程、IE、AI 研发、软件平台和资金方之间的核心接口人，确保 5 方诉求对齐和方案落地。
• Served as the single interface bridging manufacturing engineering, IE, AI R&D, software platform, and funding body — aligning expectations and driving solution delivery across all 5 parties.

IE 工程师（总装车间及效率管理） / Industrial Engineer, Assembly Shop & Efficiency at 大众安徽 / Volkswagen Anhui (2024-02 – 2026-04)

总装车间面临新车型导入，我负责车门分装线工艺优化和跨车间人力规划。同时，作为公司级项目，主导了全口径人工工时（HPU）管理体系在全公司的导入——这些实战积累构成了面向客户展示制造业领域知识的核心基础。 The assembly shop faced new-model introduction. I owned door sub-assembly line optimization and cross-shop headcount planning. In parallel, I led the company-wide deployment of the HPU management system — hands-on experience that forms the foundation for credible client-facing manufacturing consultation.

• 主持车门分装线生产准备研讨会（Production Process Preparation），通过产线平衡方法对工位进行分析和重组，最终优化 4 个工位，使直接人工工时降低 0.125 小时。
• Led a Production Process Preparation workshop for the door sub-assembly line, applying line-balancing methods to analyze and reorganize workstations — ultimately optimizing 4 workstations and reducing direct labor hours per vehicle by 0.125 hours.
• 构建人力规划数学模型，通过前提条件的数学推演为各车间生成目标人员计划，覆盖千人级编制——建立了以方法论驱动的效率诊断和方案设计能力。
• Built a mathematical headcount-planning model using premise-driven quantitative reasoning to generate target staffing plans for each shop, covering a 1,000+ person workforce — establishing methodology-driven efficiency diagnostics and solution design capabilities.
• 主导 HPU 体系导入：向各职能部门解释算法逻辑，逐一谈判确定各部门年度目标并达成共识；构建 HPU 计算数学模型，建立标准化月度报告机制，并开发自动化报告生成工具替代手工流程——体现从诊断 → 建模 → 工具化的完整方案交付能力。
• Led HPU system deployment: explained calculation methodology to each functional department, negotiated annual targets department by department to achieve alignment; built a mathematical HPU calculation model, established standardized monthly reporting, and developed an automated report generation tool — demonstrating a complete diagnosis → modeling → tooling delivery loop.
• 获得 MTM-1 与 MTM-UAS 认证，将 MTM 方法系统应用于工艺分析和效率评估。
• Earned MTM-1 and MTM-UAS certification; systematically applied MTM methodology to process analysis and efficiency evaluation.

精益培训师 / Lean Trainer at 大众安徽 · 培训与精益中心 / Volkswagen Anhui · Training & Lean Center (2023-08 – 2024-02)

大众安徽快速扩张期，大量新员工对集团生产体系缺乏了解。我独立开发并交付了体系化培训——体现面向客户的知识转移与赋能交付能力。 During Volkswagen Anhui's rapid scale-up, many new employees lacked familiarity with the Group Production System. I independently developed and delivered systematic training — demonstrating client-facing knowledge transfer and enablement delivery capabilities core to consulting.

• 独立设计并交付 KPS 基础培训课程，本地化开发 5S、标准化作业、过程质量及间接区域九大浪费等模块，累计培训 200+ 人次，学员满意度评分位居前列，内容被纳入标准入职体系。
• Designed and delivered KPS Basic Training; localized modules on 5S, standardized work, in-process quality, and nine types of waste in indirect areas. Trained 200+ participants with top-tier satisfaction ratings; content integrated into the standard onboarding curriculum.
• 面向制造运营部管理层开展精益专项培训，将生产体系理念转化为不同层级可理解、可操作的语言。
• Delivered lean training for manufacturing operations division management, translating production-system concepts into language actionable at each organizational level.

培训与精益中心总协调 / General Coordinator, Training & Lean Center at 大众安徽 · 培训与精益中心 / Volkswagen Anhui · Training & Lean Center (2022-07 – 2023-08)

大众安徽需要从零建设培训与精益中心。我主导了从概念到交付的全周期项目。 Volkswagen Anhui needed to build a Training & Lean Center from the ground up. I led end-to-end program delivery from concept to launch.

• 统筹投资规划、施工协调、设备本地化设计、采购及部署全流程，总预算超千万人民币，中心按期交付。
• Orchestrated full lifecycle — investment planning, construction coordination, localized equipment design, procurement, and deployment — with total budget exceeding 10M+ RMB. Center delivered on schedule.
• 负责制造运营部培训间接费用年度预算规划。
• Managed the manufacturing operations division's annual training overhead budget.
• 赴 Audi Brussels 和大众集团零部件天津分公司完成内训师培训。
• Completed train-the-trainer programs at Audi Brussels and Volkswagen Group Components Tianjin.
• 2022 年获评优秀初级员工——体现大型项目交付管理能力。
• Recognized as Excellent Junior Employee in 2022 — demonstrating large-scale program delivery management capability.

效率管理专员 / General Staff, Productivity Management at 大众安徽 / Volkswagen Anhui (2021-08 – 2022-07)

• 参与 Tavascan 车身车间生产准备研讨会，支持新车型产线规划。
• Participated in the Tavascan Body Shop Production Process Preparation Workshop, supporting new-model production line planning.
• 协调制造运营部人力及间接费用预算（战略规划与运营规划轮次），建立对工厂成本逻辑的全貌理解。
• Coordinated the manufacturing operations division's headcount and overhead budget planning across strategic planning and operational planning cycles, building a comprehensive understanding of automotive factory cost logic.
• 担任中试车间工程师认证与蓝领培训项目的总协调。与 HR 联合创建实习生流程与政策体系。
• Served as general coordinator for Pilot Hall Engineer Qualification and blue-collar training programs. Co-created internship process and policy framework with HR.

效率管理实习生 / Intern, Productivity Management at 大众汽车中国投资有限公司 / Volkswagen Group China (2019 – 2021)

为支撑中国区管理层跨工厂生产效率对标决策，按月收集并分析各整车及零部件工厂的工时数据，分析报告被纳入中国区月度生产效率回顾。同期支持间接区域流程优化内训师培训和工作坊，协调大众集团中国区第 20 届工业工程与生产体系年会。 Supported Volkswagen Group China management's cross-plant benchmarking by collecting and analyzing monthly labor-hour data across all China Region plants. Analysis reports were incorporated into the monthly China Region productivity review. Also supported process optimization train-the-trainer sessions and workshops, and coordinated the 20th Volkswagen Group China Industrial Engineering & Production System Conference.

M.Sc. in Materials Science of Steel / 材料科学硕士 – 德国亚琛工业大学（RWTH Aachen） (2017 – 2020)

B.Eng. in Metallurgical Engineering / 冶金工程学士 – 北京科技大学（USTB） (2013 – 2017)