创新设计是推动未来产业发展的先导与基础环节，也是激发新质生产力的关键；推动创新设计，需坚持哲学思想引领，摒弃跟踪模仿的逆向思维，从单一技术创新迈向系统创新，提升关键领域自主创新能力。本文结合人类文明发展历程，精准识别设计进化规律；结合系统科学理论，分析现代设计与创新设计内在逻辑差异。研究发现，创新设计是基于“人 ‒ 机 ‒ 环境”多要素融合的开放式系统，具备自适应复杂动态环境的能力，结合显性／隐性知识融合的完备知识体系，从本源处激发颠覆性创新。本文基于现象学本质还原方法，结合专长知识学习过程，提出了“知识生成 ‒ 由隐入显 ‒ 由显入隐 ‒ 显隐融合”知识现象学第一原理；基于知识现象学，建立了“设计问题空间 ‒ 显性知识空间 ‒ 隐性知识空间 ‒ 创新解空间”正向创新设计架构；基于“功能 ‒ 行为 ‒ 结构”设计理论逆向解耦，建立了“技术问题空间 ‒ 知识基础识别 ‒ 应用场景预测 ‒ 耦合技术预测”颠覆性技术创新预测架构，联合推进颠覆性创新设计系统工程，并以人形机器人为例，尝试建立了人形机器人颠覆性创新设计框架，初步验证了该系统工程的合理性。最后从科学、技术、产业3个维度，系统分析了全球未来产业发展的竞争态势，提出了发展人工智能与基础研究双向耦合驱动的科研体系、加强关键领域技术研发、健全知识资源的共享服务平台等我国未来产业发展建议。为高效推进创新设计，未来需进一步建立健全细分领域的正向创新设计方法，分类制定技术路线图，强化设计成果的产业应用，更好激发国家创新潜力，支撑未来产业高质量发展。

Innovative design serves as both a precursor and a foundational component in advancing future industries. It is also a key driver in fostering new quality productive forces. To promote innovative design, it is essential to uphold philosophical guidance, abandon the reverse thinking of imitation and follow-up, and shift from isolated technological innovation toward systemic innovation. This approach enhances the independent innovation capacity in critical areas. This study integrates the development trajectory of human civilization to precisely identify the evolutionary patterns of design, and applies systems science theory to analyze the intrinsic logical differences between modern and innovative design. The study finds that innovative design is rooted in an open system that integrates human, machine, and environmental elements. It possesses the capacity to adapt to complex and dynamic contexts. By drawing on a comprehensive knowledge system that fuses explicit and tacit knowledge, it stimulates disruptive innovation at its source. To this end, drawing on the essential reduction method of phenomenology and the process of expert knowledge acquisition, this study establishes a first-principles framework of knowledge phenomenology: knowledge generation‒transition from tacit to explicit‒transition from explicit to tacit‒integration of tacit and explicit knowledge. Based on this foundation, a forward-oriented innovative design framework is proposed: design problem space‒explicit knowledge space‒tacit knowledge space‒innovative solution space. Furthermore, using reverse decoupling based on the function‒behavior‒structure design theory, a predictive framework for disruptive technological innovation is developed: technological problem space‒knowledge base identification‒application scenario prediction‒convergent technology forecasting. This framework enables the integrated advancement of disruptive innovation design as a systems engineering process. Taking humanoid robots as an example, the study establishes a disruptive innovation design framework for humanoid robots and preliminarily validates the rationality of this systems engineering approach. Furthermore, from the three dimensions of science, technology, and industry, this study analyzes the global competitive landscape of future industries and proposes three development recommendations: establishing a research system driven by the bidirectional coupling of artificial intelligence and basic research, strengthening technological research and development in key areas, and improving the knowledge resource sharing platform. To efficiently advance innovative design, three measures can be implemented: establishing and improving forward-oriented design methods for specialized areas; developing categorized technology roadmaps; and strengthening the industrial application of design outcomes, thereby better stimulating national innovation potential and supporting the high-quality development of future industries.