绿色化与智能化协同发展研究综述：演进逻辑、融合模式与未来挑战

A review of the synergistic development of green and intelligent manufacturing: Evolutionary logic, integration models, and future challenges

摘要

绿色化与智能化已成为制造业高质量发展的核心导向，在碳排放双控制度、“人工智能+制造”等专项行动政策赋能下，二者深度融合成为构建循环可持续现代产业体系、推动制造业转型升级的关键路径. 本文基于制造业发展新形势，首先系统梳理绿色制造与智能制造的演进历程和发展现状，剖析二者融合发展的内在逻辑与必然趋势；其次，构建绿色化与智能化融合发展新模式，提出了内生碳变量（Endogenous carbon variables, ECV）这一重要思想，搭建了“感–联–知–控–碳”一体化架构，并系统阐释 ECV–智能制造的核心技术体系；最后，从技术、生态、管理三个维度，提出 ECV–智能制造模式落地面临的现实挑战，为制造业实现绿色与智能协同发展、破解发展瓶颈提供理论支撑与实践路径指引.

Abstract

Greenization and intelligentization are focus areas for the high-quality development of manufacturing industry in the new era, and they are critical for China to address global climate change, achieve “dual carbon” goals, and enhance core industrial competitiveness. Empowered by policies such as dual control over the amount and intensity of carbon emissions and the special initiative of “Artificial Intelligence+Manufacturing,” the in-depth integration of green manufacturing and intelligent manufacturing is not only an inherent requirement for building a circular and sustainable industrial system, but is also important to drive the transformation and upgrading of the manufacturing industry from extensive development to refined and low-carbon development. This is of great practical significance for realizing the coordinated development of ecological and economic benefits. Based on current opportunities and challenges impacting the development of the manufacturing industry, this study first performs a systematic review of the evolution process and development status of green manufacturing and intelligent manufacturing. The development of green manufacturing has undergone an evolutionary process from passive compliance to active management. Relying on new-generation information technologies such as big data, artificial intelligence and the Internet of Things, intelligent manufacturing has realized the intelligent transformation of production processes and greatly improved production efficiency and product quality. On this basis, the study analyzes the internal logic of their integrated development, and highlights that green manufacturing provides development orientation for intelligent manufacturing, while intelligent manufacturing offers technical support for green manufacturing. The synergies between the two approaches are mutually beneficial, and their integrated development is important for the high-quality development of the manufacturing industry. Secondly, to solve the current problems such as inadequate integration and poor coordination between the two, this paper proposes the concept of endogenous carbon variables (ECV), embedding carbon factors into the whole process of intelligent manufacturing and breaking the traditional model of “production first, emission reduction later.” To achieve this, the study constructs an integrated architecture of “Sensing–connecting–cognition–control–carbon.” In this architecture, “Sensing” accurately collects carbon data throughout the production process; “Connecting” realizes the interconnection and intercommunication of various sets of data; “Cognition” achieves the precise accounting and optimization of carbon footprints relying on algorithmic models; and “Control” realizes the real-time regulation of carbon emissions in production processes. As the ultimate goal and core of the architecture, “Carbon” is integrated into various levels and serves as the ultimate goal of the entire framework. This paper systematically discusses the core technical system of ECV intelligent manufacturing, covering intelligent perception and digital twin technology, data circulation and industrial Internet technology, data-driven and AI optimization technology, as well as closed-loop control and edge computing technology, which provides robust technical support for the implementation of the integrated model. Finally, combined with the actual development of China’s manufacturing industry, it systematically analyzes practical challenges in the implementation of the ECV intelligent manufacturing model from three dimensions, namely technology, ecology, and management. From the technological perspective, green and low-carbon intelligent manufacturing systems are limited with respect to carbon data acquisition, multi-source data fusion, and intelligent optimization and control. From an ecological perspective, there is a lack of sound coordination mechanisms and industrial chain support. From a management perspective, imperfect corporate carbon management systems and data governance mechanisms, as well as human capacity deficiencies all restrict the green transformation of manufacturing enterprises. This paper aims to provide solid theoretical support for the coordinated green and intelligent development of the manufacturing industry, help China’s manufacturing industry accelerate the construction of a low-carbon industrial system, and elevate the development of the manufacturing industry to a new level.

关键词

绿色制造 / 智能制造 / 制造业转型 / 内生碳变量 / 低碳工业

Key words

green manufacturing / intelligent manufacturing / manufacturing transformation / endogenous carbon variables / low-carbon industry

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基金资助

国家自然科学基金资助项目(U25A20433)

国家自然科学基金资助项目(92567203)

国家自然科学基金资助项目(62573044)