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离散制造企业数字化改造新范式
电子技术应用
徐赤1,王维维2,林大涛3,朱晗3
1.杭州自动化技术研究院;2.中国计量大学;3.图快数字科技(杭州)公司
摘要: 离散制造企业在推进数字化改造过程中,普遍面临数据孤岛现象突出、数据治理体系不完善、系统数据与业务调度机制不统一、应用协同性不足以及建设路径模糊等多重挑战。首先系统性地分析了数据中台、工业互联网平台、微服务架构、企业服务总线等现有主流技术方案的优势与局限性,指出其在应对中小离散制造企业需求时普遍存在数据与业务分离、数据可靠性保障不足、成本与效果矛盾、缺乏统一调度机制等共性问题。针对这些问题,提出了一种全新的数字化改造范式,主要包括以下创新举措:以数据标准为突破口,构建覆盖制造企业全域、全量、全时的数据治理体系;以企业大脑为核心,构建依托大模型支撑的放射状数字化架构;以数据底座为平台,建立多源异构系统数据与业务的统一调度机制;以小快轻准为原则,打造基于低代码开发的微单元协同型应用集群模式;以透明工厂为实施抓手,探索企业数字化改造与未来工厂建设的新路径。新范式通过数据与业务一体化融合、存储订阅机制创新、企业主导的数据标准、轻量化应用集群和放射状架构设计五大核心突破,有效解决了现有方案的局限性。……
中图分类号:T-01 文献标志码:A DOI: 10.16157/j.issn.0258-7998.257630
中文引用格式: 徐赤,王维维,林大涛,等. 离散制造企业数字化改造新范式[J]. 电子技术应用,2026,52(3):139-148.
英文引用格式: Xu Chi,Wang Weiwei,Lin Datao,et al. A new paradigm for digital transformation in discrete manufacturing enterprises[J]. Application of Electronic Technique,2026,52(3):139-148.
A new paradigm for digital transformation in discrete manufacturing enterprises
Xu Chi1,Wang Weiwei2,Lin Datao3,Zhu Han3
1.Hangzhou Institute of Automation Technology;2.China Jiliang University;3.TuKua Digital Technology (Hangzhou) Co., Ltd.
Abstract: Discrete manufacturing enterprises face multiple challenges in advancing digital transformation, including prominent data silos, inadequate data governance systems, inconsistencies between system data and operational scheduling mechanisms, insufficient application collaboration, and unclear implementation pathways. This paper first systematically analyzes the advantages and limitations of existing mainstream technical solutions such as data middle platform, industrial internet platform, microservice architecture, and enterprise service bus, pointing out their common problems in addressing the needs of small and medium-sized discrete manufacturing enterprises, including data-business separation, insufficient data reliability assurance, cost-benefit contradictions, and lack of unified scheduling mechanisms. To address these issues, this paper proposes a new paradigm for digital transformation, which mainly includes the following innovative measures: Using data standards as the breakthrough point, establish a comprehensive data governance system that covers all aspects, encompasses all data, and operates in real time across manufacturing enterprises; Centered around the corporate brain, build a radial digital architecture supported by large models; Using the data foundation as a platform, establish a unified scheduling mechanism for multi-source heterogeneous system data and business operations; Adopting the principles of small, fast, lightweight, and precise, to build a micro-unit collaborative application cluster model based on low-code development; Using transparent factories as the implementation vehicle, to explore new pathways for enterprise digital transformation and future factory construction. The new paradigm effectively addresses the limitations of existing solu
Key words : discrete manufacturing;digitalization;enterprise brain; data foundation;application cluster;data governance

引言

在当前全球制造业转型升级的浪潮中,离散制造企业的数字化改造已成为提升竞争力、实现可持续发展的核心战略[1]。随着工业4.0与智能制造的深入推进,制造业正经历从传统生产模式向数字化、网络化、智能化方向的根本性变革[2]。这一转变不仅是技术层面的升级,更涉及企业管理、运营机制乃至商业模式的系统性重构。离散制造企业通常面临高度定制化的生产需求,导致数据采集与处理的复杂度显著提升[3]。此外,企业内部普遍存在信息孤岛,各类系统之间数据难以集成与共享,严重制约了数字化改造的进程。加之企业在资金、技术、人才等方面的资源约束,进一步增加了数字化转型的不确定性与实施难度[4]。

因此,推进数字化改造不仅是离散制造企业顺应产业变革的重要方向,更是构筑核心竞争力和实现长远发展的关键路径[5]。通过深度的数字化赋能,企业才能在日益激烈的市场竞争中保持优势,并实现高质量、可持续的增长。


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作者信息:

徐赤1,王维维2,林大涛3,朱晗3

(1.杭州自动化技术研究院,浙江 杭州 310012;

2.中国计量大学, 浙江 杭州 310018;

3.图快数字科技(杭州)公司, 浙江 杭州 310012)

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