基于动态窗口的数字化平台协同机制设计

Design of a Collaborative Mechanism for Digital Platforms Based on Dynamic Windows

摘要: 新型工业化是中国式现代化的重要组成部分，离散制造正在从“先设计后生产”向“设计与制造并行”转型。针对离散智能装备领域中产品生命周期管理(Product Lifecycle Management, PLM)与企业资源计划管理(Product Lifecycle Management, ERP)单向线性集成所引起的审批滞后、计划抖动与供应链不稳定问题，提出并构建了基于部件级精细化状态驱动、动态变更窗口和数字孪生闭环反馈的三位一体并行协同框架。首先，通过引入九级状态标签，实现对变更管理与下发等关键环节的精细化管理；其次，设计双层可配置的频次与时段动态审批窗口，通过批次合并审批平衡响应速度与计划稳定性；最后，集成工厂级数字孪生模型，基于实时BOM与生产线数据实现仿真评估、可视预警、动态优先快速决策闭环。在某大型装备制造企业的验证中，该框架使平均审批周期由4.5天降至1.5天，计划抖动率由28.0%降至8.5%，二次返工次数由3.5次降至1次，显著提升了审批效率、排产稳定性与生产连续性。该方法丰富了产品生命周期管理与供应链协同的理论，为离散制造行业提供了一套可落地的并行协同解决方案。

Abstract: The new wave of industrialization is a vital component of Chinese-style modernization, and discrete manufacturing is shifting from a “design-then-manufacture” paradigm to parallel “design and manufacturing”. To address issues such as approval delays, plan fluctuations, and supply chain instability caused by one-way linear integration of Product Lifecycle Management (PLM) and Enterprise Resource Planning (ERP) in the field of discrete intelligent equipment, this paper proposes and constructs a three-in-one parallel collaborative framework. This framework is driven by component-level refined status management, dynamic change windows, and closed-loop feedback via digital twins. Firstly, by introducing nine-level status tags, the framework enables refined management of key processes such as change management and order release. Secondly, a dual-layer configurable dynamic approval window is designed to balance response speed and plan stability through batch consolidation and flexible approval frequency and periods. Finally, a factory-level digital twin model is integrated, enabling simulation evaluation, visual early warning, and dynamic priority-based rapid decision-making closed-loops based on real-time BOM and production line data. Application and verification in a large equipment manufacturing enterprise showed that the framework reduced the average approval cycle from 4.5 days to 1.5 days, decreased plan fluctuation rate from 28.0% to 8.5%, and reduced the average number of reworks from 3.5 to 1. These improvements significantly enhanced approval efficiency, production scheduling stability, and manufacturing continuity. The proposed method enriches the theory of product lifecycle management and supply chain collaboration and provides a practical parallel collaborative solution for the discrete manufacturing industry.