| 标 题： |
3D-printing DLP production line modelling and optimisation by event driven simulation
基于事件驱动模拟的3D打印DLP生产线建模与优化 |
| 作 者： |
Zahra Isania
Giuseppe Casalino |
| 关键词： |
Digital light processing (DLP) [数字光处理（DLP）]
3D printing [ 3D打印]
Additive manufacturing [ 增材制造]
Production optimization [ 生产优化]
FlexSim [ FlexSim]
Discrete event simulation (DES) [ 离散事件仿真（DES）] |
| 出版年： |
2026 |
| 期刊名： |
The International Journal of Advanced Manufacturing Technology
先进制造技术国际杂志 |
| 年卷期： |
|
| 摘 要： |
This study presents an event-driven simulation approach to optimizing the production workflow of plastic component manufacturing using 3D-printing Digital Light Processing (DLP). By combining Business Process Model and Notation (BPMN), empirical testing, and Discrete Event Simulation (DES) using FlexSim, this study established a simulation framework that accounts for defects and is tailored to specific geometries. Three production scenarios were evaluated. The model captured the process dynamics from printing to post-processing, including real-world factors such as failure rates, operator availability, and machine configuration. The innovative contribution lies in demonstrating a novel, defect-aware simulation methodology that integrates BPMN-driven process modelling with geometry-specific parameterization and entity-level logic into a Discrete Event Simulation framework. This fusion not only enhances the realism of DLP-based production analysis but also advances the state-of-the-art in modelling and simulation by introducing a scalable, geometrysensitive (entity-parameterized) approach applicable to future real-world additive manufacturing systems (AMS).
本研究提出了一种基于事件驱动的仿真方法，用于优化采用3D打印数字光处理（DLP）制造塑料零部件的生产流程。通过结合业务流程模型与符号（BPMN）、实证测试以及使用FlexSim进行的离散事件仿真（DES），本研究建立了一个考虑缺陷因素并针对特定几何形状量身定制的仿真框架。对三种生产场景进行了评估。该模型全面捕捉了从打印到后处理的工艺动态，包括故障率、操作人员可用性及设备配置等现实因素。研究的创新之处在于，提出了一种新颖的、注重缺陷识别的仿真方法，将BPMN驱动的流程建模与针对几何形状的参数化及实体级逻辑整合进离散事件仿真框架中。这种融合不仅提升了基于DLP的生产分析的真实性，还推动了建模与仿真的前沿发展，为未来实际应用的增材制造系统（AMS）引入了一种可扩展且具几何敏感性的实体参数化方法。 |
| 中文内容为网络AI翻译，专业术语未必准确，仅供参考。 |
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