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<p>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, geometry-sensitive (entity-parameterized) approach applicable to future real-world additive manufacturing systems (AMS).</p>

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3D-printing DLP production line modelling and optimisation by event driven simulation

  • 期刊论文

  • 发表日期：

    2026年3月3日

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  • Zahra Isania,
  • Giuseppe Casalino

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, geometry-sensitive (entity-parameterized) approach applicable to future real-world additive manufacturing systems (AMS).