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<p>In today’s competitive landscape, the demand for scheduling optimization to enhance processes and industrial plants is rapidly increasing. To address this need, we introduce a scheduling optimization approach for a compact continuous pharmaceutical manufacturing line by developing a mixed integer linear programming (MILP) model that incorporates all necessary constraints and bounds. The MILP employs a continuous time representation and an extension to a multi-product manufacturing line to improve the capabilities of current equipment and the model itself is shown. To reinforce the ideas and exemplify the overall concept, we present simulation results, demonstrating the optimal scheduling plans for various scenarios. In a case study, we applied the MILP to a manufacturing line and successfully integrated the optimal scheduling plan into the plant. Our results show that the time constraints, expected mass flows, and mass hold-ups align with those of the optimal scheduling plan, confirming that fully automated and integrated operations are feasible.</p>

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Scheduling Optimization of a Compact End-to-End Pharmaceutical Manufacturing Line: Design and Experimental Evaluation

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年4月8日

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  • Sebastian Knoll,
  • Martin Steinberger,
  • Lisa Kuchler,
  • Atabak Azimi,
  • Markus Tranninger,
  • Stephan Sacher,
  • Martin Horn

摘要

In today’s competitive landscape, the demand for scheduling optimization to enhance processes and industrial plants is rapidly increasing. To address this need, we introduce a scheduling optimization approach for a compact continuous pharmaceutical manufacturing line by developing a mixed integer linear programming (MILP) model that incorporates all necessary constraints and bounds. The MILP employs a continuous time representation and an extension to a multi-product manufacturing line to improve the capabilities of current equipment and the model itself is shown. To reinforce the ideas and exemplify the overall concept, we present simulation results, demonstrating the optimal scheduling plans for various scenarios. In a case study, we applied the MILP to a manufacturing line and successfully integrated the optimal scheduling plan into the plant. Our results show that the time constraints, expected mass flows, and mass hold-ups align with those of the optimal scheduling plan, confirming that fully automated and integrated operations are feasible.