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<p>The performance analysis of the syrup manufacturing system in a pharmaceutical plant is explained in this article. The System consists of a Mixer, Filling, Sealing, and Labelling Machines. An expanded variant of Petri Nets called a Stochastic Petri Net (SPN) is used for performance modeling— a Petri Net model created using GRIF Petri Net software. The analysis illustrates the effect of different subsystem’s varied rates of failure and repair on the performance of the system. Matlab software is used to create a 3D graph of the performance of the system. In this article, a Literature review has also been carried out over the last ten years. Research is also carried out on the impact of an increase in repairmen on system performance. For this system, a Decision Support System (DSS) has also been suggested to facilitate the concerned plant management regarding the appropriate maintenance decisions. Critical subsystems are identified using the decision support system to help maintenance management.</p>

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Performability assessment of the syrup manufacturing system of a pharma industry plant applying Stochastic Petri Nets approach

  • 期刊论文

  • 发表日期：

    2025年2月24日

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  • Mausoof Sheikh,
  • P. C. Tewari

摘要

The performance analysis of the syrup manufacturing system in a pharmaceutical plant is explained in this article. The System consists of a Mixer, Filling, Sealing, and Labelling Machines. An expanded variant of Petri Nets called a Stochastic Petri Net (SPN) is used for performance modeling— a Petri Net model created using GRIF Petri Net software. The analysis illustrates the effect of different subsystem’s varied rates of failure and repair on the performance of the system. Matlab software is used to create a 3D graph of the performance of the system. In this article, a Literature review has also been carried out over the last ten years. Research is also carried out on the impact of an increase in repairmen on system performance. For this system, a Decision Support System (DSS) has also been suggested to facilitate the concerned plant management regarding the appropriate maintenance decisions. Critical subsystems are identified using the decision support system to help maintenance management.