OPTIMIZATION AND PERFORMANCE EVALUATION OF SUGAR MILL PLANT MICRO COMPONENTS USING PSO.

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Bibliographic Details
Title:	OPTIMIZATION AND PERFORMANCE EVALUATION OF SUGAR MILL PLANT MICRO COMPONENTS USING PSO.
Authors:	Kumar, Sandeep¹ praansandeep@gmail.com
Source:	Reliability: Theory & Applications. Dec2025, Vol. 20 Issue 4, p1241-1253. 13p.
Subjects:	Particle swarm optimization, Systems availability, Operations research, Reliability in engineering, Mathematical optimization, Failure analysis, Sugar factories, Markov processes
Abstract:	Sugar mill plants, especially their core processing units, are highly dependent on a well-organized and efficient maintenance strategy for reliable operation. In this study, an availability-based simulation model was developed for a 25,500 TCD sugar mill. This model is based on a Markov-based performance evaluation framework, which uses differential equations to form state-transition diagrams representing transitions between fully operational, partially operational, and failure states. A comparative analysis of the subcomponents studied concluded that a centrifugal pump failure has minimal impact on overall system availability, while a clarification unit failure has the most significant impact. To improve system reliability and performance, the Particle Swarm Optimization (PSO) method was applied to optimize failure and repair rates. The experimental results obtained show that the overall availability of the system after applying the proposed optimization strategy is achieved at 88.57%, which shows effectiveness and practical utility of the model. [ABSTRACT FROM AUTHOR]
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Database:	Engineering Source

Description
Abstract:	Sugar mill plants, especially their core processing units, are highly dependent on a well-organized and efficient maintenance strategy for reliable operation. In this study, an availability-based simulation model was developed for a 25,500 TCD sugar mill. This model is based on a Markov-based performance evaluation framework, which uses differential equations to form state-transition diagrams representing transitions between fully operational, partially operational, and failure states. A comparative analysis of the subcomponents studied concluded that a centrifugal pump failure has minimal impact on overall system availability, while a clarification unit failure has the most significant impact. To improve system reliability and performance, the Particle Swarm Optimization (PSO) method was applied to optimize failure and repair rates. The experimental results obtained show that the overall availability of the system after applying the proposed optimization strategy is achieved at 88.57%, which shows effectiveness and practical utility of the model. [ABSTRACT FROM AUTHOR]
ISSN:	19322321
DOI:	10.24412/1932-2321-2025-489-1241-1253