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Growing Science » International Journal of Industrial Engineering Computations » Performance analysis and optimization for CSDGB filling system of a beverage plant using particle swarm optimization

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International Journal of Industrial Engineering Computations

ISSN 1923-2934 (Online) - ISSN 1923-2926 (Print)
Quarterly Publication
Volume 8 Issue 3 pp. 303-314 , 2017

Performance analysis and optimization for CSDGB filling system of a beverage plant using particle swarm optimization Pages 303-314 Right click to download the paper Download PDF

Authors: Parveen Kumar, P.C. Tewari

DOI: 10.5267/j.ijiec.2017.1.002

Keywords: Performance optimization, PSO, Bottling system, Markov approach

Abstract: The paper deals with the performance analysis and optimization for Carbonated Soft Drink Glass Bottle (CSDGB) filling system of a beverage plant using Particle Swarm Optimization (PSO) approach. The CSDGB system consists of seven main subsystems arranged in series namely Uncaser, Bottle Washer, Electronic Inspection Station, Filling Machine, Crowner, Coding Machine and Case Packer. Considering exponential distribution for probable failures and repairs, mathematical modeling is performed using Markov Approach (MA). The differential equations have been derived on the basis of probabilistic approach using transition diagram. These equations are solved using normalizing condition and recursive method to drive out the steady state availability expression of the system i.e. system’s performance criterion. The performance optimization of system has been carried out by varying the number of particles and number of generations. It has been observed that the maximum availability of 90.27% is achieved at flock size of 55 and 90.84% at 300th generation. Thus, findings of the paper will be useful to the plant management for execution of proper maintenance decisions.

How to cite this paper
Kumar, P & Tewari, P. (2017). Performance analysis and optimization for CSDGB filling system of a beverage plant using particle swarm optimization.International Journal of Industrial Engineering Computations , 8(3), 303-314.

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Journal: International Journal of Industrial Engineering Computations | Year: 2017 | Volume: 8 | Issue: 3 | Views: 3643 | Reviews: 0

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