Open AccessBehavioral analysis and availability optimization of complex repairable industrial system using particle swarm optimization
Author(s) -
Amit Kumar,
Vinod Kumar,
Vikas Modgil
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1240/1/012158
Subject(s) - particle swarm optimization , container (type theory) , range (aeronautics) , probabilistic logic , computer science , process (computing) , mathematical optimization , reliability engineering , markov chain , engineering , algorithm , mathematics , artificial intelligence , machine learning , mechanical engineering , aerospace engineering , operating system
The complexity in industrial system design under specific practical constraints has a great impact on the range of prediction in system behavior. The data collected in such conditions lead to the high range of uncertainties and the consequence is a possibility of low system performance. Thus, the main objective of the present study is to analyze the system behavior and remove the uncertainties up to the desired accuracy. For this, the mathematical formulation of the system is carried out using probabilistic approach i. e. Markov process. The input failure and repair rate parameters of various sub-systems used in the mathematical expression are considered as constant and statistically independent. Further, the particle swarm optimization (PSO) technique has been used to optimize the system performance in order to improve the system efficiency. A complex repairable system of ton container manufacturing plant has been considered to demonstrate the effectiveness of proposed methodology.