Mathematical modelling, performance analysis and optimization for the availability of casting system using Markov integrated genetic algorithm approach

This article presents an exploration of mathematical modeling and performance enhancement of a casting system in the steel industry. The study employs the implementation of Markov processes and genetic algorithm to achieve these objectives. The system comprises of four subsystems namely transfer lad...

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Bibliographic Details
Published in:International journal on interactive design and manufacturing 2024-09, Vol.18 (7), p.5139-5149
Main Authors: Mehta, Munish, Singh, Mukhtiar, Francis, Vishal, Singh, Jasvinder, Taufik, Mohammad
Format: Article
Language:English
Subjects:
Availability
CAE) and Design
Computer-Aided Engineering (CAD
Continuous casting
Continuous casting machines
Design optimization
Differential equations
Electronics and Microelectronics
Engineering
Engineering Design
Failure
Genetic algorithms
Grinding machines
Industrial Design
Instrumentation
Iron and steel industry
Markov processes
Mathematical models
Mechanical Engineering
Original Paper
Performance enhancement
Preventive maintenance
Probability distribution functions
Repair
Shot blasting
Subsystems
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Summary:This article presents an exploration of mathematical modeling and performance enhancement of a casting system in the steel industry. The study employs the implementation of Markov processes and genetic algorithm to achieve these objectives. The system comprises of four subsystems namely transfer laddle, continuous casting machine, shot blasting machine and grinding machine. These are arranged in a way that failing of a single subsystem halts the working of overall system. Using probabilistic approach, differential equations have been developed from transition diagram based on Markov process. Failure and repair rates follow exponential distribution. To ascertain steady state availability, differential equations are solved using normalizing conditions. Further, genetic algorithm is applied to find optimal values of failure/repair rates to estimate the optimal plant availability.
ISSN:1955-2513
1955-2505
DOI:10.1007/s12008-023-01572-6