Volume 2 Issue 3 pp. 689-698 Summer, 2011


Mathematical modelling and performance optimization of CO2 cooling system of a fertilizer plant


Sanjeev Kumar and P. C. Tewari


This paper discusses the mathematical modeling and performance optimization of CO2 cooling system of a fertilizer plant using genetic algorithm. The fertilizer plant comprises of various systems viz. shell gasification and carbon recovery, desulphurization, co-shift conversion, decarbonation- CO2 cooling, CO2 removal, nitrogen wash and ammonia synthesis, etc. One of the most important functionaries of a fertilizer plant is CO2 cooling system. The CO2 cooling system of a fertilizer plant has five main subsystems, arranged in series. We propose a mathematical model, which considers exponential distribution for the probable failures and repairs. We also use probabilistic approach and derive differential equations based on Markov birth-death process. These equations are then solved using normalizing conditions to determine the steady state availability of the CO2 cooling system. The performance of each subsystem of CO2 cooling system of a fertilizer plant is also optimized using genetic algorithm. The results of the proposed model of this paper is useful to the plant management for the timely execution of proper maintenance decisions and hence to enhance the system performance.


DOI: 10.5267/j.ijiec.2010.08.004

Keywords: Performance optimization, CO2 cooling system, Genetic algorithm, Meta-heuristic
References

Arora, N., & Kumar, D. (1997). Availability analysis of steam and power generation systems in thermal power plant. International Journal of Microelectronics Reliability, 37, 795-799.

Boudali, H., & Dugan, J. B. (2005). A discrete-time Bayesian network reliability modeling and analysis framework. Reliability Engineering and System Safety, 87, 337–349.

Castro, H. F., & Cavalca, K. (2003). Availability optimization with genetic algorithm. International Journal of Quality and Reliability Management, 20 (7), 847-863.

Chales, C., & Kondo, A. (2003). Availability allocation to repairable systems with genetic algorithms: a multi-objective formulation. Reliability Engineering and System Safety, 82 (3), 319-330.

Dhillon, B.S., & Singh, C. (1981). Engineering reliability- new techniques and applications. New York: John Wiley and Sons.

Goldberg, D. E. (2003). Genetic algorithm in search, optimization and machine learning. Pearson Education Asia New Delhi.

Kurien, K. C. (1988). Reliability and availability analysis of repairable system using discrete event simulation. Ph.D Thesis, Indian Institute of Technology, New Delhi,

Kenaraagui, R., & Husseiny, A. (1988). Reliability and availability analysis of fusion power plants. International Journal of Engineering, 1 (1), 63-72.

Kumar, D., Singh, I.P., & Singh, J. (1988). Reliability analysis of the feeding system in the paper industry. International Journal of Microelectronics Reliability, 28, 213-215.

Kumar, D., Singh, I.P., & Singh, J. (1988). Availability of the feeding system in the sugar industry. International Journal of Microelectronics Reliability, 28, 867-871.

Kumar D., & Pandey, P.C. (1993). Maintenance planning and resource allocation in urea fertilizer Plant. International Journal of Quality and Reliability Engineering, 9, 411-423.

Kumar, S., Kumar, D. & Mehta, N. P. (1999). Maintenance Management for Ammonia Synthesis System in a Urea Fertilizer Plant. International Journal of Management and System (IJOMAS), 15, 211-214.

Kumar, S., Tewari, P.C., & Kumar, S. (2008). Development of performance evaluating model for CO-Shift conversion system in the fertilizer plant. International Journal of Engineering Research and Industrial Applications (IJERIA), 1(6), 369-382.

Kumar, S., Tewari, P.C., & Kumar, S. (2009). Simulation model for evaluating the performance of urea decomposition system in a fertilizer plant. International Journal of Industrial Engineering and Practices,1(1),10-14.

Kumar, S., Tewari,P. C., Kuma, S. & Gupta, M. (2010). Availability optimization of CO-Shift conversion system of a fertilizer plant using genetic algorithm technique. Bangladesh Journal of Scientific and Industrial Research (BJSIR), 45 (2),133-140.

Somani, A. K., & Ritcey, J. A. (1992). Computationally efficient phased mission reliability analysis for systems with variable configuration., IEEE Transactions on Reliability, 41(4), 504–511.

Srinath, L. S. (1994). Reliability Engineering, 3rd. edition, East-West Press Pvt. Ltd., New Delhi.

Tewari, P.C., Kumar, D., & Mehta, N.P. (2000). Decision support system of refining system of sugar plant. Journal of Institution of Engineers (India), 84, 41-44.

Tewari, P.C., Joshi, D., & Rao, S. M., (2005). Mathematical modeling and behavioural analysis of a refining system using genetic algorithm. Proceedings of National Conference on Competitive Manufacturing Technology and management for Global Marketing, Chennai, 131-134.

Tsai, Y.T., Wang, K.S., & Teng, H.Y. (2001). Optimizing preventive maintenance for mechanical components using genetic algorithms. Reliability Engineering and System Safety, 74 (1), 89-97.