Performance Modeling and Availability Analysis of Yarn Dyeing System of a Textile Industry
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 33122
Performance Modeling and Availability Analysis of Yarn Dyeing System of a Textile Industry

Authors: P. C. Tewari, Rajiv Kumar, Dinesh Khanduja

Abstract:

This paper discusses the performance modeling and availability analysis of Yarn Dyeing System of a Textile Industry. The Textile Industry is a complex and repairable engineering system. Yarn Dyeing System of Textile Industry consists of five subsystems arranged in series configuration. For performance modeling and analysis of availability, a performance evaluating model has been developed with the help of mathematical formulation based on Markov-Birth-Death Process. The differential equations have been developed on the basis of Probabilistic Approach using a Transition Diagram. These equations have further been solved using normalizing condition in order to develop the steady state availability, a performance measure of the system concerned. The system performance has been further analyzed with the help of decision matrices. These matrices provide various availability levels for different combinations of failure and repair rates for various subsystems. The findings of this paper are therefore, considered to be useful for the analysis of availability and determination of the best possible maintenance strategies which can be implemented in future to enhance the system performance.

Keywords: Availability Analysis, Markov Process, Performance Modeling, Steady State Availability.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1089086

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2309

References:


[1] Khan, M. R. R. and Kabir, A. B. M. Z. (1995), "Availability Simulation of an Ammonia Plant”, Reliability Engineering and System Safety, Vol. 48, pp. 217-227.
[2] Coit, D. W., Jin, T., and Wattanapongsakorn, N. (2004), "System Optimization Considering Component Reliability Estimation Uncertainty: A Multi-Criteria Approach”, IEEE Transactions on Reliability, vol. 53, no. 3, pp. 369-380.
[3] Dai, Y. S., Wang, X. L. (2006),”Optimal Resource Allocation on Grid Systems for Maximizing Service Reliability Using a Genetic Algorithm”, Reliability Engineering and System Safety, No. 91, pp. 1071-1082.
[4] Sharma, R.K. and Kumar, S. (2008), "Performance Modeling in Critical Engineering Systems using RAM Analysis”, Reliability Engineering and System Safety, Vol. 93, pp. 891–897.
[5] Kumar, S., Tewari, P.C. (2009), "Performance Evaluation and Availability Analysis of Ammonia Synthesis Unit in a Fertilizer Plant”, Journal of Industrial Engineering International, vol. 5, no. 9, pp. 17-23.
[6] Garg, Deepika, Singh, Jai and Kumar, Kuldeep (2009), "Performance Analysis of a Cattle Feed Plant”, Journal of Science & Technology ICFAI, vol. 5, no. 2, pp. 83-94.
[7] Garg, S., Singh, J., and Singh, D.V. (2010), "Availability and Maintenance Scheduling of a Repairable Block-Board Manufacturing System”, International Journal of Reliability and Safety, vol. 4, no. 1, pp. 104- 118.
[8] Sachdeva, A., Kumar, D. and Kumar, P. (2010), "Planning and Optimizing the Maintenance of Paper Production Systems in a Paper Plant”, International Journal of Computers & Industrial Engineering, vol. 55, pp. 817–829.
[9] Kumar, S. and Tewari, P.C.(2011), "Mathematical Modeling and Performance Optimization of CO2 Cooling System of a Fertilizer Plant ” , International Journal of Industrial Engineering Computations , vol. 2, pp. 689-695.
[10] Khanduja, R., Tewari,P.C., and Chauhan, R.S.(2012), "Performance Modeling and Optimization for the Stock Preparation Unit of a Paper Plant using Genetic Algorithm”, International Journal of Quality and reliability Management, Vol. 28, No. 6, pp. 688-703.
[11] Wang, Z. et al. (2013),"A New Approach for Reliability Analysis with Time-Variant Performance Characteristics", Reliability Engineering and System Safety 115 pp. 70–81.