ABSTRACT
This study investigated the availability of centrifugal pumps in Afam VI Gas Plant, using lognormal distribution. The lognormal distribution as a more effective and tested means of determining the appropriate time for maintenance or parts replacement was used in this study to establish a maintenance technique that will minimize system downtime, forecast maintenance requirements and reduce maintenance cost and time. The lognormal distribution parameters were obtained from the probability plot in Minitab software. The value for scale parameter obtained as 7.618 gives an idea of the scale on the horizontal axis; the shape parameter was 0.4324, and the total number of technical systems was 20. The Weibull shape parameter was 2.802 which imply that failure rate is increasing with time. The scale parameter was 2485 which gives the idea of the scale on the horizontal axis. The probability value (p-value) of the distributions are greater than 0.05, this concludes that the data followed both lognormal and Weibull distributions. The study proved that lognormal distribution is more reliable than the Weibull distribution between 200 hours and 2600 hours. The decrease in reliability with increase in time could be as a result of friction and wear of the engineering members of the pump, which was not appropriate by the operating environment. The availability of the technical system at 2600 hours with lognormal distribution was observed to be 0.7, while that of Weibull was 0.6. It was observed that the availability of the system with both lognormal and Weibull distributions decreased with increase in time. Hence, lognormal distribution can be used to estimate the availability of the centrifugal pump and other engineering systems with parts or components that fail primarily due to stress, corrosion or fatigue.
References
[1] J. Barabady, Reliability and maintainability analysis of crushing plants in jajarm bauxite mine of Iran. Proceedings of Reliability and Maintainability Symposium, IEEE, New York, NY (2015) 109-115
[2] D.R Dolas, M.D Jaybhaye, S.D Deshmukh, Estimation of the system reliability using weibull distribution. IPEDR 75 (29) (2017) 43-50
[3] M. Khan, Modified inverse rayleigh distribution. Journal of Statistics Applications and Probability 2(5) (2015) 115-132
[4] J. Mi, Interval estimation of availability of a series system, IEEE Transaction on Reliability, 40 (5) (2016) 541-546
[5] M. Muhammad, M.A.A. Majid, N.A. Ibrahim, Reliability assessment for centrifugal pumps in a petrochemical plant. Engineering Asset Lifecycle Management Springer London, 3(4) (2016) 398-404
[6] K.S. Mohammed, J.J. Artur, M.A. German, The log-normal modified weibull distribution and its reliability implications. Reliability Engineering and System Safety, 18(8) (2019) 6–22
[7] A. Rosin, M. Hecht, J. Handal, Analysis of airport-runway availability. Proceedings of Annual Reliability and Maintainability Symposium, IEEE, New York, NY (2017) 432-40.
[8] A. Sandberg and U. Stromberg, Gripen: with focus on availability performance and life support cost over the product life cycle. Journal of Quality in Maintenance Engineering, 5(4) (2018) 325-334
[9] J. Selvakumar and K. Natarajan, Failure Analysis of Centrifugal Pumps Based on Survey. Journal of Engineering and Applied Sciences, 10(4) (2015) 86-92
[10] A. Sericola, Interval-availability distribution of 2-state systems with exponential failures and phase-type repairs, IEEE Transaction on Reliability, 43(2) (2019) 335-343
[11] H.F.Yu, The effect of mis-specification between the lognormal and weibull distributions on the interval estimation of a quantile for complete data. Communications in Statistics – Theory and Method, 41(9) (2015) 1617-1635
[12] Le, K. (2016). A Double-event Testing Approach to Improve Network-element Availability. Proceedings of Annual Reliability and Maintainability Symposium, IEEE, New York, NY, 334-8
[13] Li, J., & He, J. (2018). A Recursive Decomposition Algorithm for Network Seismic Reliability Evaluation. Earthquake Engineering and Structural Dynamics, 31, 1525-1539
[14] Liu, W., & Li, J. (2019). An Improved Recursive Decomposition Algorithm for Reliability Evaluation of Lifeline Networks. Earthquake Engineering and Engineering Vibration 8(3):409-419
[15] Mahesh, N. D., Mariappan, V., Srividhya, P.K., & Kurtikar, V. (2018). Multi-state Failure Phenomenon and Analysis using Semi-Markov model, International Journal of Quality & Reliability Management, 35(9), 2080-2091
[16] Marathe, R.R., & Ryan, S.M. (2018). On the validity of the geometric Brownian motion assumption. The Engineering Economist, 50(2), 159-167
[17] Marseguerra, M., Zio, E., & Podofillini, L. (2018). Optimal Reliability/Availability of Uncertain Systems via Multi-objective Genetic Algorithms. IEEE Transaction on Reliability, 53(3), 424-34
[18] McFadden, R.H. (2017). Developing a database for a reliability availability and maintainability improvement program for an industrial plant or commercial building, IEEE Transaction on Industry Applications, 26(4), 735-40
[19] Mohammed, K. S., Artur J. L &German, M.A. (2019) The Log-normal Modified Weibull Distribution and its Reliability Implications. Reliability Engineering and System Safety, 18(8), 6-22
[20] Nkemnole, E. B., & Samiyu, M. A. (2017). Inference on Stress-Strength Reliability for Log-Normal Distribution based on Lower Record Values. AMSE JOURNALS – AMSE IIETA, 22(1), 77-97
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