Wednesday , April 24 2024

Reliability Evaluation Based on a Fuzzy Expert System:
Centrifugal Pump Application

Belhadef RACHID1, Ahmed HAFAIFA2,
Nadji HADROUG2, Mohamed BOUMEHRAZ3
1 Faculty of Science and Technology, University of Jijel, Algeria
r.belhadef@univ-biskra.dz
2Applied Automation and Industrial Diagnostics Laboratory,
Faculty of Science and Technology, University of Djelfa
17000 DZ, Algeria
Hafaifa.ahmed.dz@ieee.org, N_Hadrzoug@univ-djelfa.d
3 University of Biskra, Algeria
medboumehraz@univ-biskra.dz

Abstract:  In the development process of modern industrial systems, predictive reliability becomes very important in the design and exploitation of industrial facilities. This paper proposes the development of a new approach to the assessment of predictive reliability, applied to a centrifugal pump based on a fuzzy expert system to improve its performance under actual operating conditions. The obtained results clearly demonstrate how the reproduction of the main dynamic characteristics of the examined pump, using the proposed fuzzy model enables better performance regarding reliability.

Keywords: Predictive reliability, reliability analyses, fuzzy system, fuzzy modelling, fuzzy expert system, centrifugal pump, safety system, industrial process.

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CITE THIS PAPER AS:
Belhadef RACHID, Ahmed HAFAIFA, Nadji HADROUG, Mohamed BOUMEHRAZ, Reliability Evaluation Based on a Fuzzy Expert System: Centrifugal Pump Application, Studies in Informatics and Control, ISSN 1220-1766, vol. 25(2), pp. 181-188, 2016. https://doi.org/10.24846/v25i2y201605

  1. Introduction

Reliability analysis is essential for ensuring dependability in industrial systems. Today, the technological evolution of industrial equipment has led to significant progress in the areas of quality and dependability to meet the needs of the user, particularly in the process of quality improvement that impacts the predicted reliability. Indeed, reliability has become a key quality and decision support parameter because reliability covers multiple aspects, such as failure analysis systems.

Several studies have been conducted to assess as accurately as possible the predictive reliability [1, 2, 3, 4, 5 and 6]. Many persistent problems exist in the field of predictive reliability, such as population samples, rates of non-constant failures, lengthy and expensive trials, missing data and other technical and practical problems. This work proposes a fuzzy model describing the predictive reliability of a centrifugal pump. This method of evaluation and reliability analysis is based on the field of artificial intelligence, specifically fuzzy expert systems, and offers advantageous performance in the modelling of the predicted reliability of the process considered.

In this work, through the various tests using real data, we clearly demonstrate that the obtained results using the proposed fuzzy model reproduce the main reliability features in the examined pump, allowing for the best performance when used for calculations of the failure rates of each component of the examined centrifugal pump.

REFERENCES

  1. BELHADEF, R., A. HAFAIFA, M. BOUMEHRAZ, Vibrations Detection in Industrial Pumps based on Spectral Analysis to Increase Their Efficiency, Management Systems in Production Engineering, 2016, vol. 1(21), pp. 55-61.
  2. CHATTERJEE, S., S. NIGAM J. b. SINGH, L. N. UPADHYAYA, Application of Fuzzy Time Series in Prediction of Time between Failures & Faults in Software Reliability Assessment, Fuzzy Information and Engineering, 3(3), 2011, pp. 293-309.
  3. COOLEN, F. P. A., P. COOLEN-SCHRIJNER, K. J. YAN, Nonparametric Predictive Inference in Reliability, Reliability Engineering & System Safety, 78(2), 2002, pp. 185-193.
  4. HALIMI, D., A. HAFAIFA, E. BOUALI, Maintenance Actions Planning in Industrial Centrifugal Compressor based on Failure Analysis, Maintenance and Reliability, vol. 16(1), 2014, pp. 17-21.
  5. SYOMIN, D., A. ROGOVYI, Features of a Working Process and Characteristics of Irrotational Centrifugal Pumps, Procedia Engineering, vol. 39, 2012, pp. 231-237.
  6. LI, F., G. ZHENG, Z. TIAN, Optimal Operation Strategy of the Hybrid Heating System Composed of Centrifugal Heat Pumps and Gas Boilers, Energy and Buildings, vol. 58, 2013, pp. 27-36.
  7. GUO, S.-X., Z.-Z. LÜ, Procedure for Computing the Possibility and Fuzzy Probability of Failure of Structures, Applied Mathematics and Mechanics, vol. 24(3), 2003, pp. 338-343.

  1. Hafaifa, A., A. Z. Djeddi, A. Daoudi, Fault Detection and Isolation in Industrial Control Valve based on Artificial Neural Networks Diagnosis, of Control Engineering and Applied Informatics, vol. 15(3), 2013, pp. 61-69.
  2. Hafaifa, A., r. Belhadef, m. Guemana, Reliability Model Exploitation in Industrial System Maintainability using Expert System Evaluation, of the 4th International Conference on Integrity, Reliability and Failure IRF201323-27 June 2013, Funchal, Madeira, Portugal. pp. 387-388.
  3. Hari Prasad M., a. Rami Reddy GSrividya., A. k. Verma, Reliability Estimation of Passive Systems using Fuzzy Fault Tree Approach. Intl. Journal of System Assurance Engineering and Management, vol. 3(3), 2012, pp. 237-245.
  4. Wu, h.-c., Bayesian System Reliability Assessment under Fuzzy Environments, Reliability Engineering & System Safety, vol. 83(3), 2004, pp. 277-286.
  5. Wu, H.-C., Fuzzy Bayesian Estimation on Lifetime Data, Computational Statistics, vol. 19(4), 2004, pp. 613-633.
  6. Černetič, j., M. Čudina, Estimating Uncertainty of Measurements for Cavitation Detection in a Centrifugal Pump, Measurement, vol. 44(7), 2011, pp. 1293-1299.
  7. Joe Askew, Centrifugal Pumps Avoiding Cavitation, World Pumps, vol. 2011(7–8), 2011, pp. 34-36, 38-39.
  8. Li, B., m. Zhu, K. Xu, A Practical Engineering Method for Fuzzy Reliability Analysis of Mechanical Structures, Reliability Eng. & System Safety, vol. 67(3), 2000, pp. 311-315.
  9. Marcello Braglia, Gionata Carmignani, Marco Frosolini, Francesco Zammori, Data Classification and MTBF Prediction with a Multivariate Analysis Approach, Reliability Engineering & System Safety, vol. 97(1), 2012, pp. 27-35.
  10. Maurizio Bevilacqua, Marcello Braglia, Roberto Montanari, The Classification and Regression Tree Approach to Pump Failure Rate Analysis, Reliability Engineering & System Safety, vol. 79(1), 2003, pp. 59-67.
  11. Myrto Konstandinidou, Zoe Nivolianitou, Chris Kiranoudis, Nikolaos Markatos, A Fuzzy Modeling Application of CREAM Methodology for Human Reliability Analysis, Reliability Eng. & System Safety, vol. 91(6), 2006, pp. 706-716.
  12. Olgierd Hryniewicz, An Evaluation of the Reliability of Complex Systems using Shadowed Sets and Fuzzy Lifetime Data, International Journal of Automation and Computing, vol. 3(2), 2006, pp. 145-150.
  13. Om Prakash Yadav, Nanua Singh, Ratna Babu Chinnam, Parveen S. Goel, A fuzzy logic based approach to reliability improvement estimation during product development . Reliability Engineering & System Safety, vol. 80(1), April 2003, Pages 63-74.
  14. Punit Singh, Franz Nestmann, An optimization routine on a prediction and selection model for the turbine operation of centrifugal pumps, Experimental Thermal and Fluid Science, vol. 34(2), 2010, pp. 152-164.
  15. Qimi Jiang, Chun-Hsien Chen, A numerical algorithm of fuzzy reliability, Reliability Engineering & System Safety, vol. 80(3), 2003, pp. 299-307.
  16. Rajiv Kumar Sharma, Dinesh Kumar, Pradeep Kumar, Modeling system behavior for risk and reliability analysis using KBARM, Quality and Reliability Engineering International, vol. 23(8), 2007, pp. 973–998.
  17. Ramin Gholizadeh, Aliakbar Mastani Shirazi, Bahram S. Gildeh, Eynollah Deiri, Fuzzy Bayesian system reliability assessment based on Pascal distribution, Structural and Multidisciplinary Optimization, vol. 40(1-6), 2010, pp. 467-475.
  18. Rotshtein A. P., Fuzzy-algorithmic reliability analysis of complex systems. Cybernetics and Systems Analysis, vol. 47(6), 2011, pp. 919-931.
  19. Rotshtein A. P., s. d. Shtovba, Modeling of the Human Operator Reliability with the Aid of the Sugeno Fuzzy Knowledge Base, and Remote Control, vol. 70(1), 2009, pp. 163-169.
  20. Rotshtein A. P., Shtovba S. D., Predicting the reliability of algorithmic processes with fuzzy input data, Cybernetics and Systems Analysis, vol. 34(4), 1998, pp. 545-552.
  21. Ryma Achouri, Omeima Nouicer, Hatem Mhiri, Philippe Bournot, Probable cause analysis of cracks observed on vertical centrifugal pump. Engineering Failure Analysis, Volume 29, April 2013, Pages 1-11.
  22. Subrata Chakraborty and Palash Chandra Sam, Probabilistic safety analysis of structures under hybrid uncertainty, International Journal for Numerical Methods in Engineering, vol. 70(4), 2007, pp. 405–422.
  23. Trinath Sahoo, Making centrifugal pumps more reliable, World Pumps, vol. 2009(513), 2009, pp. 32-36.
  24. Yu Ge Dong, Xin Zhao Chen, Hyun Deog Cho, Jong Wan Kwon, Simulation of Fuzzy reliability indexes, KSME International Journal, vol. 17(4), 2003, pp. 492-500.
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