Username   Password       Forgot your password?  Forgot your username? 


Residual Life Prediction of Long-Term Storage Products Considering Regular Inspection and Preventive Maintenance

Volume 14, Number 12, December 2018, pp. 2941-2950
DOI: 10.23940/ijpe.18.12.p4.29412950

Zhaoli Song, Qian Zhao, Zhijun Cheng, Xiwen Wu, Yong Yang, and Bo Guo

Department of Management, National University of Defence Technology, Changsha, 410072, China

(Submitted on September 12, 2018; Revised on October 17, 2018; Accepted on November 21, 2018)


Predicting the residual life of long-term storage products with regular inspection and preventive maintenance is of great significance nowadays. In this paper, a model of storage process that takes multi-stage degradation and preventive maintenance into consideration is established. Considering the amount of degradation of the product to follow the Wiener process, we put forward a method to predict the residual life of long-storage products based on the degradation model in a multi-stage storage process. Through a simulation method, five experiments are performed to calculate and compare the residual life in different situations. Finally, we find that the dramatic changes of environmental conditions during the inspection period influence the residual storage life observably. By simulation, this model is effective by making full use of data collected during storage time, including degradation amount and maintenance information.


References: 16

                    1. H. Y. Gao, F. J. Zuo, Z. Q. Lv, S. P. Zhu, and H. Z. Huang, “Residual Life Prediction based on Nonlinear Fatigue Damage Accumulation Model,” Journal of Shanghai Jiaotong University (Science), Vol. 20, No. 4, pp. 449-453, 2015
                    2. Y. Zhao, E. Zio, and G. Fu, “Remaining Storage Life Prediction for an Electromagnetic Relay by a Particle Filtering-based Method,” Microelectronics Reliability, Vol. 79, pp. 221-230, 2017
                    3. X. Zhang, S. W. Tang, T. Y. Liu, and B. C. Zhang, “A New Residual Life Prediction Method for Complex Systems based on Wiener Process and Evidential Reasoning,” Journal of Control Science and Engineering, Vol. 5, pp. 1-12, 2018
                    4. B. K. Guépié and S. Lecoeuche, “Similarity-based Residual Useful Life Prediction for Partially Unknown Cycle Varying Degradation,” in Proceedings of IEEE Conference on Prognostics and Health Management (PHM), pp. 1-7, 2015
                    5. J. Son, Q. Zhou, S. Zhou, X. Mao, and M. Salman, “Evaluation and Comparison of Mixed Effects Model based Prognosis for Hard Failure,” IEEE Transactions on Reliability, Vol. 62, No. 2, pp. 379-394, 2013
                    6. Y. J. Du, B. Zhang, and C. C. Zhang, “Maintenance of Storage Batteries in Automatic Meteorological Observation Stations,” Meteorological and Environmental Research, Vol. 4, No. 5-6, pp. 52-53, 2013
                    7. H. Cherkaoui, K. T. Huynh, and A. Grall, “Quantitative Assessments of Performance and Robustness of Maintenance Policies for Stochastically Deteriorating Production Systems,” International Journal of Production Research, Vol. 56, No. 3, pp. 1089-1108, 2018
                    8. H. R. Komijani, M. Shahin, M. B. Shahin, and A. Jabbarzadeh, “Condition-based Maintenance Considering Shock and Degradation Processes,” Decision Science Letters, Vol. 6, No. 2, pp. 151-164, 2017
                    9. M. Zhang, O. Gaudoin, and M. Xie, “Degradation-based Maintenance Decision Using Stochastic Filtering for Systems under Imperfect Maintenance,” European Journal of Operational Research, Vol. 245, No. 2, pp. 531-541, 2015
                    10. L. Yang, X. B. Ma, and Y. Zhao, “A Condition-based Maintenance Model for a Three-State System Subject to Degradation and Environmental Shocks,” Computers & Industrial Engineering, Vol. 105, pp. 210-222, 2017
                    11. M. Nourelfath, N. Nahas, M. Bendaya, and C. G. Soares, “Integrated Preventive Maintenance and Production Decisions for Imperfect Processes,” Reliability Engineering & System Safety, Vol. 148, pp. 21-31, 2016
                    12. H. Lee and H. C. Ji, “New Stochastic Models for Preventive Maintenance and Maintenance Optimization,” European Journal of Operational Research, Vol. 255, No. 1, pp. 80-90, 2016
                    13. C. Park and K. L. Tsui, “A Profile Monitoring of the Multi-Stage Process,” Quality Technology & Quantitative Management, pp. 1-17, 2018
                    14. J. F. Zheng, C. H. Hu, X. S. Si, and B. Lin, “Remaining Life Prediction of Stochastic Degradation Equipment Considering Incomplete Maintenance Impact,” Acta Electronica Sinica, Vol. 45, No. 7, pp. 1740-1749, 2017
                    15. Z. D. Sheng, Q. P. Hu, J. Liu, and D. Yu, “Residual Life Prediction for Complex Systems with Multi-Phase Degradation by ARMA-filtered Hidden Markov Model,” Quality Technology & Quantitative Management, pp. 1-17, 2017
                    16. X. S. Si, C. H. Hu, X. Y. Kong, and D. H. Zhou, “A Residual Storage Life Prediction Approach for Systems with Operation State Switches,” IEEE Transactions on Industrial Electronics, Vol. 61, No. 11, pp. 6304-6315, 2014


                                      Please note : You will need Adobe Acrobat viewer to view the full articles.Get Free Adobe Reader

                                      This site uses encryption for transmitting your passwords.