بررسی اثر ترکیبی تخصیص افزونگی و وابستگی تصادفی در مدل نگه‌داری و تعمیرات مبتنی بر شرایط در سیستم‌های سری- موازی با در نظر‌گرفتن اشتراک بار

نوع مقاله : مقاله پژوهشی

نویسندگان

1 گروه مهندسی صنایع، واحد تهران شمال، دانشگاه آزاد اسلامی، تهران، ایران.

2 گروه مهندسی صنایع، دانشگاه صنعتی خواجه نصیرالدین طوسی، تهران، ایران.

چکیده
هدف: این مقاله به‌منظور ارایه مدلی نوآورانه برای بهینه‌سازی هم‌زمان تخصیص افزونگی و تعمیر و نگه‌داری مبتنی بر شرایط در سیستم‌های سری-موازی با اشتراک بار طراحی‌شده است. هدف اصلی مدل، تعیین سطح بهینه افزونگی به‌گونه‌ای است که هم هزینه‌ها کاهش یابد و هم محدودیت‌های قابلیت اطمینان سیستم رعایت شود.
روش‌شناسی پژوهش: در این پژوهش، وابستگی‌های تصادفی بین اجزای سیستم با استفاده از مدل مخاطره متناسب و نرخ خرابی دستکاری‌شده در نظر گرفته شده‌اند تا قابلیت اطمینان به‌طور دقیق ارزیابی گردد. علاوه بر این، با استفاده از ماتریس‌های احتمال انتقال، حد کنترل بهینه برای نگه‌داری هر زیرسیستم تعیین‌شده و سیستم به‌طور دوره‌ای بازرسی می‌شود. مدل پیشنهادی با نرم‌افزار مطلب حل‌شده و عملکرد آن در چهار سناریو مختلف موردبررسی قرارگرفته است: ۱- مدل پایه بدون تخصیص افزونگی و وابستگی تصادفی، ۲- تخصیص افزونگی بدون وابستگی تصادفی، ۳- وابستگی تصادفی بدون افزونگی و ۴- مدل پیشنهادی.
یافته‌ها: نتایج نشان می‌دهند که مدل پیشنهادی تعادلی بهینه بین هزینه‌ها و قابلیت اطمینان برقرار کرده و هزینه‌های خرابی و نگه‌داری را کاهش داده است. در مقایسه با سناریوهای مختلف، مدل پیشنهادی عملکرد بهتری در بهینه‌سازی هزینه‌ها و افزایش قابلیت اطمینان نشان داده است. یافته‌ها هم‌چنین بر اهمیت هم‌زمان در نظر‌گرفتن وابستگی‌های تصادفی و تخصیص افزونگی برای بهبود عملکرد سیستم تاکید دارند.
اصالت/ارزش‌افزوده علمی: این تحقیق برای نخستین بار مدلی را ارایه می‌دهد که وابستگی‌های تصادفی و تخصیص افزونگی را به‌صورت هم‌زمان در سیستم‌های سری-موازی با اشتراک بار موردبررسی قرار می‌دهد. این مدل به‌طور قابل‌توجهی به‌بهبود عملکرد سیستم و کاهش هزینه‌های خرابی و نگه‌داری کمک می‌کند و بر اهمیت در نظر‌گرفتن هم‌زمان این دو عامل در بهینه‌سازی سیستم‌های مهندسی پیچیده تاکید دارد.

کلیدواژه‌ها


عنوان مقاله English

Investigating the combined effect of redundancy allocation and stochastic dependency in condition-based maintenance model in series-parallel systems considering load sharing

نویسندگان English

Saba Nasersarraf 1
Shervin Asadzadeh 1
Yaser Samimi 2
1 Department of Industrial Engineering, North Tehran Branch, Islamic Azad University, Tehran, Iran.
2 Department of Industrial Engineering, Khajeh Nasiruddin Toosi University of Technology, Tehran, Iran.
چکیده English

Purpose: This paper presents an innovative model for the simultaneous optimization of redundancy allocation and condition-based maintenance in series-parallel load-sharing systems. The primary objective of the model is to determine the optimal level of redundancy so that costs are minimized while system reliability constraints are met.
Methodology: In this research, stochastic dependencies between system components are considered using the proportional hazards model and tempered failure rates to assess reliability accurately. Additionally, transition probability matrices are used to determine the optimal maintenance limits for each subsystem, and periodic inspections are performed. The proposed model is solved using MATLAB, and its performance is evaluated under four different scenarios: 1) a baseline model without redundancy or stochastic dependencies, 2) redundancy allocation without stochastic dependencies, 3) stochastic dependencies without redundancy, and 4) the proposed model.
Findings: The results show that the proposed model achieves an optimal balance between cost and reliability, reducing both failure and maintenance costs. Compared to the various scenarios, the proposed model demonstrates superior performance in optimizing costs and enhancing reliability. The findings also emphasize the importance of simultaneously considering stochastic dependencies and redundancy allocation to improve system performance.
Originality/Value: This research introduces a novel approach by simultaneously considering stochastic dependencies and redundancy allocation in series-parallel load-sharing systems. The proposed model significantly improves system performance and reduces failure and maintenance costs. It underscores the importance of integrating these two factors in optimizing complex engineering systems.

کلیدواژه‌ها English

Redundancy allocation
Condition-based maintenance
Series-parallel system
Reliability
Proportional hazards model
[1]     Jardine, A. K. S., Lin, D., & Banjevic, D. (2006). A review on machinery diagnostics and prognostics implementing condition-based maintenance. Mechanical systems and signal processing, 20(7), 1483–1510. https://doi.org/10.1016/j.ymssp.2005.09.012
[2]     Banjevic, D., Jardine, A. K. S., Makis, V., & Ennis, M. (2001). A control-limit policy and software for condition-based maintenance optimization. INFOR: Information systems and operational research, 39(1), 32–50. https://doi.org/10.1080/03155986.2001.11732424
[3]     Zhao, X., Liu, B., & Liu, Y. (2018). Reliability modeling and analysis of load-sharing systems with continuously degrading components. IEEE transactions on reliability, 67(3), 1096–1110. https://doi.org/10.1109/TR.2018.2846649
[4]     Dixit, Y., & Kulkarni, M. S. (2024). Simulation based approach for reliability and remaining useful life estimation of spur gear pair under non-Markov and non-stationary load transitions. Computers & industrial engineering, 190, 110026. https://doi.org/10.1016/j.cie.2024.110026
[5]     Amari, S. V, Misra, K. B., & Pham, H. (2006). Reliability analysis of tampered failure rate load-sharing k-out-of-n: g systems. Proc. 12th issat int. conf. on reliability and quality in design, honolulu, hawaii (pp. 30–35). Researchgate.net. https://B2n.ir/bk2972
[6]     Suprasad, A. V, Krishna, M. B., & Hoang, P. (2008). Tampered failure rate load-sharing systems: Status and perspectives. In Handbook of performability engineering (pp. 291–308). Springer.  https://doi.org/10.1007/978-1-84800-131-2_20
[7]     Mohammad, R., Kalam, A., & Amari, S. V. (2013). Reliability of load-sharing systems subject to proportional hazards model. 2013 proceedings annual reliability and maintainability symposium (RAMS) (pp. 1–5). IEEE.  https://doi.org/10.1109/RAMS.2013.6517708
[8]     de Smidt-Destombes, K. S., van der Heijden, M. C., & van Harten, A. (2004). On the availability of a k-out-of-N system given limited spares and repair capacity under a condition based maintenance strategy. Reliability engineering & system safety, 83(3), 287–300. https://doi.org/10.1016/j.ress.2003.10.004
[9]     Ghasemi, A., Yacout, S., & Ouali, M. S. (2007). Optimal condition based maintenance with imperfect information and the proportional hazards model. International journal of production research, 45(4), 989–1012. https://doi.org/10.1080/00207540600596882
[10]   Keizer, M. C. A. O., Teunter, R. H., & Veldman, J. (2017). Joint condition-based maintenance and inventory optimization for systems with multiple components. European journal of operational research, 257(1), 209–222. https://doi.org/10.1016/j.ejor.2016.07.047
[11]   Keizer, M. C. A. O., Teunter, R. H., Veldman, J., & Babai, M. Z. (2018). Condition-based maintenance for systems with economic dependence and load sharing. International journal of production economics, 195, 319–327. https://doi.org/10.1016/j.ijpe.2017.10.030
[12]   Yahyatabar, A., & Najafi, A. A. (2018). Condition based maintenance policy for series-parallel systems through Proportional Hazards Model: A multi-stage stochastic programming approach. Computers & industrial engineering, 126, 30–46. https://doi.org/10.1016/j.cie.2018.09.014
[13]   Zhang, N., Fouladirad, M., Barros, A., & Zhang, J. (2020). Condition-based maintenance for a K-out-of-N deteriorating system under periodic inspection with failure dependence. European journal of operational research, 287(1), 159–167. https://doi.org/10.1016/j.ejor.2020.04.041
[14]   Coit, D. W., & Smith, A. E. (1996). Reliability optimization of series-parallel systems using a genetic algorithm. IEEE transactions on reliability, 45(2), 254–260. https://doi.org/10.1109/24.510811
[15]   Kuo, W. (2001). Optimal reliability design: Fundamentals and applications (2nd Ed.). Cambridge university press. https://B2n.ir/qw6862
[16]   Ramirez-Marquez, J. E., & Coit, D. W. (2004). A heuristic for solving the redundancy allocation problem for multi-state series-parallel systems. Reliability engineering & system safety, 83(3), 341–349. https://doi.org/10.1016/j.ress.2003.10.010
[17]   Coit, D. W., & Liu, J. C. (2000). System reliability optimization with k-out-of-n subsystems. International journal of reliability, quality and safety engineering, 7(02), 129–142. https://doi.org/10.1142/S0218539300000110
[18]   Liang, Y. C., & Lo, M. H. (2010). Multi-objective redundancy allocation optimization using a variable neighborhood search algorithm. Journal of heuristics, 16, 511–535. https://doi.org/10.1007/s10732-009-9108-4
[19]   Kayedpour, F., Amiri, M., Rafizadeh, M., Nia, A. S., & Sharifi, M. (2024). A Markov chain-based genetic algorithm for solving a redundancy allocation problem for a system with repairable warm standby components. Proceedings of the institution of mechanical engineers, part o: journal of risk and reliability, 238(4), 853–872. https://doi.org/10.1177/1748006X231164848
[20]   Kumar, U. D., Crocker, J., Knezevic, J., & El-Haram, M. (2012). Reliability, maintenance and logistic support: A life cycle approach. Springer Science & Business Media. https://doi.org/10.1007/978-1-4615-4655-9
[21]   Jin, T., Si, S., & Zhu, W. (2024). Allocating redundancy, maintenance and spare parts for minimizing system cost under decentralized repairs. Frontiers of engineering management, 11(3), 377–395. https://doi.org/10.1007/s42524-024-0145-3
[22]   Belzunce, F., Martínez-Puertas, H., & Ruiz, J. M. (2013). On allocation of redundant components for systems with dependent components. European journal of operational research, 230(3), 573–580. https://doi.org/10.1016/j.ejor.2013.05.004
[23]   Sharifi, M., Taghipour, S., & Abhari, A. (2021). Inspection interval optimization for a k-out-of-n load sharing system under a hybrid mixed redundancy strategy. Reliability engineering & system safety, 213, 107681. https://doi.org/10.1016/j.ress.2021.107681
[24]   Amiri, M., Sadeghi, M. R., Khatami, F. A. L. I., & Mikaeili, F. (2014). A multi objective optimization model for redundancy allocation problems in series-parallel systems with repairable componenets, 25(1), 71–81. http://ijiepr.iust.ac.ir/
[25]   Makis, V., & Jardine, A. K. S. (1992). Optimal replacement in the proportional hazards model. INFOR: Information systems and operational research, 30(1), 172–183. https://doi.org/10.1080/03155986.1992.11732183
[26]   Bhattacharyya, G. K., & Soejoeti, Z. (1989). A tampered failure rate model for step-stress accelerated life test. Communications in statistics-theory and methods, 18(5), 1627–1643. https://doi.org/10.1080/03610928908829990
[27]   Scheuer, E. M. (1988). Reliability of an m-out of-n system when component failure induces higher failure rates in survivors. IEEE transactions on reliability, 37(1), 73–74. https://doi.org/10.1109/24.3717
[28]   Reza Golmakani, H., & Fattahipour, F. (2011). Age-based inspection scheme for condition-based maintenance. Journal of quality in maintenance engineering, 17(1), 93–110. https://doi.org/10.1108/13552511111116277
[29]   Madi, M. T. (1993). Multiple step-stress accelerated life test: the tampered failure rate model. Communications in statistics--theory and methods, 22(9), 295–306.
[30]   Lam, J. Y. J., & Banjevic, D. (2015). A myopic policy for optimal inspection scheduling for condition based maintenance. Reliability engineering & system safety, 144, 1–11. https://doi.org/10.1016/j.ress.2015.06.009
[31]   Nasersarraf, S., Asadzadeh, S., & Samimi, Y. (2025). Control limits’ optimization for multi-component systems in condition-based maintenance incorporating stochastic dependencies among system components. OPSEARCH, 1–36. https://doi.org/10.1007/s12597-025-00906-0
[32]   Krivtsov, V., Amari, S., & Gurevich, V. (2018). Load sharing in series configuration. Quality and reliability engineering international, 34(1), 15–26. https://doi.org/10.1002/qre.2230
[33]   Lawless, J. F. (2011). Statistical models and methods for lifetime data. John Wiley & Sons. https://B2n.ir/bt8383
[34]   Birge, J. R., & Louveaux, F. (2011). Introduction to stochastic programming. Springer Science & Business Media. https://B2n.ir/jw2707