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Random preventive maintenance policy based on inspection for a multicomponent system using simulation

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Warianty tytułu
PL
Oparta na przeglądach polityka losowej konserwacji zapobiegawczej systemu wieloelementowego z wykorzystaniem symulacji
Języki publikacji
EN
Abstrakty
EN
In today's global situation where highly competitive companies demand production efficiently to reduce costs, increase product quality, and customer loyalty, maintenance becomes crucial to achieve this goal by reducing unplanned downtime, reworking of products, and costs. In this sense, the use of models that can represent this type of system, and help managers make decisions more easily, are of vital importance for companies. Thus, a preventive maintenance model for a multicomponent system with different failure mechanisms is proposed in this work. Considering that the objective is to optimize the number and the time of maintenance interventions, that will be done in the system, periodic inspections are carried out in order to minimize the expected costs of maintenance. The optimization was performed with simulation, which proved to be satisfactory, since the decision variables of the model behaved adequately when utilized within the context of an applied case study. In addition, these variables had different performances when analyzed in four different scenarios: the original model of the proposed policy, and three variations attributing costs of penalties.
PL
W dzisiejszej sytuacji globalnej, w której przedsiębiorstwa o wysokim stopniu konkurencyjności wymagają efektywnego obniżania kosztów produkcji, poprawy jakości produktów oraz zwiększania lojalności klientów, konserwacja ma zasadnicze znaczenie dla osiągnięcia tych celów poprzez redukcję nieplanowanych przestojów, oraz zmniejszenie konieczności usuwania usterek produktów a także obniżanie kosztów. W tym sensie, wykorzystanie modeli reprezentujących tego typu systemy i ułatwiające menedżerom podejmowanie decyzji , ma kluczowe znaczenie dla firm. W tej pracy zaproponowano model konserwacji zapobiegawczej dla wieloelementowego systemu o różnych mechanizmach uszkodzeń. Biorąc pod uwagę, że celem jest optymalizacja liczby i czasu trwania zabiegów konserwacyjnych dokonywanych w systemie, przeprowadzane są okresowe przeglądy mające na celu zminimalizowanie oczekiwanych kosztów utrzymania. Optymalizację przeprowadzono za pomocą symulacji, która okazała się zadowalająca, ponieważ zmienne decyzyjne modelu zachowywały się odpowiednio przy wykorzystaniu ich w kontekście omawianego studium przypadku. Dodatkowo, zmienne te przybierały różne wartości dla czterech różnych scenariuszy: pierwotnego modelu proponowanej polityki konserwacyjnej i trzech wariantów, w których uwzględniono koszty pracy systemu w stanie awaryjnym.
Rocznik
Strony
552--559
Opis fizyczny
Bibliogr. 30 poz., rys., tab.
Twórcy
  • Department of Mechanical and Production Engineering State University of Maranhão – UeMA University City Paulo VI – post office box 09, São Luís – MA – Brazil – Zip Code: 65055-970
  • Department of Production Engineering Federal University of Pernambuco – UFPe Professor Moraes rego Avenue, 1235 – University City, recife – Pe – Brazil – Zip Code: 50670-901
Bibliografia
  • 1. Alaswad S, Xiang Y. A review on condition-based maintenance optimization models for stochastically deteriorating system. Reliability Engineering & System Safety 2017; 157: 54-63, https://doi.org/10.1016/j.ress.2016.08.009.
  • 2. Alrabghi A, Tiwari A. State of the art in simulation-based optimisation for maintenance systems. Computers & Industrial Engineering 2015; 82: 167-182, https://doi.org/10.1016/j.cie.2014.12.022.
  • 3. Alrabghi A, Tiwari A. A novel approach for modelling complex maintenance systems using discrete event simulation. Reliability Engineering & System Safety 2016; 154: 160-170, https://doi.org/10.1016/j.ress.2016.06.003.
  • 4. Babishin V, Taghipour S. Optimal maintenance policy for multicomponent systems with periodic and opportunistic inspections and preventive replacements. Applied Mathematical Modelling 2016; 40: 10480-10505, https://doi.org/10.1016/j.apm.2016.07.019.
  • 5. Chen N, Ye Z-S, Xiang Y, Zhang L. Condition-based maintenance using the inverse Gaussian degradation model. European Journal of Operational Research 2015; 243:190-199, https://doi.org/10.1016/j.ejor.2014.11.029.
  • 6. Chung C A. Simulation modelling handbook: a practical approach. United States of America: CRC Press LLC, 2004.
  • 7. Dao C D, Zuo M. J. Selective maintenance of multi-state systems with structural dependence. Reliability Engineering & System Safety 2017; 159: 184-195, https://doi.org/10.1016/j.ress.2016.11.013.
  • 8. Darghouth M N, Chelbi C, Ait-kadi D. A profit assessment model for equipment inspection and replacement under renewing free replacement warranty policy. International Journal of Production Economics, 2012; 135: 899-906, https://doi.org/10.1016/j.ijpe.2011.10.029.
  • 9. Dieulle L, Bérenguer C, Grall A, Roussignol M. Sequential condition-based maintenance scheduling for a deteriorating system. European Journal of Operational Research 2003: 150: 451-461, https://doi.org/10.1016/S0377-2217(02)00593-3.
  • 10. Ding S-H, Kamaruddin S. Maintenance policy optimization—literature review and directions. International Journal of Advanced Manufacturing Technology 2015; 76:1743-1756, https://doi.org/10.1007/s00170-014-6341-2.
  • 11. Duffua S O, Ben-Day M, Al-Sultan K S, Andijani A A. A generic conceptual simulation model for maintenance system. Journal of Quality in Maintenance Engineering 2001; 7: 207-219, https://doi.org/10.1108/13552510110404512.
  • 12. Geng J, Azarian M, Pecht M. Opportunistic maintenance for multi-component systems considering structural dependence and economic dependence. Journal of Systems Engineering and Electronics 2015; 26: 493-501, https://doi.org/10.1109/JSEE.2015.00057.
  • 13. Golmakani H R, Moakedi H, Optimal nonperiodic inspection scheme for a multicomponent repairable system with failure interaction using A* search algorithm. International Journal of Advanced Manufacturing Technology 2013; 67: 1325-1336, https://doi.org/10.1007/s00170012-4569-2.
  • 14. Jardine A T J, Banjevic D. Optimizing condition-based maintenance decisions for equipment subject to vibration monitoring. Journal of Quality in Maintenance Engineering 1999; 5: 192-202, https://doi.org/10.1108/13552519910282647.
  • 15. Laggoune R, Chateauneuf B, Aissania D. Opportunistic policy for optimal preventive maintenance of a multi-component system in continuous operating units. Computers & Chemical Engineering 2009; 33: 1499-1510, https://doi.org/10.1016/j.compchemeng.2009.03.003.
  • 16. Lam J Y J, Banjevic D. A myopic policy for optimal inspection scheduling for condition based maintenance. Reliability Engineering & System Safety 2015; 144: 1-11, https://doi.org/10.1016/j.ress.2015.06.009.
  • 17. Nourelfath M, Nahas M, Ben-Daya M. Integrated preventive maintenance and production decisions for imperfect processes. Reliability Engineering & System Safety 2016; 148: 21-31, https://doi.org/10.1016/j.ress.2015.11.015.
  • 18. Rezg N, Chelbi A, Xie X-L. Modelling and optimizing a joint buffer inventory and preventive maintenance strategy for a randomly failing production unit: analytical and simulation approaches. International Journal of Computer integrated Manufacturing 2005, 18: 225-235, https://doi.org/10.1080/0951192052000288152.
  • 19. Sahraoui Y, Khelif R, Chateauneuf A. Maintenance planning under imperfect inspections of corroded pipelines. International Journal of Pressure Vessels and Piping 2013; 104: 76-82. https://doi.org/10.1016/j.ijpvp.2013.01.009.
  • 20. Scarf P A, Cavalcante C A V. Modelling quality in replacement and inspection maintenance. International Journal of Production Economics 2012; 135: 371-381, https://doi.org/10.1016/j.ijpe.2011.08.011.
  • 21. Scarf P A, Cavalcante C A V, Dwight R A, Gordon P. An Age-Based Inspection and Replacement Policy for Heterogeneous Components. IEEE Transactions on reliability 2009; 58: 641-648, https://doi.org/10.1109/TR.2009.2026796.
  • 22. Taghipour S, Banjevic D. Periodic Inspection Optimization Models for a Repairable System Subject to Hidden Failures. IEEE Transactions on Reliability 2011; 60: 275-285, https://doi.org/10.1109/TR.2010.2103596.
  • 23. Thomas L C. A Survey of Maintenance and Replacement Models for Maintainability and Reliability of Multi-Item Systems. Reliability Engineering 1986; 16: 297-309, https://doi.org/10.1016/0143-8174(86)90099-5.
  • 24. Yang L, Ma X, Zhai Q, Zhao Y. A delay time model for a mission-based system subject to periodic and random inspection and postponed replacement. Reliability Engineering & System Safety 2016; 150: 96-104, https://doi.org/10.1016/j.ress.2016.01.016.
  • 25. Yan H-C, Zhou J-H, Pang C K. Machinery Degradation Inspection and Maintenance Using a Cost-Optimal Non-Fixed Periodic Strategy. IEEE Transactions on Instrumentation and Measurement 2016; 65: 2067-2077, https://doi.org/10.1109/TIM.2016.2563998.
  • 26. Zhang J, Huang X, Fang Y, Zhou J, Zhang H, Li J. Optimal inspection-based preventive maintenance policy for three-state mechanical components under competing failure modes. Reliability Engineering & System Safety 2016; 152: 95-103, https://doi.org/10.1016/j. ress.2016.02.007.
  • 27. Zhang X, Zeng J. A general modelling method for opportunistic maintenance modelling of multi-unit systems. Reliability Engineering & System Safety 2015; 140: 176-190, https://doi.org/10.1016/j.ress.2015.03.030.
  • 28. Zhao L, Chen M, Zhou D. General (N, T, τ) Opportunistic Maintenance for Multicomponent Systems With Evident and Hidden Failures. IEEE Transactions on Reliability 2016; 65: 1298-1313, https://doi.org/10.1109/TR.2016.2570547.
  • 29. Zhao X, Al-Khalifa K N, Nakagaw T. Approximate methods for optimal replacement, maintenance, and inspection policies. Reliability Engineering & System Safety 2015; 144: 68-73, https://doi.org/10.1016/j.ress.2015.07.005.
  • 30. Zhu W, Fouladirad M, Bérenguer C. Condition-based maintenance policies for a combined wear and shock deterioration model with covariates. Computers & Industrial Engineering 2015; 85:268-283, https://doi.org/10.1016/j.cie.2015.04.005.97–2800.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-b14850bf-4de2-44b5-8135-0e1180a6d075
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