Development and sensitivity analysis of a technical object inspection model based on the delay-time concept use

• Autorzy: Jodejko-Pietruczuk A. , Werbińska-Wojciechowska S.

Identyfikatory

DOI

10.17531/ein.2017.3.11

Warianty tytułu

PL

Opracowanie i analiza wrażliwości modelu kontroli stanu obiektu technicznego z wykorzystaniem koncepcji opóźnień czasowych

• Języki publikacji: EN PL

Abstrakty

EN

n the presented paper, authors focus on the development of mathematical delay-time model for single-unit technical systems (technical objects) liable to costly failure. Failure is taken here to mean a breakdown or catastrophic event, after which the system is unusable until replacement. Implemented maintenance policy is the Block-Inspection Policy that assumes performing inspection actions at regular time intervals of T. In the perfect inspection case the availability and cost models are developed. This gives the possibility for analytical optimization of time between maintenance actions performance T for the infinite operational time of the system. Later, there is examined the compatibility of the developed analytical model with simulation results. The main target is to investigate what is the influence of the given model basic time components on the system availability ratio level and the system long-run expected maintenance costs. The analysis is conducted in the two main steps. The first one regards to analysis of expected number of events (failures, preventive replacements and inspection actions) in a single renewal cycle for the chosen range of time parameters: T and delay time h. In the next step, the availability ratio and long-run maintenance costs dependency on the chosen model’s time parameters is under consideration. At the end, the directions for further research work are defined.

PL

W artykule autorzy skupili się na opracowaniu matematycznego modelu utrzymania obiektów technicznych podlegających kosztownym uszkodzeniom z uwzględnieniem koncepcji opóźnień czasowych. Uszkodzenie w danym przypadku oznacza awarię lub zdarzenie katastrofalne, po którym obiekt jest niezdatny do użytku do momentu wymiany. Wykorzystano politykę blokowej kontroli stanu obiektu, która zakłada, że operacje diagnozy jego stanu są przeprowadzane w regularnych odstępach co T jednostek czasu. Rozpatrzono model kosztowy oraz model gotowości dla przypadku perfekcyjnej diagnozy stanu obiektu. Pozwoliło to na przeprowadzenie analitycznej optymalizacji okresu T między kolejnymi diagnozami stanu obiektu dla nieskończonego horyzontu czasowego. Następnie, zbadano zgodność opracowanego modelu analitycznego z wynikami uzyskanymi w drodze symulacji. Głównym celem było zbadanie wpływu podstawowych parametrów czasowych opracowanego modelu na poziom współczynnika gotowości oraz oczekiwanych kosztów utrzymania badanego obiektu. Analiza została przeprowadzona w dwóch etapach. Pierwszy obejmuje analizę oczekiwanej liczby zdarzeń (uszkodzeń, wymian profilaktycznych oraz operacji kontroli stanu obiektu) dla wybranych zakresów parametrów czasowych: T i opóźnienia czasowego h. W kolejnym kroku zbadano zależność wskaźnika gotowości i oczekiwanych kosztów utrzymania obiektu od wybranych parametrów czasowych modelu. Pracę kończy wskazanie kierunków dalszych prac badawczych.

Słowa kluczowe

EN

delay time; block-based maintenance; inspection

PL

opóźnienie czasowe; obsługi blokowe; diagnozowanie stanu obiektu

• Wydawca: Polskie Naukowo-Techniczne Towarzystwo Eksploatacyjne
• Czasopismo: Eksploatacja i Niezawodność
• Rocznik: 2017
• Tom: Vol. 19, no. 3
• Strony: 403--412
• Opis fizyczny: Bibliogr. 43 poz., rys.

Twórcy

autor

Jodejko-Pietruczuk A.

• Faculty of Mechanical Engineering Department of Operation and Maintenance of Logistic Systems, Transportation Systems and Hydraulic Systems Wroclaw University of Science and Technology ul. Wybrzeze Wyspianskiego 27, 50-370, Wroclaw, Poland

autor

Werbińska-Wojciechowska S.

• Faculty of Mechanical Engineering Department of Operation and Maintenance of Logistic Systems, Transportation Systems and Hydraulic Systems Wroclaw University of Science and Technology ul. Wybrzeze Wyspianskiego 27, 50-370, Wroclaw, Poland

Bibliografia

• 1. Attia A. F. Estimation of the reliability function using the delay-time models. Microelectronics Reliability 1997; 37(2): 323-327.
• 2. Babiarz B. An introduction to the assessment of reliability of the heat supply systems. International Journal of Pressure Vessels and Piping 2006; 83(4): 230-235.
• 3. Bajda A., WraŜeń M., Laskowski D. Diagnostics the quality of data transfer in the management of crisis situation. Electrical Review 2011; 87(9A): 72-78.
• 4. Baker R. D., Wang W. Estimating the delay-time distribution of faults in repairable machinery from failure data. IMA Journal of Mathematics Applied in Business & Industry 1992; 3: 259-281.
• 5. Cavalcante C. A. V., Scarf P. A., de Almeida A. T. A study of a two-phase inspection policy for a preparedness system with a defective state and heterogeneous lifetime. Reliability Engineering and System Safety 2011; 96: 627-635.
• 6. Cerone P. On a simplified delay time model of reliability of equipment subject to inspection monitoring. Journal of the Operational Research Society 1991; 42(6): 505511.
• 7. Christer A. H. A Review of Delay Time Analysis for Modelling Plant Maintenance. in: Stochastic Models in Reliability and Maintenance, Osaki S. (ed.), Springer, 2002.
• 8. Christer A H. Developments in delay time analysis for modelling plant maintenance. Journal of the Operational Research Society 1999; 50: 1120-1137.
• 9. Christer A. H. Delay-time model of reliability of equipment subject to inspection monitoring. Journal of the Operational Research Society 1987; 38(4): 329-334.
• 10. Christer A. H. Modelling inspection policies for building maintenance. Journal of the Operational Research Society 1982; 33: 723-732.
• 11. Christer A. H., Waller W. M. A Descriptive model of capital plant replacement. Journal of the Operational Research Society 1987; 8(6): 473-477.
• 12. Christer A. H., Waller W. M. Reducing production downtime using delay-time analysis. Journal of the Operational Research Society 1984; 35(6): 499-512.
• 13. Christer A. H., Waller W. M. Delay Time Models of Industrial Inspection Maintenance Problems. Journal of the Operational Research Society 1984; 35(5): 401406.
• 14. Christer A. H., Wang W. A model of condition monitoring of a production plant. International Journal of Production Research 1992; 30(9): 2199-2211.
• 15. Christer A.H., Wang W., Choi K., Van der Duyn Schouten F. A. The robustness of the semi-Markov and delay time single-component inspection models to the Markov assumption. IMA Journal of Management Mathematics 2001; 12: 75-88.
• 16. Dekker R., Scarf P. A. On the impact of optimisation models in maintenance decision making: the state of the art. Reliability Engineering and Safety 1998; 60: 111-119.
• 17. Frostig E. Comparison of maintenance policies with monotone failure rate distributions. Applied Stochastic Models in Business and Industry 2003; 19: 51-65.
• 18. Jodejko-Pietruczuk A., Nowakowski T., Werbińska-Wojciechowska S. Time between inspections optimization for technical object with time delay. Journal of Polish Safety and Reliability Association, Summer Safety and Reliability Seminars 2013; 4(1): 3541.
• 19. Jia X. Christer A. H. A periodic testing model for a preparedness system with a defective state. IMA Journal of Management Mathematics 2002; 13: 39-49.
• 20. Jiang R. A timeliness-based optimal inspection interval associated with the delay time model. Proc. of Prognostic and System Health Management Conference PHM – 2012, Beijing, 2012.
• 21. Kierzkowski A., Kisiel T. Functional readiness of the check-in desk system at an airport. Theory and engineering of complex systems and dependability. Proc. of the Tenth International Conference on Dependability and Complex Systems DepCoSRELCOMEX, June 29 - July 3, 2015, Brunów, Poland. Springer, 2015;. 223-233.
• 22. Laskowski D., Bylak M. Efficient diagnostics encoding mechanism for wireless networks. Electrical Review 2013; 89(9): 133-138.
• 23. Mazzuchi T. A., van Noortwijk J. M., Kallen M. J. Maintenance optimization. Technical Report, TR-2007-9, 2007.
• 24. Okumura S. An Inspection Policy for Deteriorating Processes Using Delay-Time Concept. International Transactions in Operational Research 1997; 4(5-6): 365-375.
• 25. Okumura S., Jardine A. K. S., Yamashina H. An inspection policy for a deteriorating single-unit system characterized by a delay-time model. International Journal of Production Research 1996; 34(9): 2441-2460.
• 26. Ozekici S. (ed.). Reliability and Maintenance of Complex Systems. NATO ASI Series, Series F: Computer and Systems Sciences, 154. Springer, 1996.
• 27. Redmond D. F. Delay Time Analysis in Maintenance. PhD thesis. Salford: University of Salford; 1997.
• 28. Restel F.J. The Markov reliability and safety model of the railway transportation system. Safety and reliability: methodology and applications: proceedings of the European Safety and Reliability Conference, ESREL 2014, 14-18 September, 2015, Wrocław, Poland. CRC Press/Balkema: 303-311.
• 29. Tang Y., Jing J. J., Yang Y., Xie C. Parameter estimation of a delay time model of wearing parts based on objective data. Mathematical Problems in Engineering 2015; Article ID 419280: doi:10.1155/2015/419280.
• 30. Valdez-Flores C., Feldman R. A survey of preventive maintenance models for stochastically deteriorating single-unit systems. Naval Research Logistics 1989; 36: 419-446.
• 31. Valis D., Koucky M., Žak L. On approaches for non-direct determination of system deterioration. Eksploatacja i Niezawodnosc - Maintenance and Reliability 2012; 14(1): 33-41.
• 32. Valis D., Vintr Z. Vehicle Maintenance Process Optimisation Using Life Cycle Costs Data and Reliability-Centred Maintenance. Proceedings of the First International Conference on Maintenance Engineering. Beijing: Science Press, 2006.
• 33. Van Oosterom C. D., Elwany A. H., Celebi D., van Houlum G. J. Optimal policies for a delay time model with postponed replacement. European Journal of Operational Research 2014; 232: 186-197.
• 34. Vintr Z., Valis D. A Tool for Decision Making in k-out-of-n System Maintenance. Applied Mechanics and Materials 2012; 110-116: 5257-5264.
• 35. Wang H. A survey of maintenance policies of deteriorating systems. European Journal of Operational Research 2002; 139: 469-489.
• 36. Wang W. An overview of the recent advances in delay-time-based maintenance modelling. Reliability Engineering and System Safety 2012; 106: 165-178.
• 37. Wang W. Delay time modelling. In: Kobbacy K. A.. H., Prabhakar Murphy D. N. (eds.). Complex system maintenance handbook. Springer-Verlag London Limited, 2008: 345-373.
• 38. Wang W. A delay time based approach for risk analysis of maintenance activities. Journal of the Safety and Reliability Society 2003; 23(1): 103-113
• 39. Wang W., Christer A. H. A modelling procedure to optimize component safety inspection over a finite time horizon. International Quality and Reliability Engineering 1997; 13: 217-224.
• 40. Yamashina H., Otani S. Cost-optimized maintenance of the elevator – single unit case. Journal of Quality in Maintenance Engineering 2001; 7(1): 49-70.
• 41. Zajac M., Swieboda J. Process hazard analysis of the selected process in intermodal transport. International Conference on Military Technologies (ICMT), 19-21 May 2015; 1-7.
• 42. Zieja M., Wazny M., Stepien S. Distribution determination of time of exceeding permissible condition as used to determine lifetimes of selected aeronautical devices/systems. Eksploatacja i Niezawodnosc - Maintenance and Reliability 2016; 18(1): 57-64.
• 43. Zhao J., Chan A. H. C., Roberts C., Madelin K. B. Reliability evaluation and optimisation of imperfect inspections for a component with multi-defects. Reliability Engineering and System Safety 2007; 92: 65-73.