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Tytuł artykułu

Determination of the average maintenance time of CNC machine tools based on type II failure correlation

Treść / Zawartość
Identyfikatory
Warianty tytułu
PL
Określenie średniego czasu konserwacji obrabiarek CNC w oparciu o korelację awarii typu II
Języki publikacji
EN
Abstrakty
EN
An average maintenance time calculation method based on components failure correlation analysis is proposed to revise the traditional system maintenance time. This paper focus on complex system type II fault correlation, using the Decision-making trial and evaluation laboratory / Interpretative structural model method to divide the fault level of components. And the copula connection function is introduced to calculation of failure rate function of failure correlation components. In addition, the system maintenance time model is established by synthesizing the failure rate function of each unit of the system. Moreover, the average maintenance time under the minimum number of failures is determined. This method shows that the minimum average maintenance time of the proposed system is more reasonable than the traditional one and provides the basis for system and component reliability design.
PL
W artykule zaproponowano metodę obliczania średniego czasu konserwacji, opartą na analizie korelacji uszkodzeń elementów składowych systemu. Metoda ta ma na celu rewizję tradycyjnego czasu konserwacji systemu. Głównym tematem pracy jest korelacja awarii typu II występujących w systemach złożonych. Elementy systemu podzielono ze względu na poziom uszkodzenia przy użyciu metody DEMATEL w połączeniu z interpretacyjnym modelowaniem strukturalnym. Funkcję intensywności skorelowanych uszkodzeń elementów systemu obliczono za pomocą funkcji łączącej (kopuły). Dodatkowo, opracowano model czasu konserwacji systemu poprzez syntezę funkcji intensywności uszkodzeń każdej jednostki systemu. Ponadto, określono średni czas konserwacji dla minimalnej liczby uszkodzeń. Metoda ta pokazuje, że minimalny średni czas konserwacji proponowanego systemu jest korzystniejszy niż tradycyjnie przyjęty i stanowi podstawę do projektowania niezawodności systemu i jego składowych.
Rocznik
Strony
604--614
Opis fizyczny
Bibliogr. 27 poz., rys., tab.
Twórcy
autor
  • NC equipment credibility Engineering Research Institute College of Mechanical Science and Engineering Jilin University People str., 5988 Changchun, 130022, China
autor
  • NC equipment credibility Engineering Research Institute College of Mechanical Science and Engineering Jilin University People str., 5988 Changchun, 130022, China
autor
  • NC equipment credibility Engineering Research Institute College of Mechanical Science and Engineering Jilin University People str., 5988 Changchun, 130022, China
autor
  • Department of Industrial Engineering College of Mechanical Science and Engineering Jilin University People str., 5988 Changchun, Jilin 130022, China
autor
  • Department of Industrial Engineering College of Mechanical Science and Engineering Jilin University People str., 5988 Changchun, Jilin 130022, China
Bibliografia
  • 1. Bu Yingyong, Zhang Huailiang. The preliminary attempt to develop preventive-predictive maintenance. Journal of Central South University 1995: 2(2):32-36, https://doi.org/10.1007/BF02652004.
  • 2. Charles E. Ebeling. An Introduction to Reliability and Maintainability Engineering. Tsinghua University Press 2010; 1:157-158.
  • 3. Cheng Xiao-min, Jia Ya-zhou, Shu Ze. Statistical research on maintenance time of CNC machine tools. Machine Tools & Hydraulics 1992; 02:83-85.
  • 4. Ebeling C E. An introduction to reliability and maintainability engineering. McGraw-Hill Education, New York 2004.
  • 5. Huang Xi-li, Han Xi-an. Method for fuzzy maintainability index demonstration in lognormal distribution. Journal of Systems Engineering and Electronics 2008; 30(2): 375-378.
  • 6. Kai Zhang, Jinchun Song, Guangan Ren, Jia Shi. Particle swarm optimization algorithm with multi methods argument. AI Communications 2016; P: 1-15.
  • 7. Lam Y. A geometric Process Maintenance Model with Preventive Repair.European Journal of Operational Research 2007; 182: 806-819, https://doi.org/10.1016/j.ejor.2006.08.054.
  • 8. Liu Duan, Hu Jian Bo, Ge Xiao Kai, el at. Monte Carlo Simulation of Maintenance Time Based on System Maintenance Work Procedure. Fire Control & Command Control 2014; 39 (7): 119-123.
  • 9. Lu Zhong, Sun You Chao, Wu Hai Qiao. System Maintainability Modeling Method Based on Colored Stochastic Time Petri Net. Journal of Mechanical Engineering 2011; 47 (10): 185-191, https://doi.org/10.3901/JME.2011.10.185.
  • 10. Ma Zhan-Fei. ISM-based architecture for network security system. ICEIT 2010 -2010 International Conference on Educational and Information Technology Proceedings 2010:1969-2014.
  • 11. Murthy D N P, Nguyen D G. Study of a multi-component system with failure interaction. Eu J Oper Res 1985; 21: 330-338, https://doi. org/10.1016/0377-2217(85)90153-5.
  • 12. Radiša Djurić, Vladimir Milisavljević. Investigation of the relationship between reliability of track mechanism and mineral dust content in rocks of lignite open pits. Eksploatacja i Niezawodnosc – Maintenance and Reliability 2016; 18 (1): 142–150, https://doi.org/10.17531/ ein.2016.1.19.
  • 13. Shahannaghi K, Babaei H, Bakhsha A et al. A New Condition Based Maintenance Model with Random Improvements on the System After Maintenance Actions:Optimizing by Monte Carlo Simulation].World Journal of Modeling and Simulation 2008; 4(3): 230-236.
  • 14. Shey-Huei Sheuab, Chin-Chih Changc, Yen-Luan Chend, Zhe George Zhangef. Optimal preventive maintenance and repair policies for multi-state systems. Reliability Engineering and System Safety 2015; 140: 78-87, https://doi.org/10.1016/j.ress.2015.03.029.
  • 15. Sklar A. Fonctions de repartition an dimensions et leurs marges. Paris: Publication Institute Statist University 1959; 8: 229-231.
  • 16. Sun Y, Ma L, Mathew J, et al. An analytical model for interactive failure. Reliability Engineering& System Safety 2006; 91(5): 495-504, https://doi.org/10.1016/j.ress.2005.03.014.
  • 17. U.S. Department of Defense. MIL-STD-470B Maintainability program requirements for systems and equipment. Ohio: Aeronautical system Center 1989.
  • 18. Wang H Z, Pham H. Reliability and Optimal Maintenance. Springer-Verlag London: Springer Series in Reliability Engineering Series, 2006.
  • 19. Wang L, Hu H J, Wang Y Q, et al. The Availability Model and Parameters Estimation Method for the Delay Time Model with Imperfect Maintenance at Inspection. Applied Mathematical Modeling 2011; (35): 2855-2863, https://doi.org/10.1016/j.apm.2010.11.070.
  • 20. Wu Jingmin, Zuo Hongfu, Chen Yong. An estimation method for direct maintenance cost of aircraft components based on particle swarm optimization with immunity algorithm. Journal of Central South University 2005; 12(2): 95-101, https://doi.org/10.1007/s11771-0050018-9.
  • 21. Wu W W. Choosing knowledge management strategies by using a combined ANP and DEMATEL approach. Expert Systems and Applications 2008; 35(3): 828-835, https://doi.org/10.1016/j.eswa.2007.07.025.
  • 22. Wu Xi, Xu Da, Mu Ge, Li Chuang. Research on verification method of equipment maintenance time based on digital prototyping. Manufacturing Technology & Machine Tool 2013; 12: 63-66.
  • 23. Y. G. Petalas; K. E. Parsopoulos; M. N. Vrahatis. Memetic particle swarm optimization. Annals of Operations Research 2007; 155(1): 99127, https://doi.org/10.1007/s10479-007-0224-y.
  • 24. Zhang Deng-Feng, Fei Sheng-Wei, Liu Yuan-Wei, Sun Yu. Approach on failure diagnosis knowledge acquisition in beginning stage of maintenance for complex equipments. Journal of Central South University (Science and Technology) 2009; 40(S1): 284-289.
  • 25. Zhang Hai-bo, Liu Liang, Huang Yang-yang. Maintain Time Model of CNC Machining Center. Modular Machine Tools & Automatic Manufacturing Technique 2014; 05:158-160.
  • 26. Zhuoqi Zhang, Su Wu, Binfeng Li. Opportunistic maintenance policy for a two-unit system with failure interactions. Journal of Tsinghua University(Science and Technology) 2012; 52(1):122-127.
  • 27. Zuo F-J, Yu L, Mi J, Liu Z, Huang H-Z. Reliability analysis of gear transmission with considering failure correlation. Eksploatacja i Niezawodnosc – Maintenance and Reliability 2015; 17 (4): 617–623, https://doi.org/10.17531/ein.2015.4.19.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-1a7c079a-ca91-4355-9f4c-65251ed0ea97
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