One system reliability assessment method for CNC grynder

• Autorzy: Liu Y. , Fan J. , Li Y.

Warianty tytułu

PL

Metoda oceny niezawodności systemu szlifierki CNC

• Języki publikacji: EN

Abstrakty

EN

The reliability level of CNC (Computer Numerical Control) grinder is usually assessed by fault data counted in laboratory or in field, which needs the grinder to be assembled and it is one afterwards estimation method. To evaluate the reliability level of CNC grinder in design phrase, one system reliability assessment method and algorithm was put forward by subsystem’s reliability in this article, which needs subsystem classification, reliability test, distribution function fitting, parameters estimation and reliability assessment. The calculation result showed that the method was feasible and accurate compared with the traditional way. The method is one contribution to reliability design for CNC grinder and is one reference to other mechatronic products.

PL

Poziom niezawodności szlifierki CNC (sterowanej numerycznie) zazwyczaj ocenia się na podstawie danych o uszkodzeniach liczonych w laboratorium lub w terenie, co wymaga zmontowania szlifierki i jest metodą oceny post-factum. Aby umożliwić ocenę poziomu niezawodności szlifierki CNC na etapie projektowania, w niniejszym artykule zaproponowano metodę oceny niezawodności systemu oraz odpowiedni algorytm wykorzystujące dane dotyczące niezawodności podsystemów. Model ten wymaga klasyfikacji podsystemów, badań niezawodności, dopasowania funkcji rozkładu, oceny parametrów oraz oceny niezawodności. Wyniki obliczeń wykazały, że omawiana metoda sprawdza się i jest dokładna w porównaniu z metodą tradycyjną. Przedstawiona metoda stanowi wkład do procesu projektowania niezawodności szlifierki CNC i znajduje odniesienie do innych produktów mechatronicznych.

Słowa kluczowe

EN

system reliability; assessment method; MTBF; CNC grinder

PL

niezawodność systemu; metoda oceny; MTBF; szlifierka CNC

• Wydawca: Polskie Naukowo-Techniczne Towarzystwo Eksploatacyjne
• Czasopismo: Eksploatacja i Niezawodność
• Rocznik: 2014
• Tom: Vol. 16, no. 1
• Strony: 97--104
• Opis fizyczny: Bibliogr. 20 poz.

Twórcy

autor

Liu Y.

• College of Mechanical Engineering and Applied Electronics Technology, Beijing university of Technology, Jidian buliding, Room 304, Pingleyuan 100, Chaoyang district, 100124, Beijing, China

autor

Fan J.

• College of Mechanical Engineering and Applied Electronics Technology, Beijing university of Technology, Jidian buliding, Room 304, Pingleyuan 100, Chaoyang district, 100124, Beijing, China

autor

Li Y.

• College of Mechanical Engineering and Applied Electronics Technology, Beijing university of Technology, Jidian buliding, Room 304, Pingleyuan 100, Chaoyang district, 100124, Beijing, China

Bibliografia

• 1. Batson RG, Jeong Y, Fonseca DJ. Control charts for monitoring field failure data. Quality and Reliability Engineering International 2006; 22: 733–755.
• 2. Bergmann RB, Bill A. On the origin of logarithmic-normal distributions: An analytical derivation, and its application to nucleation and growth processes. Journal of Crystal Growth 2008; 310: 3135–3138.
• 3. Chaudhuri G, Hu KL, Afshar N. A new approach to system reliability. IEEE Transactions on Reliability 2001; 50: 75–84.
• 4. Condra L, Bosco C, Deppe R. Reliability assessment of aerospace electronic equipment. Quality and Reliability Engineering International 1999; 15: 253–260.
• 5. Donald SJ, Himanshu P, Michael T. Improved reliability-prediction and field–reliability–data analysis for field-replaceable units. IEEE Transactions on Reliability 2002; 51: 8–16.
• 6. Giordano, Arthur A. Least square estimation with applications to digital signal processing, John-wiley, Hoboken, the United States of America, 1985.
• 7. Guo J, Du XP. Reliability sensitivity analysis with random and interval variables. International Journal for Numerical Methods in Engineering 2009; 78: 1585–1617.
• 8. Ke WJ, Wang SD. Reliability evaluation for distributed computing networks with imperfect nodes. IEEE Transactions on Reliability 1997; 46: 342–349.
• 9. Khalili A, Kromp K. Statistical properties of weibull estimators. Journal of Materials Science 1991; 26: 6741–6752.
• 10. Lazim MT, Zeidan M. Reliability evaluation of ring and triple-bus distribution systems – General solution for n-feeder configurations. International Journal of Electrical Power & Energy Systems 2013; 47: 78–84.
• 11. Lu H, Zhang YM, Lv H, “Reliability sensitivity analysis of mechanical parts with multiple failure modes,” International Conference on Quality, Reliability, Risk, Maintenance and Safety Engineering (QR2MSE) 2012; 1175–1177.
• 12. Morris HD, Mark JS. Probability and statistics. China Machine Press, Beijing, China, 2012.
• 13. Nathan G, Anthony P, Srihari K. The reliability prediction of electronic packages – an expert systems approach. International Journal of Advanced Manufacturing Technology 2005; 27: 381–391.
• 14. Payette GS, Reddy JN. On the roles of minimization and linearization in least-squares finite element models of nonlinear boundary-value problems. Journal of Computational Physics 2011; 230: 3589–3613.
• 15. Schladitz K, Engelbert HJ. On probability density functions which are their own characteristic functions. Theory of Probability and Its Applications 1996; 40: 577–581.
• 16. Voinov V, Pya N, Shapakov N. Goodness-of-fit tests for the power-generalized weibull probability distribution. Communications in StatisticsSimulation and Computation 2013; 42: 1003–1012.
• 17. Wang ZM, Yu X. Log-linear process modeling for repairable systems with time trends and its applications in reliability assessment of numerically controlled machine tools. Proceedings of the Institution of Mechanical Engineers Part O-Journal of Risk and Reliability 2013; 227: 55–65.
• 18. Yang ZJ, Chen CH, Chen F. Reliability analysis of machining center based on the field data. Eksploatacja i Niezawodnosc – Maintaince and Reliability 2013; 2: 147–155.
• 19. Young KS. Reliability prediction of engineering systems with competing failure modes due to component degradation. Journal of Mechanical Science and Technology 2011; 25: 1717–1725.
• 20. Zunino JL, Skelton DR. MEMS reliability assessment program. Conference on Reliability, Packaging, Testing, and Characterization of MEMS/MOEMS VI 2007; D4630–D4630