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**A model to predict the residual life of aircraft engines based upon oil analysis data.**
*(English)*
Zbl 1123.62073

Summary: This paper reports on a study using the available oil monitoring information, such as the data obtained using the spectrometric oil analysis programme (SOAP), to predict the residual life of a set of aircraft engines. The relationship between oil monitoring information and the residual life is established using the concept of the proportional residual, which states that the predicted residual life may be proportional to the wear increment measured by the oil analysis programmes. Assuming such a relationship between wear and the residual life exists, we formulated a recursive prediction model for the item’s residual life given measured oil monitoring information to date. A set of censored life data of 30 aircraft engines (right censored due to preventive overhaul) along with the history of their monitored metal concentration information are available to us. The metal concentration information includes many variables, such as Fe, Cu, Al, etc.; not all of them are useful, and some of them may be correlated. The principal component analysis (PCA) has been adopted to reduce the dimension of the original data set and to produce a new set of uncorrelated variables, which we shall use in the prediction model. The procedure associated with estimating model parameters is discussed. The model is fitted to the actual SOAP data from the aircraft engines, and the goodness-of-fit test has been carried out.

### MSC:

62N05 | Reliability and life testing |

62H25 | Factor analysis and principal components; correspondence analysis |

62P30 | Applications of statistics in engineering and industry; control charts |

62N01 | Censored data models |

### Keywords:

prediction; oil analysis; condition monitoring; principal component analysis; goodness-of-fit test
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\textit{W. Wang} and \textit{W. Zhang}, Nav. Res. Logist. 52, No. 3, 276--284 (2005; Zbl 1123.62073)

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### References:

[1] | Lube oil analysis expert system, Can Maintenance Eng Conf, Toronto, 1989. |

[2] | Al-Najjar, Proc Inst Mech Eng 212 pp 111– (1998) |

[3] | and Introduction to multivariate analysis, Chapman and Hall, London, 1980. |

[4] | Christer, J Oper Res Soc 50 pp 1120– (1999) |

[5] | Coolen, IEEE Trans Reliab 44 pp 505– (1995) |

[6] | and Statistical analysis of reliability data, Chapman and Hall, London, 1991. |

[7] | and Goodness-of-fit techniques, Marcel Dekker, New York, 1986. |

[8] | Fisher, J Roy Statist Soc 85 pp 87– (1922) |

[9] | Gong, European J Oper Res 96 pp 479– (1997) |

[10] | Tribology-a key element in condition monitoring, Proc Condition Monitoring 2001, Coxmoore, Oxford, 2001, pp. 20-29. |

[11] | Kumar, European J Oper Res 99 pp 507– (1997) |

[12] | State and model parameter estimation for transmissions on heavy hauler trucks using oil data, Proc COMADEM2002, 2002, pp. 339-348. |

[13] | Makis, IMA J Math Appl Bus Indus 3 pp 169– (1991) |

[14] | Pearson, Philos Mag 50 pp 157– (1900) |

[15] | et al. (Editors), Proceedings of COMADEM, 1995- 2002. |

[16] | Volk, J Oper Res Soc 53 pp 193– (2002) |

[17] | Wang, IMA J Manag Math 13 pp 3– (2002) |

[18] | Wang, J Oper Res Soc 51 pp 145– (2000) |

[19] | A model to predict equipment residual life based upon oil analysis data, Proc COMADEM2002, 2002, pp. 538-545. |

[20] | and Stochastic decision modelling of condition based maintenance, Proc COMADEM96, 1996, pp. 1175-1184. |

[21] | and Modelling condition based maintenance of production plant, Proc COMADEM97, 9-11 June 1997, Espoo, Finland, Erkki Jantunen (Editor), Julkaisija-Utgivare, Espoo, pp. 75-84. |

[22] | Wang, J Oper Res Soc 51 pp 1218– (2000) |

[23] | Mathematical statistics, Wiley, New York, 1962. · Zbl 0173.45805 |

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