Predictive maintenance for aircraft components using proportional hazard models

Abstract Unscheduled maintenance can contribute significantly to an airline's cost outlay. Reliability analysis can help to identify and plan for maintenance events. Reliability analysis in industry is often limited to statistically based approaches that incorporate failure times as the primary stochastic variable, with additional strict assumptions regarding independence of events and underlying distributions of failure phenomena. This foregoes the complex nature of aircraft operations, where a whole range of operational factors may influence the probability of occurrence of a maintenance event. The aim of this research is to identify operational factors affecting component reliability and to assess whether these can be used to reduce the number of unscheduled occurrences (i.e. failures). To do so, a data-driven approach is adopted where historical operational and maintenance data is gathered and analysed to identify operational factors with a measurable influence on maintenance event occurrence. Both time-independent and time-dependent Proportional Hazard Models (PHMs), models which incorporate operational factors as covariates, are employed to generate reliability estimates. Results obtained from analysing historical data of a set of nine components with respect to unscheduled removals indicates that adopting new maintenance schedules, derived from the proposed reliability models, can reduce the number of unscheduled occurrences.

[1]  D. Cox.  Regression Models and Life-Tables , 1972 .

[2]  Bengt Klefsjö,et al.  Proportional hazards model: a review , 1994 .

[3]  Hf Zuo,et al.  Condition Based Aero-Engine Maintenance Decision Method Using Proportional Hazards Model , 2006 .

[4]  Marvin Rausand,et al.  Reliability centered maintenance , 1998 .

[5]  Jayanthi Arasan,et al.  Modeling repairable system failures with repair effect and time dependent covariates. , 2011 .

[6]  Asit P. Basu,et al.  Statistical Methods for the Reliability of Repairable Systems , 2000 .

[7]  M. Kijima.  SOME RESULTS FOR REPAIRABLE SYSTEMS WITH GENERAL REPAIR , 1989 .

[8]  Harry A. Kinnison,et al.  Aviation Maintenance Management , 2004 .

[9]  Tore Markeset,et al.  Application of reliability models with covariates in spare part prediction and optimization - A case study , 2014, Reliab. Eng. Syst. Saf..

[10]  Jože Tavčar,et al.  Aircraft fault forecasting at maintenance service on the basis of historic data and aircraft parameters , 2017 .

[11]  R. D'Agostino,et al.  Goodness-of-Fit-Techniques , 1987 .

[12]  John C. Nash,et al.  On Best Practice Optimization Methods in R , 2014 .

[13]  Tiedo Tinga,et al.  Application of physical failure models to enable usage and load based maintenance , 2010, Reliab. Eng. Syst. Saf..

[14]  Wenbin Wang,et al.  A model to predict the residual life of aircraft engines based upon oil analysis data , 2005 .

[15]  Harold E. Ascher,et al.  Repairable Systems Reliability: Modelling, Inference, Misconceptions and Their Causes , 1984 .

[16]  Thomas D. Matteson.  Airline experience with reliability-centered maintenance , 1985 .

[17]  Guanghua Xu,et al.  A mixture Weibull proportional hazard model for mechanical system failure prediction utilising lifetime and monitoring data , 2014 .

[18]  Premaratne Samaranayake,et al.  Aircraft maintenance planning and scheduling : an integrated framework , 2012 .

[19]  Daming Lin,et al.  A review on machinery diagnostics and prognostics implementing condition-based maintenance , 2006 .

[20]  Donghua Zhou,et al.  Remaining useful life estimation - A review on the statistical data driven approaches , 2011, Eur. J. Oper. Res..

[21]  Huan-Jyh Shyur,et al.  A quantitative model for aviation safety risk assessment , 2008, Comput. Ind. Eng..

[22]  Andrew K. S. Jardine,et al.  A practical procedure for the selection of time-to-failure models based on the assessment of trends in maintenance data , 2009, Reliab. Eng. Syst. Saf..

[23]  Hoang Pham,et al.  System Software Reliability , 1999 .

[24]  Viliam Makis,et al.  Joint optimization of maintenance policy and inspection interval for a multi-unit series system using proportional hazards model , 2018, J. Oper. Res. Soc..

[25]  Stephen J. Wright,et al.  Sequential Quadratic Programming , 1999 .

[26]  John A. Buzacott,et al.  Equipment reliability and maintenance , 1985 .

[27]  J. Kalbfleisch,et al.  The Statistical Analysis of Failure Time Data , 1980 .

[28]  Tiedo Tinga,et al.  Principles of Loads and Failure Mechanisms: Applications in Maintenance, Reliability and Design , 2013 .

[29]  Narayanaswamy Balakrishnan,et al.  An Empirical Analysis of Some Nonparametric Goodness-of-Fit Tests for Censored Data , 2015, Commun. Stat. Simul. Comput..

[30]  Kash Barker,et al.  Proportional hazards models of infrastructure system recovery , 2014, Reliab. Eng. Syst. Saf..

[31]  R. Keith Mobley,et al.  An introduction to predictive maintenance , 1989 .

[32]  Jian Guo,et al.  Maintenance scheduling optimization based on reliability and prognostics information , 2016, 2016 Annual Reliability and Maintainability Symposium (RAMS).

[33]  Nikolaos Limnios,et al.  Statistical and probabilistic models in reliability , 1999 .

[34]  Juuso Töyli,et al.  Cooperative strategies for the availability service of repairable aircraft components , 2009 .