Linear assets are complex industrial systems that extend from one geographical region to another. Given the criticality of the industrial activities linked to them, it is vital to accurately estimate the systems' reliability. However, this task can be complex as the operational, maintenance and design conditions vary largely along linear asset thereby causing heterogeneity thus complicating the reliability analysis. This leads to inadequacy of the traditional single-parameter reliability approach that uses time as the only predictor variable. This thesis job reviews the existing methods to include explanatory factors into the analysis as covariates. Then, a workflow process is proposed to describe the sequence of steps and decisions needed to carry out the appropriate analysis. The presented flowcharts show how to deal with challenges that are often present in the industrial field. Approaches for dealing with multicollinearity, categorical and continuous covariates, time-dependent covariates, and repairable systems are treated in this work. Subsequently, a case study of railway track is presented as a repairable system with several covariates and failure times as provided by the Swedish Transport Administration. Two different models based on proportional hazard models i.e. the AG (Andersen-Gill) and the PWP(Prentice–Williams–Peterson) methods were run to estimate the regression parameters. Some other functions associated with reliability are obtained from the models such as the cumulative hazard rate and the probability of non-occurrence of the next recurrent event. In addition, to check the goodness of fit from the obtained models, the Cox-Snell residuals are estimated and used to verify if the estimated parameters fit the data. This procedure is done using a graphical method. From the goodness of fit test, it can be concluded that the PWP model performs better than the AG model. However, the fit is not good enough thus other model validation residual-based techniques are suggested as future work to investigate the reason for the discrepancy. Finally, some actions to deal with multicollinearity are recommended, including using a frailty model and the possibility of reformulating the covariates.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:ltu-87626 |
| Date | January 2021 |
| Creators | Rincon Franco, Alvaro Andres |
| Publisher | Luleå tekniska universitet, Drift, underhåll och akustik |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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