Prediction of remaining useful life (RUL) of Komatsu excavator under reliability analysis in the Weibull-frailty model

Weibull model for RUL estimation at RSG-GAS reactor implemented on PA01-AP01 secondary pump

Remaining Useful Life (RUL) estimation has been extensively explored in recent years. RUL could be used in deciding the maintenance timeline or inspection interval for the Reaktor Serba Guna – G. A. Siwabessy (RSG-GAS reactor). RSG-GAS reactor is a pool-type research reactor (built by the Interatom Internationale of Germany) and has been operating for more than 30 years to date. This study aimed to propose a Weibull model to find the RUL estimation value of the distribution parameters of the mean time to failure (MTTF). Therefore, the RSG-GAS reactor would be higher safety, longer lifetime and higher reliability with a smaller failure rate including for the PA01-AP01 secondary pump. The research methodology is processing data collection and estimating the parameters of the Weibull model to determine maintenance timeline or inspection intervals based on the MTTF value in case the reliability has reached the targeted percentage. Results show that the RUL estimation has been obtained for the RSG-GAS reactor. In the implemented study, a maintenance timeline has been stipulated for the PA01-AP01 secondary pump (with the model of KSB and type of CPK-S350-400) for the reliability of 90% and RUL estimation of circa 29 days.

Resilience analysis: A formulation to model risk factors on complex system resilience

Resilience is about the ability of the system to resist, adapt to, and expeditiously recover from a disruptive event. The first and maybe the crucial step of resilience management is known as resilience analysis. However, there are many obstacles in front of the analyzers to analyze the resilience of systems. One of these obstacles is precise resilience data accessibility. Conventional resilience analysis methods frequently only consider historical data (e.g., time to repair and time to failure). However, to analyze the system resilience more precisely, the effect of the risk factors, which are known as observed and unobserved covariates, should be considered in the collected resilience database. These covariates will lead to the observed and unobserved heterogeneities among the collected database. Ignoring the effect of covariate may lead to erroneous conclusion about the resilience level of the system. Since it is hard to find a homogeneous operating condition, in this study, a formulation is proposed to model the effect of these covariates on complex system resilience. Finally, it is applied to a transportation system of a surface mine.