Conditional-based maintenance (CBM) decision-making is of high interests in recent years due to its better performance on cost efficiency compared to other traditional policies. One of the most respected methods based on condition-monitoring data for maintenance decision-making is Proportional Hazards Model (PHM). It utilizes condition-monitoring data as covariates and identifies their effects on the lifetime of a component. Conventional modeling process of PHM only treats the degradation process as a whole lifecycle. In this paper, the PHM is advanced to describe a multi-zone degradation system considering the fact that the lifecycle of a machine can be divided into several different degradation stages. The methods to estimate reliability and performance prognostics are developed based on the proposed multi-zone PHM to predict the remaining time that the machine stays at the current stage before transferring into the next stage and the remaining useful life (RUL). The results illustrate that the multi-zone PHM effectively monitors the equipment status change and leads to a more accurate RUL prediction compared with traditional PHM.
On the use of cluster analysis for interpretation of soil pollution monitoring data obtained near mining enterprise
