Reliability has become an issue to the Tianhe supercomputer series with the scaling of the system. Proactive fault-tolerance based on failure prediction turns into an effective way to improve the system’s fault tolerance ability. Data collection is the basis of the failure prediction which has a great impact on the prediction accuracy, while current data collection methods for failure predictio...

In this paper, the problem of predicting times to failure of units censored in multiple stages of progressively hybrid censoring for the proportional hazards family is considered. We discuss different classical predictors. The best unbiased predictor ($BUP$), the maximum likelihood predictor ($MLP$) and conditional median predictor ($CMP$) are all derived. As an example, the obtained results ar...

Reliability prediction methods for early design stages suffer from the lack of empirical failure data. However, expert knowledge and data from similar in-service components are information sources ready available. In this work, an expert elicitation procedure for failure rate prediction is presented. In contrast to direct elicitation procedures such as FMEA, relations to in-service components a...

Heart failure is one of the real cardio-vascular ailments influencing the center matured and the matured. It happens because of diminished cardiovascular yield. It can be both right-sided and left-sided failure of heart. This research study proposes a bio-inspired computing paradigm called particle swarm optimization shortly termed as PSO towards the prediction of heart failure. The implementat...

A sudden failure of a critical component in light-emitting diode (LED) manufacturing equipment would result in unscheduled downtime, leading to a possibly significant loss in productivity for the manufacturer. It is therefore important to be able to predict upcoming failures. A major obstacle to failure prediction is the limited amount of equipment lifecycle data available for training, as equi...

Preventive maintenance (PM) is an effective approach to promoting reliability. Time-based and condition-based maintenance are two major approaches for PM. No matter which approach is adopted for PM, whether a failure can be early detected or even predicted is the key point. This paper presents the experimental results of a failure prediction method for preventive maintenance by state estimation...

Online failure prediction for large-scale software systems is a challenging task. One reason is the complex structure of many—partially inter-dependent—hardware and software components. State-of-the-art approaches use separate prediction models for parameters of interest or a monolithic prediction model which includes different parameters of all components. However, they have problems when deal...

Using a conditional method, explicit formulae for computing quantiles pertinent to prediction intervals for future Weibull order statistics are developed for two cases: when only previous independent failure data are available, and when both previous independent failure data and early-failure data in current experiment are available. The second case includes the case when only current early-fai...