ENBIS-26 Conference

Session

Reliability

Sep 8, 2026, 10:55 AM

Conveners

Reliability

• Antonio Pievatolo (CNR-IMATI)

Reliability

• Antonio Pievatolo (CNR-IMATI)

35. Statistical Travel Time Inference Under Incomplete Data: A Queueing-Theoretic Approach

Dingyi Wang (Academy of Mathematics and Systems Science, Chinese Academy of Sciences)

9/8/26, 10:55 AM

Reliability

Travel time reliability (TTR) is an important issue in transportation systems, significantly influencing individual decision-making and aggregate travel demand. The inherent uncertainty in travel time is crucial for various applications, which requires the estimation of entire travel time distribution instead of merely the expected travel time. This work proposes a statistical framework for...

4. Importance inference of optimal test planning for degradation analysis

Chien-Yu Peng (Academia Sinica)

9/8/26, 11:15 AM

Reliability

Determination of the decision variables such as the inspection period, number of measurements, and sample size is crucial for planning an efficient degradation test. For widely used stochastic processes, the necessary and sufficient conditions for the explicit expression of optimal decision variables can be derived by minimizing the approximate variance of an estimator of interest under a...

71. A scheme for the predictive replacement of litium-ion batteries, using reinforcement learning

Antonio Pievatolo (CNR-IMATI)

9/8/26, 11:35 AM

Reliability

Based on previous results we obtained, it is possible to establish a replacement decision policy for every pair of charge/discharge cycle index and (discretized) state of health of a lithium-ion battery, using Monte Carlo reinforcement learning to optimize a state-action value function. This function balances the value of using the battery for as long as possible against the loss due to...

30. Variable Selection under Cumulative Exposure Model for Time-to-Event Data with Time-Varying Covariates

Yueyao Wang (Zhejiang Gongshang University)

9/8/26, 12:00 PM

Reliability

In various industrial applications, sensors are widely used to collect the signals for predicting the lifetime of product units or systems.
From a modeling perspective, the signal from each sensor can be considered as a time-varying covariate and the lifetime of units can be considered as the response.In the literature, cumulative exposure models are used to link the lifetime response with...

47. Reliability testing of repairable systems available in diverse configuration variants

Nikolaus Haselgruber (CIS Consulting in Industrial Statistics GmbH)

9/8/26, 12:20 PM

Reliability

Reliability testing is one of the last and most expensive steps in the development process of a complex technical repairable system. It ensures a certain level of reliability prior to market release and provides the basis for estimation of expected maintenance and warranty costs. Depending on system complexity and diversity of available configurations, current industrial practice is to select...