On the practical interest of discrete Inverse Polya and Weibull-1 models in industrial reliability studies
Alberto Pasanisi, C\^ome Roero, Nicolas Bousquet, Emmanuel Remy

TL;DR
This paper evaluates the practical usefulness of discrete Inverse Polya and Weibull-1 models for industrial reliability, highlighting their suitability in specific scenarios like low aging and cycle-based measurements.
Contribution
It provides a comparative analysis of two discrete lifetime models, clarifying their applicability and limitations in industrial reliability assessments.
Findings
Inverse Polya is intuitive for low (decelerated) aging scenarios.
Both models are limited when data are heavily censored or aging nature is unknown.
Continuous models like Weibull often outperform discrete models in flexibility.
Abstract
Engineers often cope with the problem of assessing the lifetime of industrial components, under the basis of observed industrial feedback data. Usually, lifetime is modelled as a continuous random variable, for instance exponentially or Weibull distributed. However, in some cases, the features of the piece of equipment under investigation rather suggest the use of discrete probabilistic models. This happens for an equipment which only operates on cycles or on demand. In these cases, the lifetime is rather measured in number of cycles or number of demands before failure, therefore, in theory, discrete models should be more appropriate. This article aims at bringing some light to the practical interest for the reliability engineer in using two discrete models among the most popular: the Inverse Polya distribution (IPD), based on a Polya urn scheme, and the so-called Weibull-1 (W1) model.…
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