Applied Probability and Statistical Inference in Quality and Reliability Engineering

A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "E: Applied Mathematics".

Deadline for manuscript submissions: 20 December 2026 | Viewed by 641

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Department of Statistics and Insurance Science, University of Piraeus, 185 34 Piraeus, Greece
Interests: nonparametric statistical inference; statistical reliability theory; statistical process control; order statistics; applied probability
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Guest Editor
Laboratory of Statistics and Data Analysis, Department of Statistics and Actuarial-Financial Mathematics, University of the Aegean, GR-83200 Karlovasi, Greece
Interests: model selection; applied probability; reliability theory; medical statistics; time series; biostatistics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Probability theory and statistics play a fundamental role in the research of various scientific fields, such as engineering, computer science, medicine, biology, or economics. Several statistical methods and probabilistic approaches, such as order statistics, Markov chain embedding, computational statistics, generating functions approaches, or nonparametric statistics have attracted considerable interest from researchers in recent decades.

The aim of this Special Issue is to provide some evidence which reflects the importance of statistical techniques and probabilistic modelling in applied scientific areas related to reliability engineering. We welcome articles establishing theoretical methodologies in these fields, but papers providing interesting and innovative applications, including solutions of important practical problems and case studies of probability and statistics, shall also be considered. Thus, this Special Issue is expected to be a collective work by a number of leading researchers and practitioners in their respective fields of expertise and, in general, experts who have been working at the forefront of applied probability, statistics, and reliability theory.

Dr. Ioannis S. Triantafyllou
Prof. Dr. Alex Karagrigoriou
Guest Editors

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Keywords

  • reliability modelling
  • nonparametric statistics
  • probabilistic methods
  • statistical models and methods
  • reliability and risk analysis
  • stochastic models and methods
  • probabilistic models in reliability
  • nonparametric methods in reliability
  • software reliability
  • Markov and semi-Markov processes in reliability
  • stochastic problems in reliability
  • multi-state systems
  • maintenance policies in reliability
  • order statistics in reliability
  • statistical process control
  • quality management
  • run length distribution
  • control charts

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Research

14 pages, 620 KB  
Article
Consecutive-k-out-of-n: G Systems with Stochastically Effective Protection Blocks
by Ioannis S. Triantafyllou
Mathematics 2026, 14(14), 2474; https://doi.org/10.3390/math14142474 - 9 Jul 2026
Viewed by 270
Abstract
In the present work, we study the reliability of consecutive-k-out-of-n: G systems equipped with imperfect protection blocks that enhance the operating probability of protected components only with probability q. This stochastic effectiveness fits to realistic scenarios, where protective [...] Read more.
In the present work, we study the reliability of consecutive-k-out-of-n: G systems equipped with imperfect protection blocks that enhance the operating probability of protected components only with probability q. This stochastic effectiveness fits to realistic scenarios, where protective actions are not fully reliable. We derive a recurrence scheme for computing the reliability of the aforementioned structure, while asymptotic expressions are also provided. In addition, we investigate the impact of the protection parameters on the asymptotic convergence rate of the reliability for the underlying consecutive-k-out-of-n: G systems equipped with imperfect protection blocks. Several numerical results are produced in order to shed light on how the effectiveness and positioning of stochastic protection affect system reliability. Finally, a DNA sequencing application is described in order to provide some evidence about the applicability of the proposed scheme in real-life situations. Full article
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