Optimal replacement policies for deteriorating systems under imperfect delayed repair via a quasi renewal–alpha process

Maintenance optimization of repairable deteriorating systems remains an important problem in reliability engineering, particularly when repairs are imperfect and maintenance activities are subject to delays. This paper proposes an imperfect delayed repair maintenance model based on a Quasi Renewal–Alpha Process. An N-failure replacement policy is considered, and renewal–reward theory is used to derive expressions for the expected renewal cycle length and the long-run average cost rate. Analytical conditions are established for the existence and uniqueness of the optimal replacement number. Numerical examples are presented to illustrate the analytical results, and an empirical comparison with the classical Quasi Renewal Process is conducted using a publicly available failure-time dataset. Based on the Akaike Information Criterion (AIC), the Quasi Renewal–Alpha Process provides a better fit than the classical Quasi Renewal Process for this dataset.

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Publication Details

Journal
Discover Applied Sciences
Published
2026-10-28
DOI
https://doi.org/10.1007/s42452-026-09506-z
Primary Topic
Reliability and Maintenance Optimization
Type
article
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article

Optimal replacement policies for deteriorating systems under imperfect delayed repair via a quasi renewal–alpha process

Pervaiz Iqbal, D. Babu, M. Sutha, R. Neelakandan et al.
Discover Applied Sciences
Reliability and Maintenance Optimization
article

Optimal replacement policies for deteriorating systems under imperfect delayed repair via a quasi renewal–alpha process

Pervaiz Iqbal, D. Babu, M. Sutha, R. Neelakandan, M. Mageswari
article en

Abstract

Maintenance optimization of repairable deteriorating systems remains an important problem in reliability engineering, particularly when repairs are imperfect and maintenance activities are subject to delays. This paper proposes an imperfect delayed repair maintenance model based on a Quasi Renewal–Alpha Process. An N-failure replacement policy is considered, and renewal–reward theory is used to derive expressions for the expected renewal cycle length and the long-run average cost rate. Analytical conditions are established for the existence and uniqueness of the optimal replacement number. Numerical examples are presented to illustrate the analytical results, and an empirical comparison with the classical Quasi Renewal Process is conducted using a publicly available failure-time dataset. Based on the Akaike Information Criterion (AIC), the Quasi Renewal–Alpha Process provides a better fit than the classical Quasi Renewal Process for this dataset.

Discover Applied Sciences
Government of Tamil Nadu (IN), B.S. Abdur Rahman Crescent Institute of Science & Technology (IN)
Openalex Percentile: Top 13%
Reliability and Maintenance Optimization
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