Simulation modeling of mean time between unscheduled removals of radio-electronic systems

Ulansky, Vladimir; Machalin, I. A.

doi:10.18372/1990-5548.33.5606

Cited by 2 publications

(8 citation statements)

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“…1800 for prognostic-based inspection reaching 0.997 and 0.915 at t = 4000 h, respectively. We can explain the PPSO behavior by the combined effect of the true-positive, false-negative 1, and false-negative 2 probabilities (see Figures 8,10(a), (d), and (f)). Thus, CBM inspection is more effective by the criterion of maximum PPSO than prognostic-based inspection because it provides a higher PPSO value.…”

Section: Efficiency Comparison Of Inspections At Condition-based and ...mentioning

confidence: 91%

“…Equations ( 8) and ( 10) imply that Y A,i is a function of S(t), N(t i ), and the replacement threshold L i . The presence of N(t i ) in (10) leads to appearing a random measurement error of the time to failure at inspection time t i , which we define as follows:…”

Section: Probabilistic Indicators Of Imperfect Cbm Inspectionsmentioning

confidence: 99%

“…The random variable Y A,i has a continuous range of values from 2N to + N. A mismatch between the solutions of equations ( 8) and (10) results in the appearance of one of the following mutually exclusive events when inspecting the system at the time t i :…”

Section: Probabilistic Indicators Of Imperfect Cbm Inspectionsmentioning

confidence: 99%

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Probabilistic indicators of imperfect inspections used in modeling condition-based and predictive maintenance

Raza

Ulansky

2022

Proceedings of the Institution of Mechanical Engineers, Part O:

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This study proposes mathematical models for assessing the probabilistic indicators of imperfect inspections conducted when performing condition-based and predictive maintenance. The inspections used in mentioned types of maintenance differ in decision rules regarding system operability at the time of checkup. Contrary to the previous studies, we present the decision rule for each type of inspection on the time axis, which allows the formulation of the set of mutually exclusive events at discrete times. The correct and incorrect decisions correspond to true-positive, false-positive, true-negative, and false-negative events. We propose general expressions for computing the probabilities of possible decisions for both types of inspection. The paper introduces the effectiveness indicators of condition-based and predictive maintenance such as average operating costs, total error probability, and a posteriori probability of failure-free operation. We illustrate the developed approach by calculating the probabilities of correct and incorrect decisions using a specific stochastic deterioration process. The results of the calculations verify that probabilities of correct and incorrect decisions for both types of inspection are very substantially time-dependent despite the large number of published studies where these probabilities are independent of time.

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Section: Efficiency Comparison Of Inspections At Condition-based and ...mentioning

confidence: 91%

Section: Probabilistic Indicators Of Imperfect Cbm Inspectionsmentioning

confidence: 99%

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Probabilistic indicators of imperfect inspections used in modeling condition-based and predictive maintenance

Raza

Ulansky

2022

Proceedings of the Institution of Mechanical Engineers, Part O:

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“…In 2012, ref. [56] examined the mission availability. The authors defined the non-stationary mission availability as the probability that the interval of trouble-free system operation θ entirely falls within one of the intervals between inspections [kτ, (k + 1)τ], k = 0, .…”

Section: False Positive αmentioning

confidence: 99%

“…. ., N. The study showed that if the system has an exponential distribution of time to a hidden failure, then the following relation holds [56]:…”

Section: False Positive αmentioning

confidence: 99%

A Historical Survey of Corrective and Preventive Maintenance Models with Imperfect Inspections: Cases of Constant and Non-Constant Probabilities of Decision Making

Ulansky,

Raza

2024

Aerospace

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Maintenance strategies play a crucial role in ensuring the reliability and performance of complex systems. Imperfect inspections, characterized by the probabilities of false positives and false negatives, significantly impact the effectiveness of maintenance decisions. This survey explores maintenance models under imperfect inspections, characterized by constant and non-constant probabilities of false positives and false negatives. This study investigates various maintenance approaches, such as preventive and corrective maintenance, and evaluates their performance, considering the uncertainties introduced by imperfect inspections. By analyzing the existing literature and research findings, this survey provides valuable insights into the challenges and opportunities associated with maintenance decision making in the presence of inspection imperfections. The comparison between maintenance models with constant and non-constant probabilities of false positives and false negatives sheds light on the dynamic nature of these models, enabling a deeper understanding of their real-world applicability and effectiveness. This comprehensive overview is a valuable resource for researchers, practitioners, and decision makers involved in maintenance planning and optimization in diverse industrial sectors.

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Simulation modeling of mean time between unscheduled removals of radio-electronic systems

Cited by 2 publications

References 0 publications

Probabilistic indicators of imperfect inspections used in modeling condition-based and predictive maintenance

Probabilistic indicators of imperfect inspections used in modeling condition-based and predictive maintenance

A Historical Survey of Corrective and Preventive Maintenance Models with Imperfect Inspections: Cases of Constant and Non-Constant Probabilities of Decision Making

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