Some Insights Into the Effect of Maintenance Quality for a Protection System

Berrade, María Dolores; Scarf, Philip; Cavalcante, Cristiano Alexandre Virgínio

doi:10.1109/tr.2015.2417431

Cited by 28 publications

(24 citation statements)

References 26 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However when the inspection procedure is not reliable, with a high rate of false negatives, the best policy is pure preventive replacement, M = 1. This result agrees with that in Berrade et al [6] and the study given therein about the consequences of low quality inspections on the optimum policy. One of the reasons for postponement is the notion that an immediate replacement when a defect is detected (τ = 0) is cost-prohibitive.…”

Section: Numerical Examplessupporting

confidence: 93%

“…The examples show that when the following two conditions hold: the time to defective state follows an exponential distribution and the probability of false negatives is low, M = ∞. A similar result is proved in Berrade et al [6]. Moreover note that the model in its current terms does not include any downtime or any other penalty when inspections are carried out and T and τ show no asymptotic behaviour but tend, respectively, to 0 and infinity for those cases where X is exponential and M = ∞.…”

Section: Model 2 Non-negligible Inspection Timessupporting

confidence: 77%

“…If so, the following probabilities become zero: renewal on opportunity after a true positive inspection P (OT P i ) in (1) or a false positive inspection P (OF P i ) in (4), renewal on failure after a true positive inspection P (F T P i ) in (3) or false positive inspection P (F F P i ) in (6). When τ = 0 a failure may occur after a negative inspection, whether it is a true negative or not, but never after a positive one because a positive inspection always implies the immediate replacement of the unit.…”

Section: The Case τ =mentioning

confidence: 99%

“…In our paper, we relax this restrictive assumption. Further, we allow the possibility that inspections may be imperfect, so that false negatives (whereby inspection indicates that the system is no-defective when it is in fact defective) and false positives are possible (as in Berrade et al [6], [7], [8]). The consequences of imperfect maintenance interventions mentioned in points 4 and 5 whereby strong components may be replaced with weak components have been analyzed in Scarf and Cavalcante [30] and [31].…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

A study of postponed replacement in a delay time model

Berrade

Scarf

Cavalcante

2017

Reliability Engineering & System Safety

View full text Add to dashboard Cite

We develop a delay time model for a one component system with postponed replacement to analyze situations in which maintenance might not be executed immediately upon discovery of a defect in the system. Reasons for postponement are numerous: to avoid production disruption or unnecessary or ineffective replacement; to prepare for replacement; to extend component life; to wait for an opportunity. This paper explores conditions that make postponement cost-effective. We are interested in modelling the reality in which a maintainer either prioritizes functional continuity or is not confident of the inspection test indicating a defective state. In some cases more frequent inspection and a longer time limit for postponement are recommended to take advantage of maintenance opportunities, characterized by their low cost, arising after a positive inspection. However, when the cost of failure increases, a significant reduction in the time limit of postponement interval is observed. The examples reveal that both the time to defect arrival and delay time have a significant effect upon the cost-effectiveness of maintenance at the limit of postponement. Also, more simply, we find that opportunities must occur frequently enough and inspection should be a high quality procedure to risk postponement.

show abstract

Section: Numerical Examplessupporting

confidence: 93%

Section: Model 2 Non-negligible Inspection Timessupporting

confidence: 77%

Section: The Case τ =mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A study of postponed replacement in a delay time model

Berrade

Scarf

Cavalcante

2017

Reliability Engineering & System Safety

View full text Add to dashboard Cite

show abstract

“…Finally, we can note studies inspecting and modeling the effect of human errors in enterprise systems such as nuclear power plants [34], [35], and studies trying to improve the maintenance and test quality of enterprise systems, in favor of maintenance cost and reliability/availability [36], [37].…”

Section: B Human Error In Safety-critical Applicationsmentioning

confidence: 99%

Modeling Impact of Human Errors on the Data Unavailability and Data Loss of Storage Systems

Kishani

Asadi

2018

IEEE Trans. Rel.

View full text Add to dashboard Cite

Data storage systems and their availability play a crucial role in contemporary datacenters. Despite using mechanisms such as automatic fail-over in datacenters, the role of human agents and consequently their destructive errors is inevitable. Due to very large number of disk drives used in exascale datacenters and their high failure rates, the disk subsystem in storage systems has become a major source of Data Unavailability (DU) and Data Loss (DL) initiated by human errors. In this paper, we investigate the effect of Incorrect Disk Replacement Service (IDRS) on the availability and reliability of data storage systems. To this end, we analyze the consequences of IDRS in a disk array, and conduct Monte Carlo simulations to evaluate DU and DL during mission time. The proposed modeling framework can cope with a) different storage array configurations and b) Data Object Survivability (DOS), representing the effect of system level redundancies such as remote backups and mirrors. In the proposed framework, the model parameters are obtained from industrial and scientific reports alongside field data which have been extracted from a datacenter operating with 70 storage racks. The results show that ignoring the impact of IDRS leads to unavailability underestimation by up to three orders of magnitude. Moreover, our study suggests that by considering the effect of human errors, the conventional beliefs about the dependability of different Redundant Array of Independent Disks (RAID) mechanisms should be revised. The results show that RAID1 can result in lower availability compared to RAID5 in the presence of human errors. The results also show that employing automatic fail-over policy (using hot spare disks) can reduce the drastic impacts of human errors by two orders of magnitude.

show abstract

Imperfect and worse than old maintenances for a gamma degradation process

Corset,

Fouladirad,

Paroissin

2024

Appl Stoch Models Bus & Ind

View full text Add to dashboard Cite

This article considers a condition‐based maintenance for a system subject to deterioration. The deterioration is modeled by a non‐homogeneous gamma process, more precisely the gamma process and the preventive maintenance are imperfect or worse than old. The corrective maintenance actions are as good as new. The maintenance efficiency or non‐efficiency parameters as well as the deterioration parameters are considered to be unknown. The monitoring data under consideration give indirect information on the maintenance parameters. Therefore, an expected maximum algorithm is applied for parameter estimation.

show abstract

Some Insights Into the Effect of Maintenance Quality for a Protection System

Cited by 28 publications

References 26 publications

A study of postponed replacement in a delay time model

A study of postponed replacement in a delay time model

Modeling Impact of Human Errors on the Data Unavailability and Data Loss of Storage Systems

Imperfect and worse than old maintenances for a gamma degradation process

Contact Info

Product

Resources

About