Modeling failure and maintenance effects of a system subject to multiple preventive maintenance types

Said, Uthman; Taghipour, Sharareh

doi:10.1109/rams.2016.7448007

Cited by 6 publications

(2 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Said et al [8] apresentam uma análise para quantificar os efeitos de múltiplas políticas de manutenção preventivas sobre a confiabilidade e disponibilidade de equipamentos móveis. Considera-se um sistema complexo e reparável, como um caminhão de transporte subterrâneo submetido a manutenção corretiva e vários tipos de manutenção preventiva (MP).…”

Section: Trabalhos Relacionadosunclassified

Evaluating the impact of maintenance policies associated to SLA contracts on the dependability of data centers electrical infrastructures

Melo

Silva

Callou

2020

RITA

View full text Add to dashboard Cite

Due to the growth of cloud computing, data center environment has grown in importance and in use. Data centers are responsible for maintaining and processing several critical-value applications. Therefore, data center infrastructures must be evaluated in order to improve the high availability and reliability demanded for such environments. This work adopts Stochastic Petri Nets (SPN) to evaluate the impact of maintenance policies on the data center dependability. The main goal is to analyze maintenance policies, associated to SLA contracts, and to propose improvements. In order to accomplish this, an optimization strategy that uses Euclidean distance is adopted to indicate the most appropriate solution assuming conflicting requirements (e.g., cost and availability). To illustrate the applicability of the proposed models and approach, this work presents case studies comparing different SLA contracts and maintenance policies (preventive and corrective) applied on data center electrical infrastructures.

show abstract

Section: Trabalhos Relacionadosunclassified

Evaluating the impact of maintenance policies associated to SLA contracts on the dependability of data centers electrical infrastructures

Melo

Silva

Callou

2020

RITA

View full text Add to dashboard Cite

show abstract

“…In this case, the product terms will change to the sum of the logarithmic events. For the same kind of multiple systems, the logarithm of the likelihood is then the sum of the likelihood of the individual system (Said and Taghipour, 2016).…”

Section: Mle Approach To Obtain Parametersmentioning

confidence: 99%

Prediction of restoration factor for various maintenance types of railway systems using analytical hierarchy process

Das

Goyal

Gautam

2019

JQME

View full text Add to dashboard Cite

Purpose For repairable systems (RSs), reliability estimation is generally performed using virtual age models. Virtual age models consider the effect of maintenance actions by reducing system age using restoration factor (RF). RF is generally estimated from system failure data using various statistical methods. However, RSs such as railway systems experience various types of maintenance actions at different times during their life cycle. To consider all these different types of actions, we need multiple RFs in the virtual age model. As failure data are limited, the estimation of so many parameters becomes a complex problem and it can lead to erroneous inferences. These RFs are representative of effects of maintenance activities on the system. Therefore, these can be predicted from the information about the maintenance actions performed on the system. The paper aims to discuss these issues. Design/methodology/approach The paper considers different types of maintenance actions to predict RF of the system. These maintenance actions involve the replacement of components at some level of assembly. Each component in an assembly has its own impact on assembly restoration. RF for assembly/systems can be obtained by aggregating effects of multiple component replacement using analytical hierarchy process . The RF values obtained for different types of maintenance actions are then used to calculate the virtual age of the system at different failure points. Using these virtual age failure points, suitable distribution is fitted and parameters are estimated. The distribution and parameters provide information about reliability of the system at any point of time. Findings This paper provides an easier approach that gives different RFs for different types of PM and CM. To calculate RFs, it considers the impact of maintenance actions performed as well as the impact of the component on which they are performed. It is simpler and gives more consistent results than other approaches, which estimate RF using different statistical methods. Originality/value This paper provides an alternative approach to predict RF parameters instead of estimating these parameters using statistical methods. Estimation of parameters using different statistical methods is complex in nature and gives erroneous and inconsistent results. The approach given in this paper is simpler and gives more reliable results. This approach can be useful in estimating parameters for RSs when failure data are limited.

show abstract

Optimization of electrical infrastructures at data centers through a DoE-based approach

2021

View full text Add to dashboard Cite

Modeling failure and maintenance effects of a system subject to multiple preventive maintenance types

Cited by 6 publications

References 10 publications

Evaluating the impact of maintenance policies associated to SLA contracts on the dependability of data centers electrical infrastructures

Evaluating the impact of maintenance policies associated to SLA contracts on the dependability of data centers electrical infrastructures

Prediction of restoration factor for various maintenance types of railway systems using analytical hierarchy process

Optimization of electrical infrastructures at data centers through a DoE-based approach

Contact Info

Product

Resources

About