Babakalli Alkali

Scheduling preventive maintenance for oil pumps using generalized proportional intensities models

Percy and Alkali presented generalizations of the proportional intensities model introduced by Cox. They identified several features of these models that are particularly relevant for modelling complex repairable systems subject to preventive maintenance (PM). These include the baseline intensity, scaling factors and explanatory variables. We investigate these aspects in detail and apply the models to five sets of reliability data collected from the main pumps at oil refineries. We use likelihood methods to estimate the model parameters and compare how well the models fit the data. Our analyses suggest that a log-linear baseline intensity function performs well and that an exponential deterministic scaling function is useful for corrective maintenance. The inclusion of explanatory variables to represent the quality of last maintenance and time since last maintenance also proves to be beneficial. We develop algorithms for simulating the reliability behaviour of a complex repairable system into the future, in order to schedule appropriate maintenance activities, identifying special cases that simplify the algebra. Applying these methods to the oil pump data, we derive recommendations for PM plans and demonstrate that adopting this strategy can lead to substantial savings.

Analysis of Significant Factors on Cable Failure Using the Cox Proportional Hazard Model

This paper proposes the use of the Cox proportional hazard model (Cox PHM), a statistical model, for the analysis of early-failure data associated with power cables. The Cox PHM analyses simultaneously a set of covariates and identifies those which have significant effects on the cable failures. In order to demonstrate the appropriateness of the model, relevant historical failure data related to medium voltage (MV, rated at 10 kV) distribution cables and High Voltage (HV, 110 kV and 220 kV) transmission cables have been collected from a regional electricity company in China. Results prove that the model is more robust than the Weibull distribution, in that failure data does not have to be homogeneous. Results also demonstrate that the method can single out a case of poor manufacturing quality with a particular cable joint provider by using a statistical hypothesis test. The proposed approach can potentially help to resolve any legal dispute that may arise between a manufacturer and a network operator, in addition to providing guidance for improving future practice in cable procurement, design, installations and maintenance.

Competing risks and opportunistic informative maintenance

The present paper makes a link between the literature on competing risks and that of opportunistic maintenance. Three models for competing risk involving censoring through opportunistic maintenance are discussed. One is an existing opportunistic maintenance model, one is a new opportunistic variant on an existing competing risk model, and the third is a new model that captures the notion of opportunistic informative maintenance. These models show that even though opportunities may occur according to a process that is independent of the failure process, the appropriate competing risk models may still involve dependencies. This work was motivated by observation of practices in a coal-fired power plant consisting of four generating units, which is briefly described. Through simulation examples it is shown how these competing risk models can be used to support decision making about maintenance rules, and the identifiability issues associated with the models are discussed. Competing risk theory addresses statistical estimation problems which are a common concern in much of the maintenance literature, and focuses attention on non-age-related information available to maintainers.

Analysis of cable failure modes and cable joint failure detection via sheath circulating current

Power cables are preferred in urban areas for power transmission and distribution because of their high reliability, environmental friendliness and the visual invisibility. Whilst the volume of underground power cable has been growing steadily, the voltage level of the power cables have also increased significantly in recent years. The increasing volume of high voltage power cables brings about technical challenges to the power system operators and maintenance engineers. One of these challenges is the application of appropriate condition monitoring techniques to detect incipient cable faults and to reduce unplanned outages. This paper aims to analyse the causes, modes and mechanisms, among cable joint failures, and to propose an applicable sheath circulating current monitoring technique with the associated criteria for fault diagnosis. Two joint faults, flooded link box and joint insulation breakdown, are analysed in detail. Finally, a set of criteria is proposed for cable joint fault diagnosis based on the simulation of an 110kV underground power cable system of length 1.5km.

Evaluation of Generalised Proportional Intensities Models with Application to the Maintenance of Gas Turbines

In this paper generalised proportional intensities models are fitted to gas turbine generator failure and maintenance data. The systems of interest have identical maintenance procedures and information about preventive maintenance (PM) and corrective maintenance (CM) activities is known. Closed-form maximum log-likelihood estimates of the model parameters are evaluated, and the model goodness-of-fit is measured. A simulation study is conducted to determine an optimal cost effective PM schedule. Our analysis and results facilitate decision support for determining the cost-optimal maintenance strategy. Copyright

Competing Risks in Reliability

Competing risks models are used to analyze operational field data in reliability. They assume that different failure risks and maintenance events compete with one another to be the cause of the system being taken out of service. These risks censor each other and it is because of this censoring that problems arise when trying to identify marginal distributions for the time to failure. These problems can only be surmounted by making assumptions about the underlying dependencies between the competing risks variables, requiring a deeper understanding of the maintenance policies in place. Keywords: competing risks; identifiability; marginal distribution; dependence; subsurvivor functions; subdistributions

Reliability modelling and analysis of a single machine subsystem of a cable plant

This paper presents a real case analysis of a single machine subsystem of a cable plant using reliability modelling. Real maintenance data of a cable plant are collected for this purpose. Three types of maintenance are noted for the subsystem: repair, preventive maintenance random (PMR) and preventive maintenance scheduled (PMS). The subsystem is repaired upon failure, while preventive maintenance (PM) is carried out at random and scheduled basis. Optimum reliability indices such as mean time to subsystem failure (MTSF), availability of the subsystem, expected busy period of the repairman and expected number of subsystem repairs are obtained. Analysis is done using semi Markov processes and regenerative point techniques.

Failure prediction of power cables using failure history and operational conditions

This paper classifies the causes of cable failures according to two types: unpredictable random causes; and predictable ageing effects. A piecewise power-law non-homogeneous Poisson process and a stochastic electro-thermal model are proposed to predict total annual failures and failures due specifically to ageing, respectively. An amalgamation of the two models is then used to estimate the number of failures attributable to random causes or ageing. The proposed method is successfully applied to real data of vintage unjacketed XLPE cables. The results show that these cables have an expected lifespan of 39 years based on ageing effects alone; however, failure of these cables is dominated by random failure modes such as manufacturing defects, sudden shock, or water and electrical tree, which cause many of these cables to fail earlier in their life.

Alignment model for trunk road network maintenance outsourcing

Abstract.Road maintenance outsourcing is now the foremost strategy by which road authorities procure maintenance works. Despite growing application of road maintenance outsourcing, there are conflicting estimates on the effectiveness of road maintenance outsourcing and shortage of appropriate models to align over optimistic expectations of road authorities from road maintenance outsourcing with substantiated benefits. This paper investigates the efficacy of road maintenance outsourcing. In this paper, the different variants of road maintenance outsourcing and road maintenance works are evaluated with a SWOT analysis and a comprehensive literature review respectively. In addition, a road maintenance outsourcing alignment model based on a decision tree and Balance Score Card is proposed and illustrated with a Nigerian trunk road network authority as a case study. The result of the SWOT analysis and comprehensive literature review establishes fresh insight into road maintenance outsourcing dynamics. The pres...

Maintenance engineering management of a LNG plant critical system: a case study of gas turbine dry gas seal

This paper focuses on maintenance management of critical equipment of a New Liquefied Natural Gas (LNG) plant. The challenges associated with the risk of failure affect the operational conditions of the plant equipment, and also the recommendations by the original equipment manufacturer (OEM) to maintain critical system is a difficult task. In this paper a case study of a new gas turbine design within an LNG plant is considered. The maintenance cost, operation and availability are some of the most important concerns to the gas turbine operators. Majority of the gas turbine maintenance are related to the replacement and repair of hot section static parts. A review of the operating and maintenance practices for heavy-duty gas turbines and others critical equipment, with emphasis placed on the types of inspections and factors that influence maintenance schedules is presented. The Reliability Centred Maintenance (RCM) modeling and criticality analysis approach is used to analyse historical failure and maintenance data. To compliment the accuracy of data information careful consultation with the operators is conducted and we test the goodness of fit of using a Weibull model for the analysis. A maintenance optimisation model is discussed and an attempt is made to model the failure pattern to determine and recommend cost effective maintenance management schedule for the gas turbine dry gas seal.