V. N. A. Naikan

Availability and maintenance cost optimization of a production plant

Discusses the relationship between plant availability and maintenance expenditure and their limiting features. Achieving higher plant availability always necessitates a higher maintenance budget and may not be economically feasible in many cases. Through a mathematical modelling the variation of net income with respect to plant availability has been studied and the limiting availability values have been established. Expressions for optimum availability and maintenance cost have also been obtained. An illustrative example has been worked out.

Maintainability and reliability analysis of a fleet of shovels

Abstract Technological development has enabled the mining industry to deploy more complex and capital-intensive equipment to increase productivity, but inefficient operation and deficient maintenance often prevent utilization of its full capacity. Interest in the maintenance and operational reliability of all capital-intensive equipment has been stimulated by the current emphasis on reducing production costs. The failure and repair patterns of a fleet of four 10-m3 electric rope shovels were analysed statistically to ascertain their reliability and maintainability characteristics. Different subsystems and the types of failures in each subsystem were coded so that the failure and repair data of each subsystem could be collected and sorted and the faults therein classified separately. Common graphical tools, e.g. trend and serial correlation tests, were used to validate the assumption of independent and identically distributed failure/repair data for each subsystem before they were fitted with theoretical probability distributions. Chisquared and K-S tests were carried out with the aid of Statgraphics software to select the best-fit distribution. For most subsystems Weibull and lognormal distributions were found to give the best fit to the failure and repair data, respectively. The reliability and maintainability characteristics of the different subsystems of the shovel and of the shovel as a whole were calculated on the basis of the bestfit distributions. Analysis of the total downtime, breakdown frequency, reliability and maintainability characteristics of different subsystems and the faults in these identified dipper and electrical subsystems as weak links in the chain of subsystems. It was found that the reliability of all four shovels dropped below 50% after 24 h of working and that 25-50% of the total number of failures usually required less time to repair. The analysis of the failure patterns for all four shovels together was employed to calculate maintenance intervals for different values of reliability. These intervals were used to schedule preventive maintenance, i.e. inspection, repair, servicing or replacement, and modify inspection frequencies with reference to safety considerations, cost-effectiveness and the nature of the fault. As expected, this has resulted in a reduction of the total downtime of the shovels.

Condition monitoring strategy : a risk based interval selection

Abstract Condition monitoring (CM) has been widely applied in most of the modern process as well as manufacturing industries as a predictive maintenance tool for incipient fault detection and trouble shooting but the interval at which the measurements are to be taken to achieve the best results has not yet been rationally discussed. This paper suggests a method for designing condition monitoring measurement intervals for all types of machines, from commissioning to replacement, by considering various factors such as risk, interval availability, debugging, useful life and wear-out regions of the failure rate curve, as well as economic factors governing the replacement prospects of the machine

An Optimal Maintenance Policy for Compressor of a Gas Turbine Power Plant

This paper proposes a condition based maintenance policy for compressors of industrial gas turbine. Compressor blade fouling contributes a major performance loss in the operation of gas turbine. Water washing is usually done for recovery of the blade fouling problem. There exist two different washing methods, namely, online and offline washings. Many researchers suggested that performing a combined program of regular online washing plus periodic offline washing would give fruitful results with respect to economy. However, such studies are of empirical nature or have considered only deterministic treatment. Considering the rate of fouling as discrete state random process, we propose a condition based maintenance policy with periodic online washing and inspection directed offline washing. According to this policy, the compressor undergoes regular online washes for every 1∕λm operating hours, and also undergoes inspections at constant rate λI. If the observed condition at an inspection is worse than threshold deterioration state, then perform offline washing. Otherwise, continue with online washing. The proposed algorithm gives optimum schedules for both online washing and inspections considering minimization of total cost per operating hour as objective. It also gives optimum threshold deterioration level for performing offline washing. A comparison of the results for a hypothetical gas turbine compressor is presented as illustration.

Imperfect Repair Proportional Intensity Models for Maintained Systems

The failure processes of a maintained system can be studied from the failure data using imperfect repair models. Additional information on the failure process can also be utilized in the form of covariates using proportional intensity models for getting more realistic results. Both these models can be combined to form imperfect repair proportional intensity models making use of the times to failure and the covariate data together. Such models have been proposed earlier with imperfect repair models using maximal repair baseline intensity. One model GPIM has been proposed using minimal repair baseline intensity. This paper proposes ARA and ARI imperfect repair proportional intensity models using minimal repair baseline intensity. These models are then applied to the field data from an industrial-setting to demonstrate that appropriate parameter estimates for such phenomena can be obtained, and such models are shown to more closely describe the failure processes of a maintained system.

A managerial tool for reliability analysis using a novel Markov System Dynamics (MSD) approach

Abstract System reliability is considered as an important performance index. Performance of engineering systems can be assessed by various techniques. In the traditional analytical techniques a mathematical model is developed to represent the system and to evaluate its reliability indices. There have been attempts in the literature to evolve more realistic techniques using simulation approach for reliability analysis of systems. This paper proposes a hybrid approach called as Markov System Dynamics (MSD) approach which combines the Markov approach with system dynamics simulation approach for reliability analysis and to study the dynamic behavior of systems. This approach will have the advantages of both Markov as well as System dynamics methodologies. The proposed framework is illustrated for a single component system with a numerical example. The results of the simulation when compared with that obtained by traditional Markov analysis clearly validate the Markov System Dynamics (MSD) approach as an alternative approach for reliability analysis.

SEGMENTED POINT PROCESS MODELS FOR MAINTAINED SYSTEMS

A maintained system is generally modeled using point processes. The most common processes used are the renewal process and the non homogeneous Poisson process corresponding to maximal and minimal repair situations with homogeneous Poisson process being a special case of both. A general repair formulation with a factor indicating the degree of repair is introduced into the minimal repair model to form an Arithmetic Reduction of Intensity model. These processes are generally able to model maintained systems with a fair degree of accuracy when the system is operating under stable conditions. However whenever there is a change in the environment these models which are monotonic in nature are not able to accommodate this change. Such systems operating under different environments need to be modelled by segmented models with the system domain divided into segments at the points of changes in the environment. The individual segments can then be modeled by any of the above point process models and these can be combined to form a composite model. This paper proposes a statistical model of such an operating/maintenance environment. Its purpose is to quantify the impacts of changes in the environment on the failure intensities. Field data from an industrial-setting demonstrate that appropriate parameter estimates for such phenomena can be obtained and such models are shown to more accurately describe the maintained system in a changing environment than the single point process models usually used.

Availability modeling of repairable systems using Markov system dynamics simulation

Purpose – The purpose of this paper is to propose a novel hybrid approach called as Markov System Dynamics (MSD) approach which combines the Markov approach with system dynamics (SD) simulation approach for availability modeling and to study the dynamic behavior of repairable systems. Design/methodology/approach – In the proposed approach the identification of the single unit repairable system all possible states has been performed by using the Markov approach. The remaining stages of traditional Markov analysis are highly mathematically intensive. The present work proposes a hybrid approach called as MSD approach which combines the Markov approach with SD simulation approach to overcome some of the limitations of Markov process in a simple and efficient way for availability modeling and to study the dynamic behavior of this system. Findings – The proposed framework is illustrated for a single unit repairable system. The worked out example shows the steady state point and also it gives the point, interval...

Reliability strength design through inverse distributions—exponential and Weibull cases

This paper illustrates the inverse reliability design techniques for exponential and Weibull stress-strength models. Expressions for factor of safety, mean strength and its variability have been derived for a given range of target reliability and external load conditions. In the case of exponential models a global solution has been found out whereas in the case of the Weibull model only some specific cases have been considered. The difficulty in obtaining a global solution in the Weibull model has been discussed with possible methods to attain it.

Sequential detection of change points for maintained systems using segmented point process models

Traditionally a change point model has been used for detection of change points and estimation of parameters, as an off line change detection procedure. A segmented point process model has been used to identify the changes off-line in the failure process of a maintained system, with the process domain divided into segments at the points of change in the failure process, the individual segments being modelled by any of the usual point process models with unknown parameters. This paper proposes the use of the segmented point process model for sequentially identifying a change in the failure process of a maintained system due to a change in its operating/maintenance environment. This method is demonstrated with field data from an industrial setting and its implications for the maintenance of the systems is brought out. Copyright