Reliability Based Methodologies for Optimal Maintenance Policies in Military Aviation (original) (raw)
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International Journal of Mathematical, Engineering and Management Sciences
Reliability analysis of complex multiple repairable systems (MRS) such as aero engines, rolling stocks and nuclear power plants has always been an area of interest for the research fraternity. An appropriate age based overhaul maintenance policy for such systems can provide impetus to the operations. The paper proposes two different age based maintenance policies; Policy-I and Policy-II, to evaluate the overhaul time of an aero engine, where Policy-I considers MRS with imperfect corrective maintenance (CM), whereas Policy-II examines MRS with both imperfect CM and preventive maintenance (PM). The paper then provides a spare parts estimation model for both the policies. The developed policies and spares parts model are validated by considering field failure data of aero engines as a case and the obtained results are compared with the existing time based maintenance policy used for aero engines. The paper recommends the best policy to be used for MRS in general and the considered case...
Maintenance policies with minimal repair and replacement on failures: analysis and comparison
International Journal of Production Research, 2020
The main objective of a maintenance policy consists of conducting maintenance actions at lower costs. This paper proposes an approach for comparing numerically three maintenance strategies, involving minimal repairs at failure, replacement with complete renewal only at the first failure, and replacement with complete renewal at each failure. These strategies are integrated into a modified block replacement policy that includes corrective and preventive maintenances. The approach proceeds by presenting the mathematical models at the component level and at the system level. As the renewal function for generalised Weibull distributions is impossible to obtain, a novel asymptotic algorithm is introduced for estimating the replacements number. However, a multi-component industrial example is proposed for selecting the strategy that minimises the maintenance costs. A sensitivity analysis is performed for comparing an opportunistic maintenance policy with the proposed replacement policy to check if substantial cost reduction still possible. The experiment results show clearly that the third strategy is the most efficient and reduces maintenance costs to a very low level. Finally, we think that the developed study provides a flexible and less costly solution to deal with maintenance decision-making for systems that do not have modern technological equipment to collect data from system breakdowns.
Models for maintenance optimization: a study for repairable systems and finite time periods
Reliability Engineering & System Safety, 2002
The problem of selecting a suitable maintenance policy for repairable systems and for a ®nite time period is presented. Since the late seventies, examples of models assessing corrective and preventive maintenance policies over an equipment life cycle exist in the literature. However, there are not too many contributions regarding real implementation of these models in the industry, considering realistic timeframes and for repairable systems. Modeling this problem requires normally the representation of different corrective and/or preventive actions that could take place at different moments, driving the equipment to different states with different hazard rates.
Analytical method for optimization of maintenance policy based on available system failure data.
An analytical optimization method for preventive maintenance (PM) policy with minimal repair at failure, periodic maintenance, and replacement is proposed for systems with historical failure time data influenced by acurrent PM policy. The method includes a new imperfect PM model based on Weibull distribution and incorporates the current maintenance interval T0 and the optimal maintenance interval T to befound. The Weibull parameters are analytically estimated using maximum likelihood estimation. Based on this model, the optimal number of PM and the optimal maintenance interval for minimizing the expected cost over an infinite time horizon are also analytically determined. A number of examples are presented involving different failure time data and current maintenance intervals to analyze how the proposed analytical optimization method for periodic PM policy performances in response to changes in the distribution of the failure data and the current maintenance interval.
An integrated approach to a condition based maintenance policy and applications
2010
Unexpected system failures pose a significant problem in human safety and health care applications, service and manufacturing sectors, national infrastructure (nuclear power plants and civil structures), and national security (military operations). The main challenges associated with unexpected failures are related to characterizing the failure uncertainty and the stochastic nature of the degradation processes. An accurate failure time prediction and a reliability assessment are necessary if the appropriate maintenance resources (personnel, tools, spare parts, etc.) are to be assembled. For this reason the thesis presents a mathematical framework for integrating degradation-based sensor data streams with high-level logistical decision models. To achieve this goal, a software has been realized in order to simulate a discontinuous operational scenario (such as aircraft operations) in which two different maintenance policies were applied, a scheduled and a condition-based one. The former refers to a typical maintenance policy, in which no prognostic data are available, so that maintenance is scheduled basing only on prior knowledge of components' failure behavior. The latter approach, instead, implements the information given by prognostics in order to fully exploit the component's residual useful life and reduce the lead time to deliver spare parts. The last change is achieved through a revision and a modification of the entire supply chain model in a Just-In-Time-like perspective: thanks to a more precise knowledge of the time to failure, spare parts can be stored in depots so to be in the maintenance zone just before they are needed. Thus, it is possible to move these parts to higher level depots, where hold stocking costs are typically lower. As for prognostics, it has been made possible through the realisation of a RUL estimation algorithm. It is to say that many techniques have been found in literature, but none of them faced the prognostic problem with the aim of finding a closed form for RUL estimation The most promising predictive algorithm, among those developed before this work, turned out to be a Bayesian estimator based on the degradation pattern of the monitored component, under the likely assumption of exponential shape of such pattern. This algorithm has been the starting point for the one developed in this work. Leveraging on Bayesian probability theory, the up-to-date RUL probability density function of the component is evaluated at each time step, starting from the prior knowledge of the component's residual life, a stochastic parameter that is evaluated from experimental tests always done before commissioning. The ________________________________________________________________ information about RUL prediction was then used to define the optimal moment at which scheduling and performing maintenance. These values were found through an objective function optimization that took into account the main drivers associated to condition-based maintenance decision making process. Furthermore the opportunity to introduce CBM (condition based maintenance) concepts based on prognostic into a cracked railway axle management is investigated. The performances of two different prognostic algorithm are assessed on the basis of their RUL (remaining useful life) predictions accuracy. The CBM approach is compared to the classical preventive maintenance approach to railway axle maintenance management based on expensive and regular NDT. The effect of monitoring frequency and the monitoring infrastructure size error is assessed as well.
The South African Journal of Industrial Engineering, 2015
Asset and maintenance managers are often confronted with difficult decisions related to asset replacement or repair. Various analytical models, such as decision analysis and simulation, can assist a manager in making better decisions. This paper proposes that by combining renewal theory with decision analysis methods, the expected value (EV) of information for non-repairable components can be calculated. Subsequently, it is proposed that this method can be used to determine the expected replacement cost per unit time of predictive maintenance. It is argued that this predicted cost will give the maintenance decision-maker the ability to compare it to the cost of alternative maintenance strategies when choosing between strategies. Although this paper is limited to non-repairable components, the theory and methodology can also be applied to repairable systems.
Pesquisa Operacional, 2009
The use of stochastic point processes to model the reliability of repairable systems has been a regular approach to establish survival measures in failure versus repair scenarios. However, the traditional processes do not consider the actual state in which an item returns to operational condition. The traditional renewal process considers an "as-good-as-new" philosophy, while a non-homogeneous Poisson process is based on the minimal repair concept. In this work, an approach based on the concept of Generalized Renewal Process (GRP) is presented, which is a generalization of the renewal process and the non-homogeneous Poisson process. A stochastic modeling is presented for systems availability analysis, including testing and/or preventive maintenances scheduling. To validate the proposed approach, it was performed a case study of a hypothetical auxiliary feed-water system of a nuclear power plant, using genetic algorithm as optimization tool.
A considerable amount of valuable operational life of an frontline aircraft can be conserved and effectively utilized for routine operational requirements, if component replacement downtime can be avoided during the operational cycle of an frontline aircraft. Component replacement downtime compounds to the existing scheduled routine maintenance downtimes and at times it extends much longer as certain critical components replacements warrants for a series of post replacement checks during flying prior declaring aircraft fit for routine operational commitments without restrictions. Hence optimal scheduling of the component replacement periodicity or avoiding component replacement during aircraft operational life always contribute to the increase in the operational exploitation of an frontline aircraft. This paper discusses the various downtime associated with the routine aircraft inspections during the operational cycle of aircraft. The paper also provides a brief on the various methods and tools prescribed in Maintenance Repair and Overhaul agencies undertaking major overhaul / inspection of aircraft in scheduling the component life, with an aim to achieve increased operational exploitation time during frontline exploitation.
Reliability Analysis in the Formulating Of Maintenance Program
IOSR Journal of Mechanical and Civil Engineering, 2014
Over the years, modern maintenance cost has gradually built up, often frighteningly outpacing material or labor costs in cost of production. This is however brought about the need to develop new maintenance strategies that can effectively reduce the cost, while at the same time adequately maintain the integrity of the equipment, this work takes a look at various concepts of reliability such as Fault Tree Analysis (FTA). Failure Mode and Effect Analysis (FMAE), Reliability Centered Maintenance (RCM), the usefulness of data associated concepts such as MeanTime To Failure (MTTF), instantaneous failure rate, lifetime of components and others in uncovering the root causes of the failure associated with an Ingersoll-Rand compressor.
Reliability Engineering & System Safety, 2019
This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. Highlights Estimated the availability of components with universal generating function Developed model for component availability using failure and maintenance rates Estimated the expected future assets integrity via maintenance actions Predicted availability by considering-no, minor and major maintenance actions