Modeling Preventive Maintenance in Complex Systems

This thesis presents an explicit consideration of the impacts of modeling decisions on the resulting maintenance planning. Incomplete data is common in maintenance planning, but is rarely considered explicitly. Robust optimization aims to minimize the impact of uncertainty--here, in contrast, I show how its impact can be explicitly quantified. Doing so allows decision makers to determine whether it is worthwhile to invest in reducing uncertainty about the system or the effect of maintenance. The thesis consists of two parts. Part I uses a case study to show how incomplete data arises and how the data can be used to derive models of a system. A case study based on the US Navy\u27s DDG-51 class of ships illustrates the approach. Analysis of maintenance effort and cost against time suggests that significant effort is expended on numerous small unscheduled maintenance tasks. Some of these corrective tasks are likely the result of deferring maintenance, and, ultimately decreasing the ship reliability. I use a series of graphical tests to identify the underlying failure characteristics of the ship class. The tests suggest that the class follows a renewal process, and can be modeled as a single unit, at least in terms of predicting system lifetime. Part II considers the impact of uncertainty and modeling decisions on preventive maintenance planning. I review the literature on multi-unit maintenance and provide a conceptual discussion of the impact of deferred maintenance on single and multi-unit systems. The single-unit assumption can be used without significant loss of accuracy when modeling preventive maintenance decisions, but leads to underestimating reliability and hence ultimately performance impacts in multi-unit systems. Next, I consider the two main approaches to modeling maintenance impact, Type I and Type II Kijima models and investigate the impact of maintenance level, maintenance interval, and system quality on system lifetime. I quantify the net present value obtained of the system under different maintenance strategies and show how modeling decisions and uncertainty affect how closely the actual system and maintenance policy approach the maximum net present value. Incorrect assumptions about the impact of maintenance on system aging have the most cost, while assumptions about design quality and maintenance level have significant but smaller impact. In these cases, it is generally better to underestimate quality, and to overestimate maintenance level

An Investigation Into the Economic Useful Life of Commercial Aircraft as Impacted by Maintenance and Economic Variables

This research involved examining the economic useful life of commercial aircraft and the impact of maintenance and economic variables on the viability and longevity of the asset. The data sample consisted of the entire population of Boeing commercial aircraft produced between 1956 and 2021. The objective was to determine the effect of both maintenance and economic variables on the longevity and usefulness of commercial aircraft. As manufacturers work with issues such as service life, economic life, safety, and critical design features, those in the aviation community focus on the operational side of the equation––how long can one operate the asset, and at what point is it no longer effective to continue investing into the asset? The research presents an extensive review of the maintenance and technological advances in commercial aircraft over the last 60 years and an investigation of various aspects of the economic useful life concept in both use and application from an appraisal and industry perspective. The research focus is on the actual age at which an asset is removed from operational service and the underlying causes of such a decision

Modelo de apoio à decisão para a manutenção condicionada de equipamentos produtivos

Doctoral Thesis for PhD degree in Industrial and Systems EngineeringIntroduction: This thesis describes a methodology to combine Bayesian control chart and CBM (Condition-Based Maintenance) for developing a new integrated model. In maintenance management, it is a challenging task for decision-maker to conduct an appropriate and accurate decision. Proper and well-performed CBM models are beneficial for maintenance decision making. The integration of Bayesian control chart and CBM is considered as an intelligent model and a suitable strategy for forecasting items failures as well as allow providing an effectiveness maintenance cost. CBM models provides lower inventory costs for spare parts, reduces unplanned outage, and minimize the risk of catastrophic failure, avoiding high penalties associated with losses of production or delays, increasing availability. However, CBM models need new aspects and the integration of new type of information in maintenance modeling that can improve the results. Objective: The thesis aims to develop a new methodology based on Bayesian control chart for predicting failures of item incorporating simultaneously two types of data: key quality control measurement and equipment condition parameters. In other words, the project research questions are directed to give the lower maintenance costs for real process control. Method: The mathematical approach carried out in this study for developing an optimal Condition Based Maintenance policy included the Weibull analysis for verifying the Markov property, Delay time concept used for deterioration modeling and PSO and Monte Carlo simulation. These models are used for finding the upper control limit and the interval monitoring that minimizes the (maintenance) cost function. Result: The main contribution of this thesis is that the proposed model performs better than previous models in which the hypothesis of using simultaneously data about condition equipment parameters and quality control measurements improve the effectiveness of integrated model Bayesian control chart for Condition Based Maintenance.Introdução: Esta tese descreve uma metodologia para combinar Bayesian control chart e CBM (Condition- Based Maintenance) para desenvolver um novo modelo integrado. Na gestão da manutenção, é importante que o decisor possa tomar decisões apropriadas e corretas. Modelos CBM bem concebidos serão muito benéficos nas tomadas de decisão sobre manutenção. A integração dos gráficos de controlo Bayesian e CBM é considerada um modelo inteligente e uma estratégica adequada para prever as falhas de componentes bem como produzir um controlo de custos de manutenção. Os modelos CBM conseguem definir custos de inventário mais baixos para as partes de substituição, reduzem interrupções não planeadas e minimizam o risco de falhas catastróficas, evitando elevadas penalizações associadas a perdas de produção ou atrasos, aumentando a disponibilidade. Contudo, os modelos CBM precisam de alterações e a integração de novos tipos de informação na modelação de manutenção que permitam melhorar os resultados.Objetivos: Esta tese pretende desenvolver uma nova metodologia baseada Bayesian control chart para prever as falhas de partes, incorporando dois tipos de dados: medições-chave de controlo de qualidade e parâmetros de condição do equipamento. Por outras palavras, as questões de investigação são direcionadas para diminuir custos de manutenção no processo de controlo.Métodos: Os modelos matemáticos implementados neste estudo para desenvolver uma política ótima de CBM incluíram a análise de Weibull para verificação da propriedade de Markov, conceito de atraso de tempo para a modelação da deterioração, PSO e simulação de Monte Carlo. Estes modelos são usados para encontrar o limite superior de controlo e o intervalo de monotorização para minimizar a função de custos de manutenção.Resultados: A principal contribuição desta tese é que o modelo proposto melhora os resultados dos modelos anteriores, baseando-se na hipótese de que, usando simultaneamente dados dos parâmetros dos equipamentos e medições de controlo de qualidade. Assim obtém-se uma melhoria a eficácia do modelo integrado de Bayesian control chart para a manutenção condicionada

Innovation for maintenance technology improvements

A group of 34 submitted entries (32 papers and 2 abstracts) from the 33rd meeting of the Mechanical Failures Prevention Group whose subject was maintenance technology improvement through innovation. Areas of special emphasis included maintenance concepts, maintenance analysis systems, improved maintenance processes, innovative maintenance diagnostics and maintenance indicators, and technology improvements for power plant applications

RELIABILITY CENTERED MAINTENANCE (RCM) FOR ASSET MANAGEMENT IN ELECTRIC POWER DISTRIBUTION SYSTEM

The purpose of Maintenance is to extend equipment life time or at least the mean time to the next failure. Asset Maintenance, which is part of asset management, incurs expenditure but could result in very costly consequences if not performed or performed too little. It may not even be economical to perform it too frequently. The decision therefore, to eliminate or minimize the risk of equipment failure must not be based on trial and error as it was done in the past. In this thesis, an enhanced Reliability-Centered Maintenance (RCM) methodology that is based on a quantitative relationship between preventive maintenance (PM) performed at system component level and the overall system reliability was applied to identify the distribution components that are critical to system reliability. Maintenance model relating probability of failure to maintenance activity was developed for maintainable distribution components. The Markov maintenance Model developed was then used to predict the remaining life of transformer insulation for a selected distribution system. This Model incorporates various levels of insulation deterioration and minor maintenance state. If current state of insulation ageing is assumed from diagnostic testing and inspection, the Model is capable of computing the average time before insulation failure occurs. The results obtained from both Model simulation and the computer program of the mathematical formulation of the expected remaining life verified the mathematical analysis of the developed model in this thesis. The conclusion from this study shows that it is beneficial to base asset management decisions on a model that is verified with processed, analysed and tested outage data such as the model developed in this thesis

HOW IMPROVED CORROSION CONTROL PRACTICES IN THE U.S. NAVY'S ARLEIGH BURKE CLASS DESTROYER ENGINEERING SPACES MIGHT ENHANCE SHIP EFFICIENCY WHILE OPERATING

This research attempted to answer how improved corrosion-control practices in the U.S. Navy’s Arleigh Burke Class Destroyer engineering spaces might enhance ship efficiency. It can be confidently stated that effective corrosion control in Arleigh Burke Destroyer engineering spaces clearly enhances ship efficiency. A semi-systematic review of the literature was used as a methodology. Data were mined using a Synthesis Matrix that isolated meta-narratives that were used later in a meta-analysis of the literature. The identified meta-narratives led to eleven emerging patterns. These patterns were condensed into six major themes and finally synthesized into two primary categories: corrosion control and ship efficiency. Although no causal relationships were proven, strong interrelationships were identified. The findings of this research recommend that in order to control corrosion and enhance ship efficiency, two strategies should be followed: 1) an implemented maintenance plan requiring training for the crew in techniques and knowledge acquisition that promote understanding of the science of corrosion and 2) decisions regarding materials selection, surface coatings, and corrosion control should be made with total ownership costs in mind, because for a ship to function efficiently it must be operational a majority of its work life.Lieutenant, United States NavyApproved for public release. Distribution is unlimited

Mathematical maintenance models of vehicles’ equipment

Dissertation for obtaining a scientific degree of Doctor of Philosophy within the specialty 05.22.20 «Maintenance and repair of vehicles». – National Aviation University, Kyiv, 2018.The thesis addresses the critical scientific problem of creating the appropriate maintenance models for digital avionics systems and degrading equipment of vehicles, which increases the operational effectiveness of such systems significantly. The thesis research includes the analysis of the current state and models of digital avionics maintenance. The study describes the necessity for developing the mathematical maintenance models for redundant digital avionics systems, considering the discontinuous nature of their operation, continuous nature of in-flight testing, possibility of both permanent and intermittent failures and organization of several maintenance levels using various diagnostic tools for detecting both failure types. Another focus of the thesis is the analysis of modern trends and mathematical models of condition-based maintenance (CBM) of vehicles’ equipment. The necessity of developing new CBM mathematical models for degrading equipment of vehicles, considering the probabilities of correct and incorrect decisions when checking system suitability for use in the upcoming operation interval, and the possibility of joint determination of the optimum inspection schedule and replacement thresholds for systems that affect and do not affect safety have been substantiated. The scientific novelty of the primary results obtained in the course of the thesis research is as follows: 1. For the first time, mathematical models to evaluate the operational reliability indicators of continuously monitored line replaceable units/line replaceable modules (LRUs/LRMs) and redundant avionics systems over both finite and infinite time interval, which, unlike known models, consider the characteristics of both permanent and intermittent 2failures, have been developed. These models allow evaluating the impact of intermittent failures on the availability and mean time between unscheduled removals (MTBUR) of LRU/LRM. 2. For the first time, generalized expressions to calculate the average maintenance costs of redundant avionics systems, considering the impact of permanent and intermittent failures, have been developed for alternative maintenance options that differ by the number of maintenance levels (one, two or three), which allows choosing the optimal maintenance option during warranty and post-warranty periods. 3. For the first time, a mathematical model of CBM, based on condition monitoring at scheduled times has been developed, which, unlike the known models, considers the probabilities of correct and incorrect decisions made when checking system suitability. This model allows formulating the criteria of determining the optimal replacement threshold for each inspection time and substantially reduce the likelihood of system failure in the forthcoming interval of operation. 4. For the first time, generalized mathematical expressions to calculate the effectiveness indicators of CBM over a finite time interval, as well as the criteria of joint optimization of the inspection schedule and replacement thresholds for systems that affect or do not affect the safety, have been developed. These results allow significantly improve the availability, reduce average maintenance costs and reduce the number of inspections. The practical value of the results obtained in the thesis is as follows: 1. The techniques to calculate probabilistic and time-related indicators of maintenance effectiveness for digital avionics LRUs/LRMs over finite and infinite operating intervals have been developed. The proposed procedures allow to estimate the availability, operational reliability function (ORF), and mean time between unscheduled removals (MTBUR) of LRUs/LRMs during warranty and post-warranty maintenance periods for both federated avionics (FA) and integrated modular avionics (IMA) architectures; 2. A technique for minimizing the warranty maintenance cost of the redundant digital avionics systems has been developed, demonstrating (through the example of the ADIRS system of the Airbus A380 aircraft) that in the case of the optimal option of warranty maintenance, the average maintenance cost per aircraft decreases by 28 %; 33. A technique for minimizing the post-warranty maintenance cost of the redundant digital avionics systems has been developed. It demonstrates (through the example of the ADIRS system of the Airbus A380 aircraft) that a three-level maintenance option with an intermittent fault detector (IFD) at I and D levels, is optimal as it reduces the total expected maintenance costs by 11 times compared to a one-level option, and by over 8.5 times compared to a two-level option without IFD; 4. A technique for determining the optimal replacement thresholds when monitoring the condition of the degrading system at scheduled times has been developed, which allows to significantly reduce the system failure probability in the forthcoming interval of operation. 5. A technique for joint determination of the optimal replacement threshold and periodicity of suitability checking when monitoring the system condition has been developed, which allows to substantially increase the availability of systems while significantly reducing the number of inspections. The results of the thesis research may be used in the development and maintenance of FA and IMA systems, as well as degrading equipment of vehicles

A framework development to predict remaining useful life of a gas turbine mechanical component

Power-by-the-hour is a performance based offering for delivering outstanding service to operators of civil aviation aircraft. Operators need to guarantee to minimise downtime, reduce service cost and ensure value for money which requires an innovative advanced technology for predictive maintenance. Predictability, availability and reliability of the engine offers better service for operators, and the need to estimate the expected component failure prior to failure occurrence requires a proactive approach to predict the remaining useful life of components within an assembly. This research offers a framework for component remaining useful life prediction using assembly level data. The thesis presents a critical analysis on literature identifying the Weibull method, statistical technique and data-driven methodology relating to remaining useful life prediction, which are used in this research. The AS-IS practice captures relevant information based on the investigation conducted in the aerospace industry. The analysis of maintenance cycles relates to the examination of high-level events for engine availability, whereby more communications with industry showcase a through-life performance timeline visualisation. Overhaul sequence and activities are presented to gain insights of the timeline visualisation. The thesis covers the framework development and application to gas turbine single stage assembly, repair and replacement of components in single stage assembly, and multiple stage assembly. The framework is demonstrated in aerospace engines and power generation engines. The framework developed enables and supports domain experts to quickly respond to, and prepare for maintenance and on-time delivery of spare parts. The results of the framework show the probability of failure based on a pair of error values using the corresponding Scale and Shape parameters. The probability of failure is transformed into the remaining useful life depicting a typical Weibull distribution. The resulting Weibull curves developed with three scenarios of the case shows there are components renewals, therefore, the remaining useful life of the components are established. The framework is validated and verified through a case study with three scenarios and also through expert judgement