A joint optimal policy of inspection and age based replacement based on a three-stage failure process

Preventive maintenance (PM) and condition-based maintenance (CBM) are two dominant maintenance policies in industrial applications. Inspection activities are the foundation of PM and CBM policies as to provide the operating information of system through processing the collected vibration data. Age based replacement is one of the most used preventive maintenance policy aiming at avoiding unplanned downtime and higher failure loss. This paper proposes a joint optimal policy of inspection and age based replacement based on a three-stage failure process for a single component system. The three-stage failure process, which is closer to reality, divides the failure process of system into three stages: namely normal, minor defective and severe defective. When the severe defective stage is identified, maintenance action is carried out immediately. The system is replaced once it reaches certain age. However, two potential actions are considered and analyzed in this paper when the minor defective stage is identified: halving the subsequent inspection interval or replacing the item immediately. As inspection may not be perfect because of the complexity of plant items, both perfect and imperfect inspection cases are considered. Finally, a case study is presented to demonstrate the efficiency of the proposed models

Condition-based maintenance—an extensive literature review

This paper presents an extensive literature review on the field of condition-based maintenance (CBM). The paper encompasses over 4000 contributions, analysed through bibliometric indicators and meta-analysis techniques. The review adopts Factor Analysis as a dimensionality reduction, concerning the metric of the co-citations of the papers. Four main research areas have been identified, able to delineate the research field synthetically, from theoretical foundations of CBM; (i) towards more specific implementation strategies (ii) and then specifically focusing on operational aspects related to (iii) inspection and replacement and (iv) prognosis. The data-driven bibliometric results have been combined with an interpretative research to extract both core and detailed concepts related to CBM. This combined analysis allows a critical reflection on the field and the extraction of potential future research directions

Preventive maintenance optimization policy based on a three-stage failure process in finite time horizon

In this paper, a preventive maintenance optimization policy based on a three-stage failure process in finite time horizon is proposed. The lifetime of system is divided into three stages by the concept of three-stage failure process, which is corresponding to the three color scheme commonly used in industry. The subsequent inspection interval is halved when the minor defective stage is identified. Once identifying the severe defective stage, maintenance action is carried out. A numerical example is presented to demonstrate the efficiency of the proposed models

Stochastic modelling of perfect inspection and repair actions for leak-failure prone internal corroded pipelines

To enhance the performance of any facility, reduce cost and failure probability involves proper inspection and repair decisions. To be able to establish the cost of repair and inspection of corroded pipelines at different stages of the corrosion defect depth growth, Markov modelling technique was adopted. This model formulated an inspection and repair technique, which has the potentials of aiding policy makers in maintenance management of internally corroded pipelines. The transition states were determined using the Remaining Useful Life (RUL) of the pipelines whilst Weibull distribution was used for calculating the corrosion wastage rates at the lifecycle transition phases. Monte Carlo simulation and degradation models were applied for determining future corrosion defect depth growth, in a bid to establish periodic inspection and repair procedures and their costs. Data from an onshore pipeline inspected with Magnetic Flux Leakage (MFL) in-Line-Inspection (ILI) technique was used to test the validity of the model. The results obtained indicate that the model has practical applications for inspection and repairs of aged-internally corroded pipelines

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

Maintenance models applied to wind turbines. A comprehensive overview

Producción CientíficaWind power generation has been the fastest-growing energy alternative in recent years, however, it still has to compete with cheaper fossil energy sources. This is one of the motivations to constantly improve the efficiency of wind turbines and develop new Operation and Maintenance (O&M) methodologies. The decisions regarding O&M are based on different types of models, which cover a wide range of scenarios and variables and share the same goal, which is to minimize the Cost of Energy (COE) and maximize the profitability of a wind farm (WF). In this context, this review aims to identify and classify, from a comprehensive perspective, the different types of models used at the strategic, tactical, and operational decision levels of wind turbine maintenance, emphasizing mathematical models (MatMs). The investigation allows the conclusion that even though the evolution of the models and methodologies is ongoing, decision making in all the areas of the wind industry is currently based on artificial intelligence and machine learning models

Preventive maintenance and replacement scheduling : models and algorithms.

Preventive maintenance is a broad term that encompasses a set of activities aimed at improving the overall reliability and availability of a system. Preventive maintenance involves a basic trade-off between the costs of conducting maintenance/replacement activities and the cost savings achieved by reducing the overall rate of occurrence of system failures. Designers of preventive maintenance schedules must weigh these individual costs in an attempt to minimize the overall cost of system operation. They may also be interested in maximizing the system reliability, subject to some sort of budget constraint. In this dissertation, we present a complete discussion about the problem definition and review the literature. We develop new nonlinear mixed-integer optimization models, solve them by standard nonlinear optimization algorithms, and analyze their computational results. In addition, we extend the optimization models by considering engineering economy features and reformulate them as a multi-objective optimization model. We optimize this model by generational and steady state genetic algorithms as well as by a simulated annealing algorithm and demonstrate the computational results obtained by implementation of these algorithms. We perform a sensitivity analysis on the parameters of the optimization models and present a comparison between exact and metaheuristic algorithms in terms of computational efficiency and accuracy. Finally, we present a new mathematical function to model age reduction and improvement factor parameter used in optimization models. In addition, we develop a practical procedure to estimate the effect of maintenance activity on failure rate and effective age of multi component systems

Modelling condition monitoring inspection using the delay-time concept

In the literature on inspection modelling, the failure distribution traditionally plays a fundamental role in model construction in that it is assumed that system failures occur instantly at random time points from new with a known pdf. of time to failure. Numerous models have been built on this basis. However, Professor Christer challenged this traditional idea and proposed the concept of delay time. The idea, which is an essential part of most engineers' experience, assumes that defects do not just appear as failures, but are present for a while before becoming sufficiently obvious to be noticed and declared as failures. The time lapse from when a defect could first be identified at an inspection to consequential failure has been termed the "delay time". It is this idea which can be captured to reveal the nature and scope for preventive maintenance or inspection. It appears that the concept is now being taken up by many other authors. In this thesis, various models for condition monitoring inspection are built on the basis of delay time analysis. Extensions and further developments are made here to enrich the delay-time modelling. Since the distribution of the delay time is important to delay time modelling, a new approach to estimate the delay time distribution is proposed. This technique, which contrasts with the previous subjective data estimation technique, is based upon objective data. Assuming the distribution of the delay time is known, models of condition monitoring inspection are fully discussed for both perfect and imperfect inspections, and for infinite and finite time horizons. Based upon the models for perfect inspection, algorithms are presented to find the optimal solution. Numerical examples are presented in each Chapter to illustrate how models and algorithms work