Optimal maintenance time for imperfect maintenance actions on repairable product

[[abstract]]This paper develops a maintenance strategy for repairable products that combines imperfect maintenance actions at pre-scheduled times and minimal repair actions for failures. Under a power law process of failures, an expected total cost is developed that involves the sum of the total cost of imperfect preventive maintenances and the expected total cost of minimal repairs. Moreover, a searching procedure is provided to determine the optimal maintenance schedule within a finite time span of warranty. When the parameters of the power law process are unknown, the accuracy of the estimated maintenance schedule is evaluated based on data through an asymptotic upper bound for the difference of the true expected total cost and its estimate. The proposed method is applied to an example regarding the maintenance of power transformers and the performance of the proposed method is investigated through a numerical study. Numerical results show that the proposed maintenance strategy could save cost whether an imperfect maintenance action or the perfect maintenance action is implemented.[[journaltype]]國外[[incitationindex]]SCI[[booktype]]紙本[[countrycodes]]GB

Optimal Burn-in Time and Imperfect Maintenance Strategy for a Warranted Product with Bathtub Shaped Failure Rate

‘Burn-in/preventive maintenance’ programme is an efficient approach used to minimise the warranty servicing cost of a product with bathtub shaped failure rate. Burn-in is a widely used method to improve the quality of product during its ‘infant mortality’ period and preventive maintenance is a scheduled necessary activity carried out during its ‘wear-out’ period. In this paper, an optimisation model is developed to determine the optimal burn-in time and optimal imperfect preventive maintenance strategy that minimises the total mean servicing cost of a warranted product with an age-dependent repair cost. We provide a numerical study to illustrate our results

Modeling and Analysis of Effective Ways for Improving the Reliability of Second-hand Products Sold with Warranty

Often, customers are uncertain about the performance and durability of the used/second-hand products. The warranties play an important role in reassuring the buyer. Offering the warranty implies that the dealer incurs additional costs to service any claims made by the customers. Reducing warranty costs is an issue of great interest to dealers. One way of improving the reliability and reducing the warranty servicing cost for second-hand items is through actions such as overhaul and upgrade which are carried out by the dealer or a third party. Improving actions allow the dealer to offer better warranty terms and to sell the item at a higher price. This paper deals with two effective approaches (virtual age approach and screening test approach) to decide on the reliability improvement strategies for second-hand products sold under various warranty policies (failure-free, rebate warranty, and a combination of free replacement and lump sum). A numerical example illustrates that from a dealer’s point of view, it is beneficial to carry out an improvement action only if the reduction in the warranty servicing cost is greater than the extra cost incurred due to this improvement action

A unified methodology of maintenance management for repairable systems based on optimal stopping theory

This dissertation focuses on the study of maintenance management for repairable systems based on optimal stopping theory. From reliability engineering’s point of view, all systems are subject to deterioration with age and usage. System deterioration can take various forms, including wear, fatigue, fracture, cracking, breaking, corrosion, erosion and instability, any of which may ultimately cause the system to fail to perform its required function. Consequently, controlling system deterioration through maintenance and thus controlling the risk of system failure becomes beneficial or even necessary. Decision makers constantly face two fundamental problems with respect to system maintenance. One is whether or when preventive maintenance should be performed in order to avoid costly failures. The other problem is how to make the choice among different maintenance actions in response to a system failure. The whole purpose of maintenance management is to keep the system in good working condition at a reasonably low cost, thus the tradeoff between cost and condition plays a central role in the study of maintenance management, which demands rigorous optimization. The agenda of this research is to develop a unified methodology for modeling and optimization of maintenance systems. A general modeling framework with six classifying criteria is to be developed to formulate and analyze a wide range of maintenance systems which include many existing models in the literature. A unified optimization procedure is developed based on optimal stopping, semi-martingale, and lambda-maximization techniques to solve these models contained in the framework. A comprehensive model is proposed and solved in this general framework using the developed procedure which incorporates many other models as special cases. Policy comparison and policy optimality are studied to offer further insights. Along the theoretical development, numerical examples are provided to illustrate the applicability of the methodology. The main contribution of this research is that the unified modeling framework and systematic optimization procedure structurize the pool of models and policies, weed out non-optimal policies, and establish a theoretical foundation for further development

Modeling Information Reliability and Maintenance: A Systematic Literature Review

Operating a business efficiently depends on effective everyday decision-making. In turn, those decisions are influenced by the quality of data used in the decision-making process, and maintaining good data quality becomes more challenging as a business expands. Protecting the quality of the data and the information it generates is a challenge faced by many companies across all industrial sectors. As companies begin to use data from these large data bases they will need to begin to develop strategies for maintaining and assessing the reliability of the information they generate using this data. A considerable amount of literature exists on data quality but minimal amounts of information exist on information reliability and maintenance. For these reasons, it is important to study the current methods used by businesses to maintain desired levels of data and information quality. The purpose of this paper is to describe and assess the available knowledge relating data quality, reliability and maintenance by performing a systematic literature review in these areas

Selective maintenance optimisation for series-parallel systems alternating missions and scheduled breaks with stochastic durations

This paper deals with the selective maintenance problem for a multi-component system performing consecutive missions separated by scheduled breaks. To increase the probability of successfully completing its next mission, the system components are maintained during the break. A list of potential imperfect maintenance actions on each component, ranging from minimal repair to replacement is available. The general hybrid hazard rate approach is used to model the reliability improvement of the system components. Durations of the maintenance actions, the mission and the breaks are stochastic with known probability distributions. The resulting optimisation problem is modelled as a non-linear stochastic programme. Its objective is to determine a cost-optimal subset of maintenance actions to be performed on the components given the limited stochastic duration of the break and the minimum system reliability level required to complete the next mission. The fundamental concepts and relevant parameters of this decision-making problem are developed and discussed. Numerical experiments are provided to demonstrate the added value of solving this selective maintenance problem as a stochastic optimisation programme

Optimal cost and availability replacement models for multi-component systems

Dans ce travail une stratégie de maintenance préventive est proposée pour un système multi composants. Cette stratégie suggère d'effectuer des remplacements préventifs de certains composants du système à tous les s unités de temps. Si une défaillance accidentelle survenait, une réparation minimale est aussitôt entreprise pour ramener le système défaillant en état d'opération sans affecter son taux de panne. Après n remplacements préventifs, le système est remis à neuf. La stratégie considérée est alors définie par deux paramètres n et s. A chaque action de maintenance, on associe une durée et un coût. Deux modèles mathématiques ont été développés pour déterminer le couple optimal (s*, n*). Le premier modèle permet de trouver le couple (s*, n*) qui minimise le coût total moyen sur un horizon infini. Le second modèle permet de déterminer le couple optimal (s*, n*) qui maximise la disponibilité stationnaire du système. Des procédures numériques ont été mises au point pour traiter les deux modèles. Plusieurs résultats numériques ont été obtenus. La stratégie proposée peut s'appliquer à plusieurs systèmes multi composants. Les modèles analytiques développés peuvent servir de base au développement de nouvelles stratégies. Un modèle d'optimisation permettant de déterminer le couple (s*, n*) qui permet de respecter un seuil de disponibilité requis, à coût minimal, est actuellement en phase de développement

Some contributions to modeling usage sensitive warranty servicing strategies and their analyses

Providing a warranty as a part of a product\u27s sale is a common practice in industry. Parameters of such warranties (e.g., its duration limits, intensity of use) must be carefully specified to ensure their financial viability. A great deal of effort has been accordingly devoted in attempts to reduce the costs of warranties via appropriately designed strategies to service them. many such strategies, that aim to reduce the total expected costs of the warrantor or / and are appealing in other ways such as being more pragmatic to implement - have been suggested in the literature. Design, analysis and optimization of such servicing strategies is thus a topic of great research interest in many fields. In this dissertation, several warranty servicing strategies in two-dimensional warranty regimes, typically defined by a rectangle in the age-usage plane, have been proposed, analyzed and numerically illustrated. Two different approaches of modeling such usage sensitive warranty strategies are considered in the spirit of Jack, Iskandar and Murthy (2009) and Iskandar (2005). An `Accelerated Failure Time\u27 (AFT) formulation is employed to model product degradation resulting due to excessive usage rate of consumers. The focus of this research is on the analysis of warranty costs borne by the manufacturer (or seller or third party warranty providers) subject to various factors such as product\u27s sale price, consumer\u27s usage rate, types and costs of repair actions. By taking into account the impact of the rate of use of an item on its lifetime, a central focus of our research is on warranty cost models that are sensitive to the usage rate. Specifically, except the model in Chapter 4 where the rate at which an item is used is considered to be a random variable; all other warranty servicing policies that we consider, have usage rate as a fixed parameter, and hence are policies conditional on the rate of use. Such an approach allows us to examine the impact of a consumer\u27s usage rate on the expected warranty costs. For the purpose of designing warranties, exploring such sensitivity analysis may in fact suggest putting an upper limit on the rate of use within the warranty contract, as for example in case of new or leased vehicle warranties. A Bayesian approach of modeling 2-D Pro-rated warranty (PRW) with preventive maintenance is considered and explored in the spirit of Huang and Fang (2008). A decision regarding the optimal PRW proportion (paid by the manufacturer to repair failed item) and optimal warranty period that maximizes the expected profit of the rm under different usage rates of the consumers is explored in this research. A Bayesian updating process used in this context combines expert opinions with market data to improve the accuracy of the parameter estimates. The expected profit model investigated here captures the impact of juggling decision variables of 2-D pro-rated warranty and investigates the sensitivity of the total expected profit to the extent of mis-specification in prior information

After-sales services optimisation through dynamic opportunistic maintenance: a wind energy case study

After-sales maintenance services can be a very profitable source of incomes for original equipment manufacturers (OEM) due to the increasing interest of assets’ users on performance-based contracts. However, when it concerns the product value-adding process, OEM have traditionally been more focused on improving their production processes, rather than on complementing their products by offering after-sales services; consequently leading to difficulties in offering them efficiently. Furthermore, both due to the high uncertainty of the assets’ behaviour and the inherent challenges of managing the maintenance process (e.g. maintenance strategy to be followed or resources to be deployed), it is complex to make business out of the provision of after-sales services. With the aim of helping the business and maintenance decision makers at this point, this paper proposes a framework for optimising the incomes of after-sales maintenance services through: 1) implementing advanced multi-objective opportunistic maintenance strategies that sistematically consider the assets’ operational context in order to perform preventive maintenance during most favourable conditions, 2) considering the specific OEMs’ and users’ needs, and 3) assessing both internal and external uncertainties that might condition the after-sales services’ success. The developed case study for the wind energy sector demonstrates the suitability of the presented framework for optimising the after-sales services.EU Framework Programme Horizon 2020, MSCA-RISE-2014: Marie Skłodowska-Curie Research and Innovation Staff Exchange (RISE) (grant agreement number 645733- Sustain-Owner-H2020-MSCA-RISE-2014) and the EmaitekPlus 2016-2017 Program of the Basque Government

Prognostics-Based Two-Operator Competition for Maintenance and Service Part Logistics

Prognostics and timely maintenance of components are critical to the continuing operation of a system. By implementing prognostics, it is possible for the operator to maintain the system in the right place at the right time. However, the complexity in the real world makes near-zero downtime difficult to achieve partly because of a possible shortage of required service parts. This is realistic and quite important in maintenance practice. To coordinate with a prognostics-based maintenance schedule, the operator must decide when to order service parts and how to compete with other operators who also need the same parts. This research addresses a joint decision-making approach that assists two operators in making proactive maintenance decisions and strategically competing for a service part that both operators rely on for their individual operations. To this end, a maintenance policy involving competition in service part procurement is developed based on the Stackelberg game-theoretic model. Variations of the policy are formulated for three different scenarios and solved via either backward induction or genetic algorithm methods. Unlike the first two scenarios, the possibility for either of the operators being the leader in such competitions is considered in the third scenario. A numerical study on wind turbine operation is provided to demonstrate the use of the joint decision-making approach in maintenance and service part logistics