Optimization of maintenance policy using the proportional hazard model

The evolution of system reliability depends on its structure as well as on the evolution of its components reliability. The latter is a function of component age during a system's operating life. Component aging is strongly affected by maintenance activities performed on the system. In this work, we consider two categories of maintenance activities: corrective maintenance (CM) and preventive maintenance (PM). Maintenance actions are characterized by their ability to reduce this age. PM consists of actions applied on components while they are operating, whereas CM actions occur when the component breaks down. In this paper, we expound a new method to integrate the effect of CM while planning for the PM policy. The proportional hazard function was used as a modeling tool for that purpose. Interesting results were obtained when comparison between policies that take into consideration the CM effect and those that do not is established.     

Real-time health prognosis and dynamic preventive maintenance policy for equipment under aging Markovian deterioration

An often seen practice of preventive maintenance (PM) is to construct a machine's reliability model based on its historical failure records. The reliability model is then used to determine the PM schedule by minimizing the machine's long-run operation cost or average machine downtime. Machines in many hi-tech manufacturing sectors are using sophisticated sensor technologies to provide sufficient immediate online data for real-time observation of equipment condition. Not only is the historical data but also the real time condition now available for scheduling a more effective PM policy. This research is to determine an effective PM policy based on real-time observations of equipment condition. We first use the multivariate process capability index to integrate the equipment's multiple parameters into an overall equipment health index. This health index serves as the basis for real-time health prognosis under an aging Markovian deterioration model. A dynamic PM schedule is then determined based on the health prognosis.     

Availability optimisation for stochastic degrading systems under imperfect preventive maintenance

This paper deals with imperfect preventive maintenance (PM) optimisation problem. The system to be maintained is typically a production system assumed to be continuously monitored and subject to stochastic degradation. To assess such degradation, the proposed maintenance model takes into account both corrective maintenance (CM) and PM. The system undergoes PM whenever its reliability reaches an appropriate value, while CM is performed at system failure. After a given number of maintenance actions, the system is preventively replaced by a new one. Both CM as well as PM are considered imperfect, i.e. they bring the system to an operating state which lies between two extreme states, namely the as bad as old state and as good as new state. The imperfect effect of CM and PM is modelled on the basis of the hybrid hazard rate model. The objective of the proposed PM optimisation model consists on finding the optimal reliability threshold together with the optimal number of PM actions to maximise the average availability of the system. A mathematical model is then proposed. To solve this problem an algorithm is provided. A numerical example is presented to illustrate the proposed maintenance optimisation model.     

Optimal integrated maintenance/production policy for randomly failing systems with variable failure rate

This article deals with the combined production and maintenance plans for a manufacturing system satisfying a random demand. We first establish an optimal production plan which minimises the average total inventory and production cost. Second, using this optimal production plan, and taking into account the deterioration of the machine according to its production rate, we derive an optimal maintenance schedule which minimises the maintenance cost. A numerical example illustrates the proposed approach, this analytical approach, based on a stochastic optimisation model and using the operational age concept, reveals the significant influence of the production rate on the deterioration of the manufacturing system and consequently on the integrated production/maintenance policy.     

A survey of the application of gamma processes in maintenance

This article surveys the application of gamma processes in maintenance. Since the introduction of the gamma process in the area of reliability in 1975, it has been increasingly used to model stochastic deterioration for optimising maintenance. Because gamma processes are well suited for modelling the temporal variability of deterioration, they have proven to be useful in determining optimal inspection and maintenance decisions. An overview is given of the rich theoretical aspects as well as the successful maintenance applications of gamma processes. The statistical properties of the gamma process as a probabilistic stress-strength model are given and put in a historic perspective. Furthermore, methods for estimation, approximation, and simulation of gamma processes are reviewed. Finally, an extensive catalogue of inspection and maintenance models under gamma-process deterioration is presented with the emphasis on engineering applications.     

维修工程管理研究与发展综述

综述了近几十年来维修工程管理的研究与发展，如人工智能、故障诊断、机器状态监测技术(如振动分析、红外检测、热录像仪等)、预测和预防性维修(PPM)、全员生产维修(TPM)和主动性维修(PM)等，论述了综合应用机器实时状态监测与故障诊断、人工智能、计算机通讯技术以及先进的维修管理理念的集成质量控制与维修系统，最后提出一种目前世界领先的远程智能维修系统。内容包括：实践应用中的维修管理评估、智能和集成维修管理、状态监测维修中的智能预测决策支持系统(IPDSS)、设备状况衰退趋势预测——人工神经网络方法、IPDSS支持的维修管理、故障诊断中的人工智能应用、基于可靠性的预防性维修安排和远程智能维修系统。     

Evaluation of maintenance policies for equipment subject to quality shifts and failures

We develop an economic model for the optimization of maintenance procedures in a production process with two quality states. In addition to deteriorating with age, the equipment may experience a jump to an out-of-control state (quality shift), which is characterized by lower production revenues and higher tendency to failure. The times to quality shift and failure are allowed to be generally distributed random variables. We consider two types of maintenance: minimal maintenance (MM) that upgrades the quality state of the equipment without affecting its age and perfect preventive maintenance (PM) that fully upgrades the equipment to the as-good-as-new condition. We derive the expression for the expected profit per time unit and we investigate, through a large number of numerical examples, the type of the optimal solution. It is concluded that in practically every case the optimal maintenance policy is an extreme one: it either calls for immediate MM as soon as a quality shift occurs (active policy) or it allows operation in the out-of-control state until the time of a scheduled PM action (passive policy).     

A nested modelling approach to infrastructure performance characterisation

Reliable and accurate predictions of infrastructure condition can save significant amounts of money for infrastructure management agencies through better planned maintenance and rehabilitation activities. Infrastructure deterioration is a complicated, dynamic and stochastic process affected by various factors such as design, environmental conditions, material properties, structural capacities and some unobserved variables. Previous researchers have explored different types of modelling techniques, ranging from simple deterministic models to sophisticated probabilistic models, to characterise the deterioration process of infrastructure systems; however, these models have limitations in various aspects. Traditional deterministic models are inadequate to capture the uncertainties associated with infrastructure deterioration processes. State-based probabilistic models can only predict conditions at fixed time points. Time-based probabilistic models require frequent observations that, in practice, are not easy to perform. The goal of this research is to develop a new probabilistic model that is capable of capturing the stochastic nature of infrastructure deterioration, while at the same time avoiding the limitations of previous modelling efforts. The proposed nested model is based on discrete choice model theory. It can be used to predict the probability of an infrastructure system staying at defined condition states by relating an index representing the performance of the infrastructure to a number of explanatory variables that characterise the structural adequacy, traffic loading and environmental conditions of the infrastructure. The proposed model includes different possible implementation paths (sequential versus multinomial) depending on the considered explanatory variables and the available data. In the case study, the proposed probabilistic model is implemented with pavement performance data collected in Texas, yielding promising preliminary results.     

Combining preventive maintenance and statistical process control: a preliminary investigation

The economic design of control charts and the optimization of preventive maintenance policies are two research areas that have recently received a great deal of attention in the quality and reliability literature. Both of these research areas are focused on reducing the costs associated with operating manufacturing processes. In addition, it is widely recognized that the maintenance of manufacturing equipment and the quality of manufactured product are related. However, these two research areas are rarely integrated. In this paper, a combined control chart–preventive maintenance strategy is defined for a process which shifts to an out-of-control condition due to a manufacturing equipment failure. An X¯ chart is used in conjunction with an age-replacement preventive maintenance policy to achieve a reduction in operating costs that is superior to the reduction achieved by using only the control chart or the preventive maintenance policy. This superior cost performance is demonstrated using a simulation-optimization approach.     

Dependability and performance stochastic modelling of a two-unit repairable production system with preventive maintenance

In this paper, a two-unit multistate repairable production system is considered in which preventive maintenance (PM) is implemented in order to improve its dependability and performance. A general model is provided for the production system using a semi-Markov process, for examining system’s limiting behaviour. Apart from combining redundancy with PM, we introduce scenarios like imperfect and failed maintenance which are usually met in real life production systems. For the proposed model, we calculate the availability, the mean time to failure and the total operational cost and we formulate optimisation problems settled with respect to the system’s inspection times. The main aim of our work is to determine the optimal inspection times and consequently the optimal PM policies to be adopted in order to optimise system’s dependability and performance.     

Impact of the use-based maintenance policy on the performance of cellular manufacturing systems

In this paper, a multi-objective integer programming approach is developed to investigate the impact of the use-based preventive maintenance (UPM) policy on the performance of the cellular manufacturing system (CMS). Under the UPM policy a maintenance schedule is established which provides for the performance of preventive maintenance (PM) only after a predetermined number of operating hours of machine use. This research indicates how PM and failure repair (FR) actions affect the effective availability of the machines and accordingly the machine and inter/intra-cell material handling costs under the UPM policy. The objective is to minimise the machine cost, inter- and intra-cell material handling and PM/FR costs. The proposed model is solved by an interactive fuzzy programming (IFP) approach to determine the best compromise solution from the decision maker point of view. IFP assumes that each objective function has a fuzzy goal and focuses on minimising the worst upper bound to obtain an efficient solution which is close to the best lower bound of each objective function. Compromise solutions are prioritised by two efficiency criteria, i.e. grouping efficiency and system availability. The performance of the proposed model is verified by a comprehensive numerical example.     

不完备生产与条件维护策略下的生产批量决策研究

构建了不完备生产与条件维护下的生产批量模型,采用威布尔分布的曲线分布宽度描述可靠性的退化性,考虑了曲线分布宽度为等比数列和等差数列2种模型,利用报酬更新理论求解了期望平均总成本的最小值。结果表明,第1种模型的期望平均总成本要高于设备不具有退化性的期望平均总成本,前者的条件维护的阈值、最优生产批量和维护次数都比后者的少;第2种模型的期望平均总成本总体要低于设备不具有退化性的期望平均总成本,前者的条件维护的阈值比后者的少,而前者的维护次数和最优生产批量都比后者的多。研究还发现,公比和公差是影响期望平均总成本的最重要因素,需求是影响条件维护的可靠性阈值的最重要因素。本文的相关启示可为管理者提供决策参考依据。     

Performance modeling in critical engineering systems using RAM analysis

Reliability, availability and maintainability (RAM) analysis of system is helpful in carrying out design modifications, if any, required to achieve minimum failures or to increase mean time between failures (MTBF) and thus to plan maintainability requirements, optimize reliability and maximize equipment availability. To this effect, the paper presents the application of RAM analysis in a process industry. Markovian approach is used to model the system behavior. For carrying out analysis, transition diagrams for various subsystems are drawn and differential equations associated with them are formulated. After obtaining the steady state solution the corresponding values of reliability and maintainability are estimated at different mission times. The computed results are presented to plant personnel for their active consideration. The results proved helpful to them for analyzing the system behavior and thereby to improve the system performance considerably by adopting and practicing suitable maintenance policies/strategies.     

Opportunistic maintenance of multi‐equipment system: a case study

A case study on preventive maintenance (PM) of a multi‐equipment system is presented in this paper. Each equipment of the system consists of many components/subsystems connected in series. Because of the series structure, opportunistic maintenance (OM) policies are more effective for the components of the equipment. A new OM policy based on the classification of opportunities has been proposed. Various OM policies have been evaluated using simulation modeling, and the new policy has been found to be more effective than the existing OM policies. The impact of this policy on the overall system has also been simulated. Copyright © 2000 John Wiley & Sons, Ltd.     

Integrating run-based preventive maintenance into the capacitated lot sizing problem with reliability constraint

A joint model for integrating run-based preventive maintenance (PM) into the capacitated lot sizing problem (CLSP) is proposed, in which the production system is subject to deterioration with usage and PM operations are implemented to restore the system. In this model, both production and PM operations are restricted by the system's maximum capacity, and the system reliability has to be maintained above a threshold value throughout the planning horizon. By linearisation of the reliability constraints, the problem is formulated as a mixed-integer linear programming. An explanatory example is given to illustrate the advantage of the joint model comparing with the interval-based PM policy in terms of system's overall cost. A three-stage heuristic is proposed to solve this integrated model, which includes a Lagrangian-based heuristic for the CLSP. The numerical experiments are conducted to evaluate the performance of the developed heuristics and the computational results show that the heuristics can provide good feasible solutions for the corresponding models. The discussion of the results is finally given in detail.     

维修管理模式对制造企业质量控制影响的实证研究

可靠的设备预防维修水平和卓越的产品质量保证能力是保障产品过程质量的关键,现有多数研究集中在质量管理模式与企业绩效的关系分析。在对过程质量控制、设备维修管理评述的基础上,探讨了设备维修管理模式与维修绩效及过程质量控制绩效间的关系。以国内制造企业的连续生产方式为研究对象,运用结构方程模型剖析了RCM、TPM、设备采购管理与和设备维修绩效、过程质量控制绩效的路径关系,发现基础维修管理活动对维修绩效有间接影响,RCM、TPM对设备维修绩效有显著影响,路径系数分别为0.346、0.717,设备维修绩效对过程质量控制绩效的影响显著,路径系数为0922。证明制造企业为提升产品质量,需要完善其设备预防维修系统。     

Condition, safety and cost profiles for deteriorating structures with emphasis on bridges

After an enormous investment in construction of highway networks undertaken in the second half of the 20th century, the highway networks of most European and North American countries are now completed or close to completion. As a result, the need in funding changed from building new highway structures to repair, rehabilitation, and replacement the existing ones. In this paper, a model for analyzing the evolution in time of probabilistic performance indicators of existing structures, in terms of condition, safety, and cost under no maintenance, preventive maintenance, and essential maintenance, is presented. This model integrates the current practice in bridge management systems based on visual inspections (condition index) with structural assessment (safety index) during the lifetime of existing structures. The proposed model allows the consideration of uncertainties in the performance deterioration process, times of application of maintenance actions, and in the effects of maintenance actions on the condition, safety, and life-cycle cost of structures by defining all parameters involved in the model as random variables. Interaction between condition and safety profiles is defined through probabilistic and deterministic relations. The probabilistic characteristics of the condition, safety, and cost profiles of deteriorating structures are computed by Monte-Carlo simulation. Several realistic examples, based on data on highway bridge components gathered in the United Kingdom, are presented.     

Control-limit preventive maintenance policies for components subject to imperfect preventive maintenance and variable operational conditions

This paper develops two component-level control-limit preventive maintenance (PM) policies for systems subject to the joint effect of partial recovery PM acts (imperfect PM acts) and variable operational conditions, and investigates the properties of the proposed policies. The extended proportional hazards model (EPHM) is used to model the system failure likelihood influenced by both factors. Several numerical experiments are conducted for policy property analysis, using real lifetime and operational condition data and typical characterization of imperfect PM acts and maintenance durations. The experimental results demonstrate the necessity of considering both factors when they do exist, characterize the joint effect of the two factors on the performance of an optimized PM policy, and explore the influence of the loading sequence of time-varying operational conditions on the performance of an optimized PM policy. The proposed policies extend the applicability of PM optimization techniques.     

Joint optimisation of production,maintenance and quality for batch production system subject to varying operational conditions

This paper considers the integration problem of production, maintenance and quality for a capacitated lot-sizing production system subject to deterioration. The effects of varying operational conditions from batch to batch on system reliability and product quality are modelled by proportional hazards models, resulting in non-monotonic failure rate and defect rate. After each batch production, imperfect preventive maintenance (PM) is determined to mitigate the system deterioration, and inspection is taken to sort nonconforming items in the finished goods. Once the cumulative number of nonconforming items exceeds a predetermined threshold, an overhaul is performed to renew the system. An integrated model for optimising production plan, PM plan and overhaul strategy is developed to minimise the total cost while satisfying all product demands. A genetic algorithm is proposed to solve the integrated model efficiently. Numerical results validate the rationality of the model with varying operational conditions consideration and its applicability in economic benefits.     

A copula-based quantified airworthiness modelling for civil aircraft engines

The aircraft engine serves as the core system of an aircraft and operates under extreme conditions, requiring high reliability and absolute safety. The design, manufacturing, and after-sales services of aircraft engines are complex processes. To ensure safety and performance, maintenance checks are performed periodically and hierarchically throughout the engine’s life-cycle. Among these checks, shop visit (SV) heavy maintenance checks play a crucial role but are also costly, especially when they occur unexpectedly and unplanned. Analysis of the maintenance logbook, recording aviation operations, reveals a significant occurrence of unplanned SVs, which may be attributed to the existing maintenance policy based on a single time-definition. To address this issue, this paper seeks to establish a novel approach to quantifying airworthiness through copula modelling, which combines two time-definitions: the flying hour (FH) and the flying cycle (FC). This approach is unique in the aviation industry. By employing the Gumbel copula with the generalized extreme value (GEV) distribution as the marginal distribution, and utilizing non-parametric association measurement parameter estimation, the quantified airworthiness of civil aircraft engine fleets across multiple product lines can be effectively modeled. This research provides valuable insights into optimizing maintenance policies and enhancing the reliability and safety of aircraft engines.