Imperfect Repair Research Articles

A grouping module assessment method for ocean engineering systems: Subsea tree system as a case

In the ocean engineering environment, the quality failure data of complex systems are difficult to obtain due to the high experiment cost. In addition, using a single model to analyze risk, reliability, availability, and maintainability is a big challenge. Based on the fault tree, Dynamic Bayes and Markov models, a state assessment method for ocean engineering systems with multiple maintenance modes is proposed in this paper. This method gives full play to the advantages of the three methods, and comprehensively analyzes the risk, reliability, availability and maintainability. This method uses fault tree and Markov model to pre-process fault data, and then inputs the pre-processed fault data into the multi-state degradation model based on dynamic Bayesian theory. Considering the maintenance strategies of no repair, perfect repair, imperfect repair and preventive repair, the model is iterated and adjusted until the model has processed all the event data and the updated model can best reflect the state of the system. The method is verified by taking the subsea tree of the subsea production system as an example. The obtained tree reliability index (mean time without failure) is basically consistent with the failure statistics of offshore and onshore reliability databases, which verifies the accuracy of the proposed method.

Cost-based performance optimization of a single system under a hierarchical imperfect maintenance policy

Abstract Due to the influence from external factors such as repair sites and seasonal climate change, it is difficult to restore the system performance to any intermediate level between perfect maintenance and minimal maintenance through imperfect maintenance. This article first categorizes the states of the system just before repair into three classes based on its internal degradation level: failure, major defect, and minor defect, with three corresponding thresholds. Subsequently, the corresponding repairs are carried out to dwindle the system’s degradation to different levels. In detail, if the internal degradation level of the system just before repair is recognized as minor defect, an imperfect repair, termed as type I imperfect repair, is implemented to scale down the degradation level below the minor defect threshold. If the degradation level is identified as major defect, an upgraded imperfect repair, termed as type II imperfect repair, is executed to only lower the degradation to the level between the minor defect threshold and major defect threshold. Otherwise, if the degradation before repair is beyond the failure threshold, replacement will be carried out instead of these imperfect repairs. Thus, a novel hierarchical imperfect maintenance structure is introduced. Then, a multi-variable repair cost model is constructed when considering the related costs incurred from inspection, type I imperfect repair, type II imperfect repair, replacement, and even system downtime. Finally, with the aid of the stationary law of Markov chains and the semi-regenerative process, the cost-based performance optimization with three parameters, including the inspection interval, minor defect threshold, and major defect threshold, is explored through a numerical experiment, and the closed expression of the optimal cost rate is provided.

Reliability analysis of multiple repairable systems under imperfect repair and unobserved heterogeneity

AbstractImperfect repairs (IRs) are widely applicable in reliability engineering since most equipment is not completely replaced after failure. In this sense, it is necessary to develop methodologies that can describe failure processes and predict the reliability of systems under this type of repair. One of the challenges in this context is to establish reliability models for multiple repairable systems considering unobserved heterogeneity associated with systems failure times and their failure intensity after performing IRs. Thus, in this work, frailty models are proposed to identify unobserved heterogeneity in these failure processes. In this context, we consider the arithmetic reduction of age (ARA) and arithmetic reduction of intensity (ARI) classes of IR models, with constant repair efficiency and a power‐law process distribution to model failure times and a univariate Gamma distributed frailty by all systems failure times. Classical inferential methods are used to estimate the parameters and reliability predictors of systems under IRs. An extensive simulation study is carried out under different scenarios to investigate the suitability of the models and the asymptotic consistency and efficiency properties of the maximum likelihood estimators. Finally, we illustrate the practical relevance of the proposed models on two real data sets.

An analytical approach to evaluate life-cycle cost of deteriorating pipelines

Optimal inspection and maintenance planning for deteriorating pipelines is important for cost-effective risk management decisions. The objective of this study is to develop an analytical approach for determining the expected value and standard deviation of life-cycle cost (LCC) for deteriorating pipelines, which can incorporate imperfect repair and inspection actions without making independent assumptions of failure and repair events. The framework is developed based on a decision tree model by using analytical methods to evaluate events and considers the impact of the inspection schedules and possible repair actions on the probability distributions of failure times. To illustrate the proposed framework, a steel transmission pipeline with a corrosion defect is used, where a stochastic model of corrosion growth is assumed and burst failure is considered as the pipeline failure mode. The case study indicates that the failure cost due to two or more failure occurrences can be ignored; and the inspection interval, repair threshold and type, the length of lifetime considered, and unit failure cost all play important roles in the expected value of the total cost. The variation in the LCC estimation is found to be significant, and it has a great impact on determination of optimal decision variables.

Optimal Bivariate Order-Replacement Policies for a Multi-State Repairable System with Reliability Constraint

A bivariate order-replacement policy for a multi-state repairable system with imperfect repair is put forward in this paper, where the decisions on when to order a spare part and when to place a replacement are based on the number of failures. The geometric processes are generalized to depict the characteristics that the successive working times are shorter and shorter while the consecutive repair times are longer and longer. According to the renewal reward theorem, a constrained optimization model for the order-replacement policy is formulated, in which the aim is to minimize the expected long-run cost rate (ELRCR) under the constraint that system availability is not less than a predetermined availability requirement. General representations of the ELRCR and system availability are derived and an approximation result of the optimization model is given under certain assumptions. Illustrative examples are provided to validate the applicability of the proposed order-replacement model and show the advantage of the order-replacement policy for the multi-state repairable system.

Non-renewable warranty cost analysis for dependent series configuration with distinct warranty periods

A warranty product often has an interval structure, resulting in different warranty periods for each component due to their distinct degradation paths. From the manufacturer’s perspective, it is reasonable to establish appropriate warranty periods for each part to achieve cost savings. This paper introduces a dependent series configuration consisting of a main component and an auxiliary component. The failure of the main component leads to system failure, while the failure of the auxiliary component only causes a random damage to the main component. These two components follow different Wiener degradation paths, and then their first passage times (FPTs) follow disparate inverse Gaussian distributions. Assuming a pre-deterministic warranty period, W, for the main component, and ηW,0<η<1, for the auxiliary component, the warranty period can be divided into two stages: [0,ηW] and [ηW,W]. In this context, the paper proposes warranty claim policies for replacement, objective-oriented imperfect repair (OOIR), and refund. The corresponding warranty costs sustained by manufacturer and consumer within these two stages are considered. Finally, a numerical example is presented to illustrate the warranty costs sustained by manufacturer and consumer under different scenarios, as well as the total warranty costs.

Rapid recovery strategy for seismic performance of seismic-damaged structures considering imperfect repair and seismic resilience

In the emergency repair process of seismic-damaged structures, it is necessary to determine the optimal repair strategy according to damage assessment results, available repair resources and repair time. In this study, the applicable conditions of various member-level and structure-level damage indexes or models are compared. Then, considering the actual conditions of limited available repair resources and repair time in the emergency repair process, the determination method of the optimal imperfect repair strategy is established. On this basis, the determination method of the optimal repair sequence is proposed by taking seismic resilience as the evaluation index. Finally, a seismic fragility analysis method that considers uniform collapse risk and residual service life of structures is introduced, which can be used to analyze the seismic performance of seismic-damaged structures and to compare the repair effectiveness of different repair strategies. Taken a 5-story reinforced concrete structure as an example for analysis. The analysis results show the optimal imperfect repair strategy and the optimal repair sequence determined by the proposed methods can effectively improve the seismic performance of seismic-damaged structures. The fragility analysis results further confirm that the repair based on the optimal imperfect repair strategy can effectively reduce the collapse risk of seismic-damaged structures.

Maintenance optimization for dependent two-component degrading systems subject to imperfect repair

Maintenance optimization for dependent two-component degrading systems subject to imperfect repair

Hierarchical condition-based maintenance planning for corrosion process considering natural environmental impact

Condition-based maintenance (CBM) powered by corrosion inspection is vital to ensure the service safety and availability of equipment structure, especially in harsh natural environments. Preventive repair and coating are two effective measures widely adopted in corrosion-centered CBM implementation, whose collaborative planning, however, is rarely reported in corrosion control models. This paper proposes a hierarchical CBM policy oriented to gradual corrosion deterioration, which quantifies the comprehensive effect of corrosive environment and uncertain coating lifetime. The long-term corrosion is governed by a generalized stochastic process incorporating multiple environmental factors. Inspections are equally spaced to reveal corrosion severity, followed by a combination of recoating, imperfect repair and replacement to restore structure health. In particular, repair is executed if the accumulated corrosion exceeds a safe control limit, and replacement is immediate if (a) the repair number attains a pre-set threshold, and (b) the residual corrosion after repair remains above the limit. The impact of random coating lifetime on CBM performance is also analytically analyzed. The long-run maintenance cost is minimized through the joint optimization of inspection interval, corrosion control limit, and imperfect repair number. The model applicability is demonstrated through numerical experiments conducted on ship deck structures under marine environment.

On the combined imperfect repair process

AbstractIn this paper, a new point process is introduced. It combines the nonhomogeneous Poisson process with the generalized Polya process (GPP) studied in recent literature. In reliability interpretation, each event (failure) from this process is minimally repaired with a given probability and GPP-repaired with the complementary probability. Characterization of the new process via the corresponding bivariate point process is presented. The mean numbers of events for marginal processes are obtained via the corresponding rates, which are used for considering an optimal replacement problem as an application.

Optimal Maintenance of a System With Multiple Deteriorating Components Served by Dedicated Teams

To maintain a multi-component system, different dedicated service teams with different skill sets and tools are often involved. Such a relationship constitutes maintenance team coalition. In most cases, it may not be the best to plan each team&#x0027;s maintenance activities independently as such independent decisions may not achieve the required system-level reliability performance (RP). To balance the reliability and costs of components in achieving a high level of system RP, an efficient method is to assign a failure penalty cost to each maintenance team and then develop their optimal maintenance policy. In this article, the Shapley value is utilized for fair penalty costs allocation to avoid any interest for teams to secede the coalition, whose actual role is to evaluate the criticality level of each component in the context of coalition. Moreover, imperfect inspection and imperfect repair are quite common in practice because of limited resources, technologies and time. To address these practical concerns, a new reliability-centered hybrid preventive maintenance policy is proposed. The optimal inspection interval and age-based replacement interval are determined for each team to minimize the cost rate over an infinite time horizon. Several numerical examples illustrate that the proposed decision-making method is effective in handling such complex maintenance problems involving a coalition of dedicated maintenance teams.

Maintenance optimization of a system subject to two-stage degradation, hard failure, and imperfect repair

Maintenance optimization of a system subject to two-stage degradation, hard failure, and imperfect repair

Reliability analysis of standby provision multi‐unit machining systems with varied failures, degradations, imperfections, and delays

AbstractThis prospective study focuses on analyzing the reliability characteristics of multi‐unit systems with standby provisioning, accounting for failures, degradation, random delays, and probabilistic imperfections. The investigation sheds light on how these unreliable attributes hinder the performance and availability of machining systems. Given the frequent occurrence of these negative attributes within machining systems, their impact on production flow, performance, and resource utilization is significant. Moreover, these unfavorable attributes hinder the adoption of advanced technologies that rely on the continuous availability of machining systems. Thorough research on operational traits serves as a foundation for developing solutions to enhance machining system efficiency and elucidates the underlying causes of machining system failures throughout their performance lifecycle. The reliability analysis employs a state‐of‐the‐art queue‐theoretic approach. In order to model the stochastic behavior of the investigated machine repair problem in a systematic manner, we consider various statistically independent failure modes, including active/standby unit failure, degraded failure, switching failure, and common‐cause failure. The unreliable characteristics of machining systems are further compounded by factors such as imperfect fault coverage, reboot delay, and imperfect repair, necessitating a comprehensive examination to strategically implement preventive, corrective, and predictive measures. The seamless operation of multi‐unit machining systems is essential for the successful integration of advanced technologies such as cloud computing, industry 4.0, and IoT. Failures, delays, degradation, and imperfections within machining systems have detrimental effects on their efficiency and availability, demanding in‐depth investigation. To facilitate numerical experimentation and sensitivity analysis of the reliability aspects of the proposed machining system, we develop performance indices such as system reliability, mean‐time‐to‐failure, and failure frequency. These metrics provide valuable insights for decision‐makers seeking to implement measures that ensure uninterrupted availability of the machining system.

Cost-Benefit Analysis of a Two-Unit Cold Standby System with Imperfect Repair Man and Abnormal Weather Conditions

Cost-Benefit Analysis of a Two-Unit Cold Standby System with Imperfect Repair Man and Abnormal Weather Conditions

Fault Tree Analysis for Reliability Analysis of Wind Turbines Considering the Imperfect Repair Effect

Wind turbines are complex and expensive equipment, requiring high reliability and low maintenance costs. However, most of the existing fault tree analysis (FTA) methods for reliability analysis of wind turbines assume that the repair of wind turbines can restore them to as good as new condition, which is called perfect repair. This assumption may not be realistic in practice, as the repair may not fully recover the original performance or functionality of the equipment or may introduce new defects or errors. This phenomenon is called imperfect repair, which can reduce the reliability of wind turbines over time. To consider the imperfect repair effect in reliability analysis, we present a new FTA approach in this study. In order to predict and assess the failure intensity and dependability of wind turbines under imperfect repair, the proposed FTA technique uses a log-linear proportional intensity model (LPIM). Failure probability, failure rate, and mean time to failure can all be improved with the suggested FTA technique for wind turbines operating with poor repair. The proposed FTA method can also identify the critical components or failure modes most affected by the imperfect repair effect and suggest preventive maintenance actions to improve the reliability of wind turbines. We demonstrate the applicability and effectiveness of the proposed FTA method through a case study on a real or hypothetical wind turbine system under imperfect repair. The findings indicate that the proposed FTA method offers a more precise and authentic assessment of the reliability of wind turbines in the presence of imperfect repair, in contrast to existing FTA methods that assume perfect repair. The findings also demonstrate that the electrical system, hydraulic system, gearbox, generator, and blade are the most critical components or failure modes affecting the system's reliability.

Markovian Unreliable Server Retrial Queue with Double Orbit, Imperfect Repair and Balking

Markovian Unreliable Server Retrial Queue with Double Orbit, Imperfect Repair and Balking

Fuzzified imperfect repair redundant machine repair problems

Fuzzified imperfect repair redundant machine repair problems

Availability Analysis of Fault Tolerant Degraded Machining System with Imperfect Repair and Multi-type Failures

Availability Analysis of Fault Tolerant Degraded Machining System with Imperfect Repair and Multi-type Failures

Reliability modelling and evaluating of wind turbine considering imperfect repair

To model and evaluate the reliability of wind turbine (WT) under imperfect repair, an improved Log-linear Proportional Intensity Model (LPIM)-based method was proposed. Initially, using the three-parameter bounded intensity process (3-BIP) as the benchmark failure intensity function of LPIM, an imperfect repair effect-aware WT reliability description model was developed. Among them, the 3-BIP was used to describe the evolution process of the failure intensity in the stable operation stage with running time, while the LPIM reflected the repair effect. Second, the estimation problem for model parameters was transformed into a minimum solution problem for a nonlinear objective function, which was then solved using the Particle Swarm Optimization algorithm. The confidence interval of model parameters was finally estimated using the inverse Fisher information matrix method. Key reliability indices interval estimation based on the Delta method and point estimation was derived. The proposed method was applied to a wind farm’s WT failure truncation time. The proposed method has a higher goodness of fit based on verification and comparison. As a result, it can bring the evaluated reliability closer to engineering practice.

Multi‐state reliability assessment for shipboard hybrid turbine‐diesel generation system with redundancy and aging effects

AbstractComplex system structures, dynamic energy demands, and tough operating environment pose a huge challenge to reliability assessment and risk control. Taking multi‐state, redundant structure and aging impact into account, reliability assessment for shipboard hybrid turbine‐diesel generation system is studied. This work adopts a comprehensive method combining the Markov method and universal generating function (UGF): the Markov method is used for reliability modeling at the unit level, and then synthesized and calculated through UGFs to obtain system‐level reliability. Based on the above methodology, this work presents a multi‐state system (MSS) model with different configuration structures and failure rate types, then compares the availability evaluation results of the single power generation system, the hybrid power system with redundancy and aging effects. The results show that (1) redundant design effectively improves system availability to meet power supply requirements; (2) in the case of system aging and imperfect repair, redundant configuration and power distribution can significantly improve the availability of power supply to be almost unaffected by aging, and effectively reduce the risk of performance failure; and (3) when the redundancy is applied, the system power supply availability is not sensitive in the high‐value range of the redundant installed capacity ratio, but sensitive in the high‐value range of effective coefficient about power compensation control.