Inspection Intervals Research Articles

Prognosis-driven reliability analysis and replacement policy optimization for two-phase continuous degradation

Numerous industrial assets inevitably encounter defect emergence during actual operation, which significantly aggravates the degradation process. This study investigates a prognosis-driven, multi-threshold inspection and replacement model for two-phase continuous degradation. Inspections are equally space to reveal the health state as well as real-time degradation level. Three degrees of control limits, namely corrective limit, defective limit and normal limit are scheduled to manipulate replacement frequencies under separate system states. At an inspection, if the system is diagnosed as normal while the degradation exceeds the normal limit, preventive replacement is postponed according to: (a) residual lifetime expectation adjusted by a control coefficient, and (b) defect identification time, whichever occurs first. Otherwise if the system is found defective with degradation exceeding the defective limit, replacement is also postponed according to a stricter coefficient. The cost model is formulated, which seeks to minimize the long-run cost rate through the joint optimization of inspection interval, control limits and safety coefficients. The applicability of the proposed model is justified via a case study on high-speed rail bearings.

Inspection Interval Optimization for Aircraft Composite Tail Wing Structure Using Numerical-Analysis-Based Approach

Recently, there has been a tremendous increase in the use of fiber-reinforced composite (FRCP) in the aviation and aerospace industries due to its superior properties of high strength, stiffness, and low weight. The most important feature of implementing composite materials in aviation is their behavior under dynamic loads and resistance to fatigue. To predict the life of composite structures and optimize the inspection interval, it is essential to predict the damage behavior of composites. In this study, a model of fatigue delamination damage of composite specimens was first constructed using a finite element analysis (FEA)-based approach. The FEA modeling was verified through comparison with experimental specimen data, and the verified FEA model was applied to the composite material aircraft tail wing structure. In this case, a Monte Carlo simulation (MCS) was performed by building a response surface model while considering the uncertainty of the mechanical parameters. Through this process, the risk as a function of flight time could be quantitatively evaluated, and the inspection interval was optimized by selecting the combination with the lowest number of repeated inspections that met the permitted risk criteria.

Sensitivity and uncertainty analysis for structural health monitoring with crack propagation under random loads: A numerical framework in the frequency domain

AbstractThe quantification of uncertainties in a system and the ability to identify the most influential parameters for a given structural health monitoring (SHM) strategy constitutes an important step for an in‐depth analysis of the problem. It is used in reliability assessment and for the definition of proper inspection intervals. In a recent paper, the authors proposed a methodology for SHM and fatigue life estimations of structures under random loads. This paper expands over those concepts and presents a framework for sensitivity and uncertainty analysis for SHM of structures in the frequency domain. The structure is an Euler–Bernoulli beam, which is modeled with the Ritz method. The conceptual simplicity of the Ritz model keeps the computational cost low. The results showed that the Walker parameter for the crack propagation law, ; the modal damping factor; and the input acceleration are important parameters affecting the variance of the remaining useful life.

Condition-based maintenance method for multicomponent system considering maintenance delay based on remaining useful life prediction: Subsea tree system as a case

Maintenance resources and personnel may not arrive in time after formulating a maintenance strategy due to the particular working environment and poor accessibility for multicomponent systems. A condition-based maintenance (CBM) method considering maintenance preparation delay based on remaining useful life (RUL) prediction is proposed. Maintenance preparations under normal and emergency conditions are considered. Inspection time is dynamically set based on the maintenance preparation time and the RUL prediction result. At the inspection time point, RUL for each component in the multicomponent system is predicted based on offline inspection data according to the degradation trend, which is simulated by combining Gamma and Poisson processes. The next inspection time can be determined subsequently. A threshold based on RUL prediction results is set as the maintenance standard to evaluate the maintenance effectiveness. Inspection interval, safety threshold, and maintenance threshold are optimized by minimizing the maintenance cost. A case study of the subsea tree system for offshore oil and gas development is conducted to demonstrate the application of the proposed CBM methodology.

Joint optimization of inspection-based and age-based preventive maintenance and spare ordering policies for single-unit systems

This paper presents a joint optimization policy of preventive maintenance (PM) and spare ordering for single-unit systems, which deteriorate subject to the delay-time concept with three deterioration stages. PM activities that combine a nonperiodic inspection scheme with age-replacement are implemented. When the system is detected to be in the minor defective stage by an inspection for the first time, place an order and shorten the inspection interval. If the system has deteriorated to a severe defective stage, it is either repaired imperfectly or replaced by a new spare. However, an immediate replacement is required once the system fails, the maximal number of imperfect maintenance (IPM) is satisfied or its age reaches to a pre-specified threshold. In consideration of the spare's availability as needed, there are three types of decisions, i.e., an immediate or a delayed replacement by a regular ordered spare, an immediate replacement by an expedited ordered spare with a relative higher cost. Then, some mutually independent and exclusive renewal events at the end of a renewal cycle are discussed, and the optimization model of such a joint policy is further developed by minimizing the long-run expected cost rate to find the optimal inspection and age-replacement intervals, and the maximum number of IPM. A Monte-Carlo based integration method is also designed to solve the proposed model. Finally, a numerical example is given to illustrate the proposed joint optimization policy and the performance of the Monte-Carlo based integration method.

Degradation prediction and rolling predictive maintenance policy for multi-sensor systems based on two-dimensional self-attention

Traditional preventive maintenance policy gradually failed to guarantee the security and economy of current mechanical systems. This paper proposed a highly efficient rolling predictive maintenance (RPdM) policy for multi-sensor system, to make maintenance decisions. In this policy, to cope with the uncertainty of remaining useful life (RUL) prediction, the degradation process of the system is first divided into four intervals according to the inspection interval and spare parts lead time. Then, the two-dimensional self-attention (TDSA) method, which extract time dimensional and feature dimensional features by parallel computation, is developed to predict the probabilities of system RUL in the four intervals instead of the point of RUL. In addition, the output probabilities of the TDSA method are utilized to calculate the maintenance cost rate of the current inspection point and future point. The maintenance decision including spare parts ordering time and maintenance time is determined by comparing the maintenance cost rate of each inspection point, and the decision is updated at the next inspection point. To verify the effectiveness of the proposed RPdM policy, the C-MAPSS dataset provided by NASA is employed to implement degradation prediction and maintenance decision. Experiment results show that the cost rate of RPdM policy is lower than preventive maintenance policy, and only 27.7% higher than ideal maintenance policy which is impossible in real engineering. Moreover, the impact of different out-of-stock costs and corrective costs are explored and shows the good robustness of the RPdM policy.

Modeling dynamic environment effects on dependent failure processes with varying failure thresholds

Devices usually fail due to multiple dependent competing failure processes resulting from internal degradation and random shocks, whose behavior may vary in different environments. This paper focuses on systems suffering from randomly occurring shocks described by Poisson processes and internal degradation characterized by linear path models simultaneously, where the wear rate, shock arrival rate, shock load size, and shock damage amount are modulated by Markovian environments, especially the hard failure threshold differs in distinct environments. Reliability analysis is performed where analytical formulas and simulation algorithms for computing reliability indexes of systems are provided, such as the reliability function. Two maintenance models are developed for systems, including a real-time maintenance policy where the computation formula for the availability function is derived, and a periodic inspection policy in which an optimization model is proposed to find the optimal inspection interval that minimizes the average long-run cost rate. Finally, an illustrative example of floating offshore wind turbine systems is given to demonstrate possible applications of the developed models and proposed methods.

Probabilistic risk assessment for the piping of a nuclear power plant: Uncertainty and sensitivity analysis by using SINTAP procedure

For the purpose of probabilistic fracture mechanics estimation in the field of reliability analysis of pressure vessels and piping, a probabilistic method by using SINTAP (Structural INTegrity Assessment Procedures for European Industry) is developed. Monte Carlo simulation (MCS) is applied to investigate the influence of both the uncertainties of random parameters and inspection strategies on the failure probability (FP). A sensitivity analysis with regard to the above-mentioned aspects is conducted to identify the most significant parameters and efficient countermeasures to reduce failure risk in specially-assumed cases. The results of this study point out that the thickness and the inner radius of the pipe have the strongest impact on the FP of the pipe, followed by the bending moment, weld residual stress (WRS), crack length, initial crack depth, yield strength (YS), ultimate tensile strength (UTS), flow strength, fracture toughness, inner pressure and axial force. Compared with the detection quality and the inspection start time, selecting an appropriate inspection interval is a more effective method to reduce the failure risk. All these results provide a reference for the design of piping systems and guide the selection of in-service inspection (ISI) strategies with suitable flaw-detection capabilities and inspection frequencies.

Modeling post-disaster business recovery under partially observed states: A case study of the 2011 great East Japan earthquake

Post-disaster business recovery is a complex stochastic process influenced by a variety of factors. Moreover, the recovery rate estimation and prediction are more challenging when limited recovery data are obtained for each firm. This study proposes a novel analytical methodology by incorporating the multi-state Markov model to estimate the conditional recovery rates of firms under partially observed recovery states while considering the impact of sector types, initial damage, and financial resource availability after disasters. The recovery process is an improvement process of multiple production capacity states, and the transition probability among states is estimated by utilizing fixed inspection interval observations under an exponential distribution function assumption. Moreover, the likelihood function is developed and maximized to estimate the parameters in the recovery function. To verify the applicability of the proposed model, 2052 firms' recovery after the 2011 Great East Japan Earthquake was conducted as an empirical case study. Specifically, post-earthquake recovery processes under different socioeconomic factors are compared and discussed, with a special focus on the impact of location and financial conditions. The results indicate that the proposed methodology is practical and effective in estimating the partially observed recovery process, which is more in line with the type of data that actual recovery cases can collect. The estimation is limited to earthquake disasters in this research, however, the concepts and framework in the recovery model are also applicable to other types of hazards.

RBM-MCDM framework for optimization of maintenance and inspection intervals of small unmanned aircrafts

PurposeUnmanned aircraft applications are quickly expanded in different fields. These systems are complex that include several subsystems with different types of technologies. Maintenance and inspection planning is necessary to obtain optimal performance and effectiveness. The failure rate in these systems is more than commercial and manned aircraft since they are usually cheaper. But maintenance and operation planning are difficult because we deal with a system that has multi-components, multi-failure models, and different dependencies between subsystems without any advanced health monitoring system. In this paper, this matter is considered and a framework to determine optimal maintenance and inspection plan for this type of system is proposed to improve system reliability and availability. The new criteria according to this field are proposed.Design/methodology/approachMaintenance of unmanned systems influences their readiness; also, according to the complexity of the system and different types of components, maintenance programming is a vital requirement. The plan should consider several criteria and disciplines; thus, multicriteria decision approaches may be useful. On another side, the reliability and safety of unmanned aircraft are the most important requirements in the design and operation phases. The authors consider these parameters and develop a framework based on risk-based maintenance to overcome the problems for unmanned systems. This framework consists of two stages: at the first stage, the critical components and failure modes are determined by FMEA, and in the second stage, the priority of maintenance tasks is determined by a fuzzy multicriteria weighted decision system. In this study, fourteen criteria with different levels of importance are developed and proposed to find the best plan for maintenance and inspection intervals. These criteria have been extracted from the literature review, the author's experience, and expert opinions.FindingsA novel framework for risk-based maintenance has been proposed. Risk determination and risk criteria are the most important factors in this framework. Risks are determined by FMEA, and new criteria are proposed that are used for decision-making. These criteria are proposed based on practical experience and experts' opinions for the maintenance process in the aeronautic industry. These are evaluated by industrial cases, and this framework capability has been demonstrated.Research limitations/implicationsThe proposed framework and criteria for small unmanned aircraft have been developed based on a practical point of view and expert opinion. Thus for implementation in other aeronautic industries, the framework may need a minor modification.Practical implicationsTwo important subsystems of an unmanned aircraft have been studied, and the capabilities of this method have been presented.Originality/valueThis research is original work to determine a maintenance program for unmanned aircraft that their application has rapidly grown up. Practical and design parameters have been considered in this work.

Condition-based opportunistic maintenance policies with two-phase inspections for continuous-state systems

This paper proposes two condition-based opportunistic maintenance policies with two-phase inspections for continuously degraded systems with real-time monitoring and periodic inspections, respectively. The degradation of the components and the system is modeled by a Gamma process. Existing literature finds the optimal maintenance strategies by monitoring the performance of all components in a multi-component system. However, it maybe unrealistic and costly to perform inspections on all components for certain systems. Hence, this study considers a two-phase inspection method, that is, the system-level inspection is conducted first, and then the decision for component-level inspection is made based on the system performance. Maintenance is performed to the component when its degradation reaches the preventive maintenance (PM) threshold or the corrective maintenance (CM) threshold at a component-level inspection. Whenever a maintenance action is implemented, the other components whose degradation exceeds an opportunistic maintenance (OM) threshold will be repaired. Then the long-run expected cost for two-component systems and multi-component systems are derived based on the semi-regenerative properties and simulation method. The combination of the system-level inspection interval, OM, PM and CM thresholds is determined to minimize the long-run expected cost. Finally, this study applies the proposed maintenance policies to the battery pack systems in electrical vehicles.

Holistic Low-Effort Model for Damage Tolerance Analysis in Preliminary Design

Abstract The paper presents reduced order results for three different realistic scenarios with respect to the damage tolerance behaviour. The scenarios are dedicated to stiffened structures and feature the fuselage side panel, the upper fuselage panel and a lower wing panel. A wide range of parameter variations is discussed and the influence on the inspection interval is shown. Results may be used both in preliminary aircraft design and structural optimisation.

Data-driven optimization of repair schemes and inspection intervals for highway bridges

Routine bridge inspections enable timely maintenance plans based on potential risks. These inspections are performed at fixed time intervals, which may be unnecessarily short for bridges in excellent conditions and precariously long for those in poor conditions. Also, deterioration models used in current bridge management approaches fail to include the effect of age, causing inaccurate predictions. This paper develops a hazard-based bridge management approach where inspection frequencies and repair suggestions are optimized based on hazard levels. A two-dimensional Markov model describes the age-dependent bridge deterioration, and a semi-Markov decision process optimizes inspection intervals and repair decisions. The objective is to minimize the expected long-term total annual costs, including expenses associated with maintenance and traffic detours. The modeling process and maintenance management framework was demonstrated on an example bridge superstructure in New York. The results showed lower annual and total costs than the conventional management method. As expected, sensitivity analyses indicated that the pre-specified choices of inspection intervals for low and high hazard levels have a significant effect on the calculated hazard threshold levels. The proposed maintenance management method is adaptable and practical; bridge authorities can identify appropriate repair actions and make inspection decisions based on simple threshold comparisons.

Failure Probability and Inspection Interval of Pressure Safety Valves: Case Study of a Gas Processing Plant

Inspection of pressure safety valves (PSVs) is critical for the safety of process plants which also involves cost. API proposes a Risk-Based Inspection (RBI) method that includes consequences and probability of failure. In this work, PSVs installed in different pressurized equipment of a gas processing plant located in Comilla, Bangladesh, have been studied in order to establish and implement a risk-based inspection planning process in the facility in accordance with API 580 and 581. The probability of failure and consequence of failure have been assessed separately and then combined to determine the risk of failure. The results have been used to assess the acceptability of the current inspection schedule in the facility and present some inspection planning guidelines in order to manage risks. The outcome indicates that a large fraction of the overall risk is concentrated in a relatively limited number of PSVs. These potentially high-risk PSVs should require greater consideration through an amended inspection plan in which more regular inspections are to be scheduled for these devices while inspection intervals may be extended for PSVs identified as having lower risk.

Investigation of Valve Failures Using Statistical Analysis of Proof Test Data

This research work examined pressure relief valve (PRV) failures by using statistical analysis of proof test data obtained from the computerized maintenance management system (CMMS) of Liquefied Natural Gas (LNG) facilities site. This study comparatively investigated the 30 months approved inspection interval for the proof test of PRVs by the Department of Petroleum Resources (DPR) of Nigeria. In this research, failure rate and failure behaviour of PRVs were evaluated and analyzed using bathtub curve. Aging effect of PRV using regression analysis and the cause of failures were also analysed. Least square multiple linear regression was the statistical tool used for the analysis with the aid of EXCEL. After thorough analysis, the study depicted drop in failure rate at different times (years) at the bathtub curve. Also, the statistical analysis found that the ageing effect from five spring loaded PRVs evaluated was at most 0.4% per year with 95% confidence and the amount of variance explained per time was minimal (R-Square 7.6%). It was recommended that the inspection interval (30 months) as approved by DPR for proof test of PRVs was optimal with regard to the required integrity condition of the PRVs since test frequencies yielded better result and consequently less risk. Also, further testing and investigation should be pursued to determine if longer intervals between inspections were possible. Furthermore, analysis from the investigation of cause of failure showed that corrosion was a cause of PRV failure and contact area factors such as sticking and cold welding

A signature-based approach for reliability modeling and maintenance optimization of a coherent system

In reliability context, mean residual lifetime (MRL) models and proportional hazard (PH) models are widely used for reliability analysis and failure prediction. Since maintenance actions typically are based on aforementioned reliability metrics, recent researches have been focused on the extensions of these two models for accurate decision-making. In this paper, using signature arguments, we propose a state-dependent mean residual life (SDMRL) model and demonstrate its applicability in both reliability and maintenance field. In preference to existing models, the SDMRL modeling can be applied to coherent systems and account both changes in the operating environment and for the natural ageing process of the system. Assuming a bivariate threshold-type policy, the paper aims at minimizing the long-run average maintenance cost per unit time by determining appropriate inspection intervals and optimal replacement policy. The proposed model and the behavior of the optimal solutions as the model parameters vary are illustrated through numerical examples.

RBI-IOWs integrated approach to risk assessment: Methodological framework and application

The planning of inspection and maintenance activities is a challenge that researches are largely addressed in petrochemical plants. The Risk-Based-Inspection (RBI) methodology, defined by the API 580 and API 581 Recommended Practices, is the main tool widely used for planning inspection and maintenance activities. However, the validity of the RBI results is closely related to the operating conditions that are supposed to remain constant throughout the inspection period. Significant efforts were made to improve the basic RBI approach. Uncertainty in forecasting models, accuracy in the assumptions of degradation-based approaches, subjective judgment and human error in risk assessment, lack of compliance with industry codes and standards, need to improve maintenance planning and inspection interval optimization, remain the key challenges to be addressed.A tool that can allow a dynamic approach to updating the inspection plan, by a real-time readjustment of the variation in the equipment's risk levels, in compliance with the oil and gas reference standards, is the API 584 Integrity Operating Windows (IOWs) methodology, through which critical windows are defined for the parameters considered to have the greatest impact on the equipment integrity. The adoption of this methodology is capable of overcoming the aforementioned limitations of the RBI, because the inspection plans can be directly modulated by monitored variations in the critical process parameters of the system under analysis.With these premises, the aim of the present study is to outline a fully integrated dynamic risk-based methodological framework to enhance the basic RBI approach by using IOWs analysis, which provides the basis for the development of a procedural model to be implemented in the inspection planning practice. Inspection and maintenance departments are the main beneficiaries, being aware of changes or upset during an operation running, which could give significant advantage in the identification of a not expected accelerated damage mechanism, and its critical effects.To show its application in improving the monitoring of critical plant parameters, which could limit the reliability of pressure equipment during their life cycle, reference is made to the PACOL-HF plant section of the SASOL factory located in Augusta (Italy). As a main result, the proposed approach and its procedural model prove effective in preventing the occurrence of undesired events, through both a real-time monitoring of the process variables, and the resulting mitigation actions that can avoid the failure of the equipment.

Joint Maintenance Strategy Optimization for Railway Bogie Wheelset

A wheelset is one of the most severely worn components of railway bogies. Its health condition has a significant impact on the safety and comfort of railway trains. Moreover, wheelset maintenance costs account for a sizeable part of the railway operating company. Therefore, it is essential to investigate executable maintenance strategies for wheelsets. In this paper, a maintenance strategy that combines periodic inspection and preventive maintenance is proposed. The wheel flange and wheel diameter deterioration models are established by the compound Poisson process based on the cumulative shock from the failure mechanism, and the Weibull distribution is adopted for modeling wheel tread failure probability. The age reduction factor is introduced to describe the maintenance effect. Then, the joint maintenance optimization model is constructed to determine the periodic inspection interval and the reprofiling strategy, with the objective of achieving a minimum maintenance cost rate and with the wheel flange thickness failure as the failure risk constraint. Lastly, a case study is provided, and the results show that, compared with the two conventional maintenance strategies with fixed inspection periods, the maintenance strategy proposed in this paper can reduce the maintenance cost rate by 27.06% and 12.0%, respectively. Moreover, the life span is prolonged by 11.51% and 11.98%, respectively.

Managing the mechanical integrity of pressure equipment using a layers of protection framework and incorporating integrity operating windows

A requirement of performance based regulatory regimes for managing process safety is to demonstrate the adequacy of control measures for reducing the risk of a major incident so far as reasonably practical (SFARP). Loss of mechanical integrity allowing loss of primary containment (LOPC) is recognized as a possible initiating step for a major incident. Often LOPC results from the action of damage mechanisms such as corrosion that are able to degrade or destroy the mechanical integrity of the containment envelope of pressure equipment. LOPC, allowing a major incident, generally arises from human error in the form of a lack of recognition of a damage mechanism that should have been identified in a HAZOP or risk assessment and captured in a standard operating practice supported by relevant training. In this paper, a layers of protection framework is proposed for assessing the performance standards and performance indicators required of control measures to allow demonstration that likelihood of LOPC has been reduced SFARP, where LOPC has resulted from a damage mechanism such as corrosion. The context is the requirement to demonstrate adequacy of the practices used to assure the integrity of the containment envelope of pressure equipment required to prevent a major incident. The assessment includes examining the adequacy of inspection as a control measure including the RBI practice of using industry failure frequency databases to underpin the justification of an extension of inspection intervals. An improvement is proposed that recognizes the role of integrity operating windows (following API RP 584) for managing the process environment including providing evidence of control of the service conditions and recording excursions from nominal service conditions. Underpinning the proposed improvement is consideration of the contribution of human error to LOPC events and the need to recognize performance shaping factors that minimize error.

Ultrasonic Testing in Nuclear Plants

The approach for nondestructive testing inspections in nuclear power plants differs significantly from nonnuclear industries. In most industries, inspections are planned and specified by owners or insurance companies. Nuclear plant inspections are, however, regulated and must follow certain processes, regulatory requirements, and required codes. Codes classify components and specify inspection methods, coverage, and inspection intervals. With regard to ultrasonic testing (UT), there is a broad range of applications for nuclear plant components. Applications vary from simple corrosion/erosion scanning to more complex techniques that require UT of difficult-to-inspect materials. These include dissimilar metal welds of materials such as stainless steel, nickel alloy, and cast stainless steels. In addition, UT inspection can include tests of complex geometries such as nozzles and turbines. Furthermore, due to the nature of the nuclear plant operation, the inspection processes must be demonstrated to validate reliability and qualify equipment and personnel. Finally, this article highlights the importance of using notches as calibration reflectors when using refracted longitudinal waves and large aperture phased array probes to improve resolution.