Component Failure Rates Research Articles

Effect of Grid Instability on Power Generation System's Reliability

Aims: Reliability assessment of power generation system may be performed with the concept of system adequacy, security or both. Grid being a major component in the power distribution chain is seen to have some influence on the state of the generation system reliability because of the perturbation that may arise from it. In this study, the generation system reliability is evaluated using both the system adequacy and security concept.
 Study Design: To capture the system security problems attributed to grid disturbance, the generation system is structured into two component systems (1 - generation component and 2 - transmission component) with a series arrangement.
 Methodology: The reliability indices such as, mean time to failure, mean time to repair, failure rate and repair rate are assessed on component bases and with respect to the entire generation system.
 Results: The effect of failure rate of the transmission component on the entire generation system failure rate was evaluated as 66.25%, 55.55%, 33.33%, 55.00% and 35.72% in year 2013, 2014, 2017 2018 and 2019 respectively for FIPL Power Plant and 52.94%, 82.35%, 61.38% and 100% effect was evaluated in the year 2016, 2017, 2018 and 2019 respectively for GT5 of Omoku Power Plant.
 Conclusion: These results showed that there is a significant influence of grid disturbances on the reliability state of the two gas turbine power plants in Nigeria. Measures on possible reliability state improvement of the power generation systems were suggested to include training and retraining of technical personnel on the management of major equipment in the generation and transmission stations.

Estimation of the Reliability of the Gear–Motor System Using a Markov Model

In this article, the reliability of a gear–motor system is analyzed on the condition that the failure of the gear leads under certain circumstances to the failure of the motor. The states of the system are modeled by a continuous-time Markov chain. The resulting system of differential equations is solved using the Laplace transform. In this way, the probabilities of the system’s states can be determined for different failure and repair rates of individual components depending on time and comparative analysis of the availability can be performed.

Techno-economic analysis of a hydraulic transmission for floating offshore wind turbines

Mechanical gearboxes have one of the highest failure rates of wind turbine components while being one of the most expensive parts to replace or service. They are easily fatigued and have a low power rating relative to their size and mass. In this article, hydraulic transmissions are proposed as an alternative to mechanical drive trains and their feasibility has been established, particularly for offshore wind turbine applications. Here, we provide an in-depth analysis regarding the techno-economic benefits of replacing the mechanical gearbox with a hydraulic transmission in an offshore system. Our analysis shows that hydraulic transmissions are particularly beneficial for offshore applications: (i) relocating 35.3% of the nacelle mass to the base, thus moving the center of gravity toward the ground level, (ii) diminishing operation and maintenance costs, and (iii) replacing now-redundant power electronics. These three benefits contribute to saving between 3.92 and 18.8% on the Levelized Cost of Electricity for average cost offshore wind turbines.

A reliability study of electric vehicle battery from the perspective of power supply system

Battery cells and modules are critical to the reliability of the power supply system of an EV. Therefore, their reliability is mainly concern before. However, EV's power supply system is a complex system. Besides battery cells and modules, it also includes many other components, the failure of which can cause a breakdown of the system as well. So, the reliability of the battery should be evaluated from the perspective of the entire power supply system rather than only considering the reliability of the battery cells and modules. This motivates the research of this paper. In the present study, the failure rates of all major components are predicted first. Then, based on the prediction results, the reliability of the entire battery system is assessed. From the assessment results, it is found that the reliability of the entire battery system is indeed much lower than those of individual components including battery modules. Moreover, as compared to the degradation of individual components, the entire system degrades more rapidly over time. Additionally, it is interestingly found that the Battery Management System (BMS) controller is not as reliable as the battery modules in the battery system considered in this paper.

Cost minimization of repairable systems subject to availability constraints using efficient cuckoo optimization algorithm

AbstractSystem availability is a key element for any industry. System designers and operators try to do their best to maintain the required availability of the systems to avoid production stoppages. They set up and undertake different maintenances, and these interventions imply cost. Therefore, the goal is to minimize the cost, but considering the constraint of the availability requirement. The problem involves three main aspects: redundancy allocation, component failure rates, and repair rates. In this paper, a novel solution approach is proposed based on an efficient cuckoo optimization algorithm (EF‐COA). Two numerical case studies are solved, and the results confirm the effectiveness of the approach proposed.

Bayesian Optimized Mixture Importance Sampling for High-Sigma Failure Rate Estimation

In many application domains, in particular automotives, guaranteeing a very low failure rate is crucial to meet functional and safety standards. Especially, reliable operation of memory components such as SRAM cells is of essential importance. Due to aggressive technology downscaling, process and runtime variations significantly impact manufacturing yield as well as functionality. For this reason, a thorough memory failure rate assessment is imperative for correct circuit operation and yield improvement. In this regard, Monte Carlo (MC) simulations have been used as the conventional method to estimate the variability induced failure rate of memory components. However, MC methods become infeasible when estimating rare events such as high-sigma failure rates. To this end, importance sampling (IS) methods have been proposed which reduce the number of required simulations substantially. However, existing methods still suffer from inaccuracies and high computational efforts, in particular for high-sigma problems. In this article, we fill this gap by presenting an efficient mixture IS approach based on Bayesian optimization, which deploys a surface model of the objective function to find the most probable failure points. Its advantages include constant complexity independent of the dimensions of design space, the potential to find the global extrema, and the higher trustworthiness of the estimated failure rate by accurately exploring the design space. The approach is evaluated on a 6T-SRAM cell as well as a master–slave latch based on a 28-nm FDSOI process. The results show an improvement in accuracy, resulting in up to $63\times $ better accuracy in estimating failure rates compared to the best state-of-the-art solutions on a 28-nm technology node.

Ecological environment fuzzy networking system protection based on optical fiber intelligent network

The optical fiber network has the characteristics of providing users with wider bandwidth and supporting the changing needs of more users. At the same time, the optical fiber network can also reduce the network infrastructure investment. The traditional Ad Hoc On-demand Distance Vector (AODV) algorithm does not consider the impact of node movement on the network, and the link disconnection frequently occurs during the routing process. The ant colony algorithm based on swarm intelligence only considers the unique factor of pheromone concentration to find the optimal path through multiple iterations, which will increase the complexity of the algorithm and affect the route establishment delay. In response to the above problems, this paper proposes a routing algorithm based on fuzzy logic. The algorithm can comprehensively consider the three factors of node location, mobility and signal strength, and greatly reduces the complexity of the algorithm. This paper gives a detailed definition of profust reliability of the Ethernet Passive Optical Network (EPON) system for distribution network communication and obtains the profust reliability parameters based on Monte Carlo simulation. After that, the reliability of profust under different networking modes was simulated, and the influence of network scale, component failure rate, component repair time and other parameters on the reliability of EPON networking profust was analyzed. The fuzzy probist reliability analysis method uses analytical methods, which are commonly used to deal with end-to-end reliability analysis problems and has certain limitations. Profust reliability analysis treats the system as a whole, which is more suitable for the reliability of complex end-to-multi-end systems.

Search the optimal ratio of system’s component reliability parameters and the heat capacity of prosumers in the district heating system

The paper presents a methodology for ensuring the reliability of heat supply to prosumer connected to a district heating system, by using the heat capacity of its own heat source and optimization of failure rates of system components. To solve this problem, a mathematical formalization is developed, within which a markov random process, a flow distribution model of the theory of hydraulic circuits, nodal reliability indices, and simplified models of heat transfer processes in heat supply to consumers are used. A case study is considered based on a test scheme of district heating system with prosumer, an analysis of the results obtained is carried out, conclusions and directions for the further research on the subject are formulated.

A Detailed Reliability Study of the Motor System in Pure Electric Vans by the Approach of Fault Tree Analysis

Attributing to the unique feature of zero carbon emission, electric vehicles (EVs) are attracting increasing interest in recent years, but their reliability, particularly the reliability of their critical components, is still a matter of concern today. In order to address this issue, much effort has been made before to assess the reliability of drive motor in the EVs. However, drive motor and motor controller are logically integrated and requested to work as one system in the EVs. In contrast to the individual reliability analysis of them, the combined assessment of the two parts can provide a more reliable prediction to the reliability of the entire motor system. Moreover, both drive motor and motor controller are composed of multiple components. The structure, type, and characteristics of these components may affect the reliability of the motor system as well. But these issues have not been considered in the previous research. In order to fill this gap of knowledge, the reliability of the entire motor system of pure electric vans that includes both drive motor and motor controller is investigated in this paper. In the research, the theoretical failure rates of subassemblies and components in drive motor and motor controller are predicted first. Then based on the failure rate prediction results, the reliability of the entire motor system (comprising both drive motor and motor controller) is assessed. Based on the assessment results, some interesting conclusions with respect to the most vulnerable subassemblies and components in the entire motor system and the potential disadvantage of existing reliability research are finally obtained. It is deemed that these new findings will be of great significance to the future reliability design and maintenance of pure electric vans.

Water Distribution System Pipe Break Failure Modeling and Analysis: Case Study of Kuwait

The Ministry of Electricity and Water (MEW), as well as other water authorities all over the world, is facing a difficult challenge in assessing the physical condition of its distribution systems. Since the majority of the mains are buried, the MEW must rely upon indirect methods, including analysis of repair records. A case study on Kuwait’s water distribution system using the techniques of survival analysis is analyzed and investigated for modeling the pipe break failures. The proportional hazard model has the advantage of being able to separate the effects of component deterioration on failure due to aging from the effects of site‐specific causes. Another desirable feature is its ability to analyze censored data. The sensitivity of the model parameters to sample size and percent censoring is examined through random sampling of the database. In addition, the proportional hazard model is suitable for describing failure rates of components.

Maintenance optimisation for multi-component system with structural dependence: Application to machine tool sub-system

Maintenance plays a key role in controlling manufacturing systems within normal operations. Consistent control within production requirements is difficult due to the complexity of manufacturing systems; that is, many components that are economically and structurally interdependent. Structural dependence between components implies that maintenance requires the disassembly of other, obstructing components. The disassembly may affect the failure rate of components and modify the maintenance plan. We proposed a maintenance optimisation model considering both economic and structural dependencies between components. The impact of structural dependence on the reliability of components was reviewed using a Proportional Hazard Model. The model implemented influencing factors such as component features, the system structure, and the production context. It supported a more accurate reliability assessment. We derived an adaptive maintenance strategy that integrated these dependencies and developed a cost-based optimisation model to determine a prudent maintenance plan. We conducted a case study on a spindle of a milling machine to prove feasibility and the model's ability to reliably assess and optimally maintain operations.

Operational reliability evaluation of PV inverter considering relative humidity and its application on power system

With the penetration of renewable energy in the power system gradually increases, the importance of power electronics is growing up. The reliability of the power electronics should be taken seriously. This paper focuses on the operational reliability of photovoltaic (PV) inverters which is the most vulnerable in grid-connected PV systems and its application on the reliability evaluation of power systems. According to the field data, the effect of relative humidity is nonnegligible to the reliability of PV inverters. First, the real-time failure rate of components in PV inverters calculation method considering relative humidity is presented. Then the operational reliability evaluation of PV inverters is proposed. Finally, the reliability of power system including grid-connected PV systems is evaluated. It is aimed to explore a bottom-up approach to "effect factors-components-devices-system" reliability evaluation to establish a link between the components/devices and system. In this paper, the numerical examples verify the necessary of considering relative humidity in reliability evaluation. The evaluation results of PV inverters are used to the Roy Billinton Test System (RBTS). The analysis shows the results may affect the overall system performance.

Reliability evaluation of an aggregate battery energy storage system in microgrids under dynamic operation

A microgrid (MG) which mainly consists of distributed generators (DGs) and energy storage systems (ESSs), is deployed to supply power for local loads. Distributed generators are mostly renewable energy sources. An aggregate system with multiple battery energy storage devices that should be used to improve the reliability of power supply from these renewable energy sources in the MG, is defined as an aggregate battery energy storage system (ABESS). The ABESS is used to control the source-load power balance so that the MG can operate at high stability and reliability to supply electricity for different customers. To demonstrate the significance of the ABESS in the MG, its operation reliability will be analyzed in this paper. A systematic method is proposed to evaluate reliability performance of the ABESS under different dynamic operation cases in the MG. Specifically, an analytic approach based on Markov models is developed to assess the operation reliability of the whole ABESS. Besides the used-time-dependent failure rates, voltage-fluctuation and power-loss dependent failure rates (VF-PL DFR) of critical components of the ABESS such as bidirectional DC/DC converters, DC/AC inverters, switching and protective devices, battery modules, and battery charger/controller are also formulated and incorporated in the reliability evaluation. According to differently dynamic operation cases of a microgrid with the ABESS and photovoltaic (PV) generation systems, the VF-PL DFR of the ABESS will be variously affected. Randomly dynamic operation scenarios of the MG are analyzed including: change in load power, the intermittent and unstable operation of PV sources, on/off-grid operation modes of the microgrid, and discharging and charging states of the ABESS. Simulation test results are presented and discussed to validate that the operation reliability of the ABESS in the microgrid significantly depends on its differently dynamic operation strategies along with the applied voltage stress.

Usulan Pembaharuan jadwal Kegiatan Preventive Maintenance pada Mesin Curing PCR PT.XYZ Menggunakan Metoda Distribusi Weibull

Seringnya terjadi kegiatan perawatan (downtime) tidak terencana mesin Curing pada line produksi ban mobil PT XYZ merupakan indikasi adanya ketidakefektifan perawatan terencana (PM) yang diterapkan perusahaan. Downtime tidak terencana menyebabkan line produksi berhenti dan kehilangan waktu berproduksi, meningkatnya jumlah produk gagal saat setup, dan tingginya biaya perawatan mesin produksi. Perusahaan perlu meningkatan efektivitas dan efisiensi kinerja system perawatan melalui pembaharuan jadwal perawatan agar availability mesin tinggi. Tujuan penelitian ini adalah mengidentifikasi komponen penyebab kegagalan fungsi mesin curing dan menghasilkan rekomendasi waktu interval perawatannya yang sesuai. Metoda distribusi Weibull digunakan untuk mendapatkan nilai index of fit time to failure beberapa komponen kritis mesin, menganalisa laju kerusakan komponen, menghitung nilai mean time between failure (MTBF) komponen sebagai durasi expected lifetime komponen tersebut. Hasil yang diperoleh menunjukkan bahwa terdapat dua komponen kritis pada mesin curing dengan indikasi laju kerusakan seiring waktu (nilai β>1), yaitu silinder press dan EPV dengan nilai MTBF sebesar 89 hari untuk silinder press dan 231 hari untuk EPV. Hasil kajian ini mengusulkan pembaharuan jadwal PM mesin curing agar mempertimbangkan penambahan kegiatan PM baru yang mengakomodir nilai durasi expected lifetime dari komponen-komponen penyebab mesin breakdown, sehingga dapat meminimalkan downtime tidak terencana.

Comparative Analysis of Radiotherapy Linear Accelerator Downtime and Failure Modes in the UK, Nigeria and Botswana

The lack of radiotherapy linear accelerators (linacs) in low- and middle-income countries (LMICs) has been recognised as a major barrier to providing quality cancer care in these regions, together with a shortfall in the number of highly qualified personnel. It is expected that additional challenges will be faced in operating precise, high-technology radiotherapy equipment in these environments, and anecdotal evidence suggests that linacs have greater downtime and higher failure rates of components than their counterparts in high-income countries. To guide future developments, such as the design of a linac tailored for use in LMIC environments, it is important to take a data-driven approach to any re-engineering of the technology. However, no detailed statistical data on linac downtime and failure modes have been previously collected or presented in the literature. This work presents the first known comparative analysis of failure modes and downtime of current generation linacs in radiotherapy centres, with the aim of determining any correlations between linac environment and performance. Logbooks kept by radiotherapy personnel on the operation of their linac were obtained and analysed from centres in Oxford (UK), Abuja, Benin, Enugu, Lagos, Sokoto (Nigeria) and Gaborone (Botswana). By deconstructing the linac into 12 different subsystems, it was found that the vacuum subsystem only failed in the LMIC centres and the failure rate in an LMIC environment was more than twice as large in six of the 12 subsystems compared with the high-income country. Additionally, it was shown that despite accounting for only 3.4% of the total number of faults, linac faults that took more than 1 h to repair accounted for 74.6% of the total downtime. The results of this study inform future attempts to mitigate the problems affecting linacs in LMIC environments.

Improving Energy Efficiency and Minimizing Backhaul Traffic in LTE-A Network with Cooperation and DTX Mechanism

The promising approach to enhance energy efficiency (EE) in LTE-A network is to switch underutilized evolved node B (eNB) to sleep mode, but it increases the transmission power to guarantee the coverage under the remaining active eNBs. The increase in transmission power can be reduced by coordinated multi-point (CoMP) technique through eNB cooperation, but this technique consumes extra power due to backhaul traffic and signal processing. This problem can be solved by the proposed energy efficient acceleration factor failure rate (EEAFR) algorithm. The algorithm jointly considers the eNB cooperation and DTX mechanism to minimize the backhaul traffic with less failure rate. Also, to enhance energy efficiency, the proposed algorithm efficiently utilizes the cooperation in all traffic load scenarios based on the decision criteria and DTX mechanism. The results are compared with the existing AFEE and Green CoMP with Backhaul Traffic algorithm. In all the traffic loads EEAFR save 59.8% energy and reduces the network outage which depends on the failure rate of the eNB components

Analysis of Historical Transformer Failure and Maintenance Data: Effects of Era, Age, and Maintenance on Component Failure Rates

For several decades, The U.S. Army Corps of Engineers has maintained a unique database of equipment failure and maintenance data for critical facilities. This article takes a closer look at historical transformer failure and maintenance data, and provides a unique analysis of failure trends. Detailed analysis shows that failure rates for different categories of transformers demonstrate unique trends over time, with equipment age, and with respect to preventative maintenance levels. By analyzing over 144 thousand unit years of operational data, this article paints a more complete picture of component reliability. The data show that careful consideration of detailed failure and maintenance can better upgrade facility design and maintenance decisions, ultimately leading to improved system reliability and reduced operational costs.

Dynamic reliability assessment of flare systems by combining fault tree analysis and Bayesian networks

ABSTRACT Flaring is a combustion process commonly used in the oil and gas industry to dispose flammable waste gases. Flare flameout occurs when these gases escape unburnt from the flare tip causing the discharge of flammable and/or toxic vapor clouds. The toxic gases released during this process have the potential to initiate safety hazards and cause serious harm to the ecosystem and human health. Flare flameout could be caused by environmental conditions, equipment failure, and human error. However, to better understand the causes of flare flameout, a rigorous analysis of the behavior of flare systems under failure conditions is required. In this article, we used fault tree analysis (FTA) and the dynamic Bayesian network (DBN) to assess the reliability of flare systems. In this study, we analyzed 40 different combinations of basic events that can cause flare flameout to determine the event with the highest impact on system failure. In the quantitative analysis, we use both constant and time-dependent failure rates of system components. The results show that combining these two approaches allows for robust probabilistic reasoning on flare system reliability, which can help improving the safety and asset integrity of process facilities. The proposed DBN model constitutes a significant step to improve the safety and reliability of flare systems in the oil and gas industry.

Adequacy studies of power systems with barrage‐type tidal power plants

Tidal as renewable energy is increasingly utilised for power generation in many countries. Integration of tidal plants into the power system requires considering the intermittent nature of the generated power caused by variable tide levels. Thus, the reliability studies of power systems including high tidal generation affected by the uncertain nature resulting from the variable water levels are investigated. The reliability model of a tidal power plant on a barrage is proposed. In the proposed model, the failure rates of the composed components (especially the hydro pump and gate) and the effect of tidal height variation on the components failure rate are considered. Also, the reliability model with numerous states resulting from the variability of the generated power through the fuzzy C-means clustering technique and Xie-Beni index is reduced to a multi-state reliability model. The resulting reliability model is utilised for the generation adequacy studies of a power system containing large-scale tidal power plants. Moreover, different reliability indices are calculated for future generation expansion planning. The proposed technique is applied to the two-test systems, and sensitivity analysis is performed. Besides, the effects of the hydro pump, maintenance, ageing of the components and peak load are investigated.

Reliability modeling methods for load-sharing k-out-of-n system subject to discrete external load

Most reliability modeling methods for the load-sharing k-out-of-n system are based on the assumed lifetime distribution and the relation function between the component failure rate and component load. However, the relation function is difficult to determine since the failure rate data have to be acquired. Therefore, this paper aims to develop a more direct reliability model for the load-sharing system based on the generalized load-strength model. In the presence of discrete external load, the proposed method utilizes the load distribution variation and strength damage after component failures to directly reflect the load-sharing effect, which can avoid measuring the failure rate. Further, the existing failure-rate-based reliability modeling method is also improved since the direct relation function between the component failure rate and component load is deduced. Two methods are both illustrated through the reliability analysis of a load-sharing redundant micro-engine system.