Reliability Goals Research Articles

Equipment diagnostics based on comparison of past abnormal behaviors using a big data platform

Nuclear monitoring systems provide an increasing amount of realtime measurements to analyse equipment condition. Storage, retrieval, and effective use of information must therefore be made as efficient as possible in order to achieve reliability goals and additional reductions in operating costs. Combining them with other data sources like equipment characteristics, maintenance logs and previous expertise reports will help make better diagnostics while minimizing the time dedicated to an analysis hence leading to better maintenance decisions. This paper presents an overview of the project under study at EDF to develop a case based reasoning platform enabling experts to efficiently retrieve similarities between past events and the current situation. Several technical barriers are encountered such as the comparison of multidimensional time series, of textual information and the extraction of signal features. The problem is here framed as a pattern classification problem where the classes correspond to equipment faults. Similarity criteria have been defined and evaluated against nuclear power plants data for the diagnosis of abnormal patterns on critical equipment. The classification results are compared with service and expertise reports using clustering and classification algorithms. The prospect of this diagnosis is to support the adjustment of maintenance schedule by estimating the remaining useful life of critical equipment.

An Expanded Approach to Evaluating Open Access Journals

The advent of open access publishing necessitates evaluating the quality of a plethora of new journals. The problem of ensuring quality is inherent in the benefits and goals of open access publishing, which attempts to establish a system for reporting research findings that is inclusive and expeditious. However, inclusivity and speed may run counter to the goals of quality and reliability, and the pressure for researchers to publish creates incentives to participate in a fraudulent system. This paper presents an alternative approach to evaluating the legitimacy of open access publications. Those concerned about the quality of open access publishing have attempted to evaluate journals based on criteria that refer to externally available information. The approach used here provides additional, internal information about participation in journals' review processes. This additional information, namely, documentation of the process from submission through review to acceptance, is crucial for evaluating potentially fraudulent open access journals that might appear legitimate based on publicly available information.

Development of CO2 emission factors from a large circulating fluidized bed boiler

ABSTRACTGreenhouse gas emissions of the nation should be precisely assessed in order to effectively tackle the problems stemming from climate changes. To do so, country-specific data that reflect a nation’s distinct characteristics must be applied to more precisely assess greenhouse gas emissions. In this research, carbon emission factors were assessed for emission sources making up over 53% of the domestic anthracite consumption with calorific values of fuels and elementary analysis. Furthermore, oxidation rates were assessed based on measurement results of unburned carbon produced from tested power plants to calculate CO2 emission factors. Ultimately, the CO2 emission factor was calculated at 106,747 kg/TJ, about 9% higher than the anthracite emission factor presented by the Intergovernmental Panel on Climate Control. Such differences are assumed to mainly come from disparities of anthracite properties along with combustion technology and differences of oxidation rates depending on the combustion conditions. Therefore, continued research on a wide variety of fuels and energy consumption facilities should be conducted in order to establish country-specific data, which will help more accurately assess greenhouse gas emissions and subsequently will lead to reliable greenhouse gas reduction goals.

Corrosion Suppression with Redox Control in KCl-MgCl2 Under Flow

Solar power systems must be competitive with conventional energy sources in in terms of cost to make up a significant portion of the electric power grid. Solar power can likely more rapidly grow and make-up a larger portion of the US power grid if systems have energy storage capability that could continue to provide power for extended periods without sunlight and vary the power as needed (i.e. – be dispatchable). Concentrated solar power tower systems with thermal energy storage using advanced high operating temperature heat transfer fluids and advanced thermodynamic cycles can potentially meet the twin goals of low cost and high reliability while being dispatchable. Molten salts are a promising candidate for a high operating temperature heat transfer fluids. Due to the decomposition of molten nitrates at temperatures above about 550 °C, molten fluorides or chlorides are expected to be needed for higher temperature operation. KCl-MgCl2 is a promising heat transfer fluid due to its low cost and good thermal transport properties. Corrosion in molten chloride salts can be severe if salt chemistry is not well controlled. Research has shown that the main corrosion mechanism in Fe-Ni-Cr alloys exposed to molten salts is selective oxidation of Cr and that the corrosion mechanism is mass transfer limited. In the research to be presented, thermosiphons were operated at three different temperature ranges to add flow to corrosion tests and evaluate changed corrosion rates. Four alloys were tested in the thermosiphons with varying temperature and with and without Mg redox control. The most extreme case tested had the hot region at ~930 °C and cold region at ~880C. The research found that naturally convective flow could increase up to 5 times the corrosion compared to static tests for Haynes-230 without corrosion inhibition. Corrosion inhibition using Mg worked well to decrease corrosion and mass transfer reactions for Fe, Co, and Ni based superalloys.

Hybrid wireless sensor networks: a reliability, cost and energy‐aware approach

Wireless sensor networks (WSNs) consist of spatially distributed sensor nodes to monitor physical or environmental conditions. These sensor nodes are typically battery-powered sensor nodes (BPSNs) and can rarely meet design goals of long network lifetime and high reliability. Energy-harvesting sensor nodes (EHSNs) that convert different types of energy to electrical energy are an alternative type of sensor nodes with a long lifetime but a high cost. Combining BPSNs and EHSNs has potential to deal with the conflicting design goals of long lifetime and reasonably low cost. In this study, the authors make new contributions by modelling a heterogeneous WSN consisting of both BPSNs and EHSNs and proposing a comprehensive cost function-based routing approach that integrates end-to-end path reliability, cost and energy consumption for providing satisfactory quality of service to applications running on hybrid WSNs. Another contribution made in this work is the optimal deployment of EHSNs using a reliability-importance-analysis-based method to improve the end-to-end path reliability within hybrid WSNs.

Drift, adaptation, resilience and reliability: Toward an empirical clarification

Much recent organizational writing, under the influence of complexity theory, describes adaptation and resilience as increasingly important organizational requirements. This emphasis, while undeniably significant, is based upon highly generalized and abstracted concepts which, as several scholars in the field have noted, have yet to produce specific researchable propositions. A particularly problematic aspect of the emerging literature on adaptation and resilience has been its treatment of research related to our understanding of high reliability organizations (HROs), organizations that must carefully manage potentially hazardous technical systems which if mismanaged could lead to catastrophic failures and cost many lives. The emphasis on adaptation and resilience we argue has led to distorted depictions of these organizations and the foundations of their reliability. Localized adaptations to complex or unpredictable situations of the sort depicted in some resilience models could actually be negative developments in relation to the pursuit of larger reliability and safety goals in these organizations.In this article, we describe a particular type of “reliability drift” which can be differentiated from adaptation. We will identify, within the context of previous and ongoing HRO research, features that actually constitute a successful strategy of reliability drift management in these organizations. This strategy includes resilience, but of a form we term “precursor resilience” – a type different from the “rebound from failure” resilience or the process of “managing the unexpected” described in some resilience literature. As we will demonstrate, for HROs it is more the expansion of expectancies that accounts for their reliability than managing the unexpected. HROs have developed strategies for managing and regulating drift while still preserving their flexibility to adapt in a constant search for improvement. We discuss the potential implications of our argument for identifying and assessing specific types of resilience and their requirements, based on a closer grounding of them in empirical research.

A resilience-based prioritization scheme for water main rehabilitation

Water supply infrastructure in the United States is one lifeline system that is in dire need of huge financial investments to counter pipeline deterioration while keeping up with increasing demands and reliability goals. With decreasing financial resources available to state and local governments, effective decision-making tools for pipeline prioritization are becoming an increasingly integral part of the water utility industry. A majority of existing prioritization frameworks are merely based on the likelihood of the failure of pipelines and the resulting consequences, with little consideration given to the utility's response time to a water pipeline failure. This paper presents a novel resilience-based framework for effective prioritization of water distribution pipelines. The novelty lies in estimating the utility's response time to a pipeline failure. The proposed framework is demonstrated on a section of a real water distribution network in a coastal city of the United States. The pipeline priority results obtained are also compared with those from a more traditional risk-based prioritization scheme, and a reasonably significant difference has been observed. While availability of quality data is a challenge, this study brings to attention the importance of response time to water pipeline failures and demonstrates the merits of incorporating it in a prioritization scheme.

A fuzzy multi-objective genetic algorithm for system reliability optimisation

The problem of optimising system reliability is often confronted with imprecise goals concerned with reduction of system costs and improvement of system reliability. Due to the presence of imprecise parameters, the impact of the decision is fuzzy and multi-objective. The present paper models the problem as a fuzzy multi-objective nonlinear program. To effectively handle the fuzzy goals and constraints of the multi-objective decision problem, a fuzzy multi-objective genetic algorithm approach (FMGA) is proposed. The proposed approach is flexible; it allows for generation of intermediate solutions, which eventually lead to high quality solutions. By using fuzzy membership functions, FMGA incorporates the decision maker's preferences and choices that influence system costs and reliability goals. Computations based on benchmark problems demonstrate the utility of the approach.

Contribution for Analysing, Saving and Prioritising of Lessons Learned Issues Regarding Product Improvement and Future Product Generations

Based on the customer's product recognition, environment protection becomes key sales arguments within the consumer goods industry. Customers expect longer usage phase of products and reduced use of resources. Product reliability may help to save resources in many ways such as replacement of parts and minimizing logistic efforts throughout the product's life span. To achieve the generic goal of reliability and sustainability, it is important to learn from product's failures during design, manufacturing and use phase. Therefore, structured knowledge regarding a long life cycle (e.g. development: 2 years; production: 6 years; usage: 15 years) should be saved. This paper outlines a conceptual Lessons Learned approach on how to analyse, save and prioritise Lessons Learned issues – based on structured weak point data and information - out of the product life cycle to improve reliability and sustainability of the subsequently product generation.

Using Reliability Modeling and Accelerated Life Testing to Formulate a Cost Model of Photovoltaic Systems with Different Architectures

As the number of photovoltaic (PV) systems grows annually and ages, the importance of long term reliability to the levelized cost of electricity (LCOE) has become increasingly clear. Likewise innovative PV system architectures being considered present opportunities for differentiation and growth into new markets, but still need to have a model for system reliability in order to justify their LCOE. Other benefits of reliability modeling include setting reliability goals for individual failure modes, determining optimum replacement and maintenance strategies, as well as prioritizing which failure modes require the most consideration in terms of research and testing. Physics of failure and materials properties are key inputs to the outcome of these models. This paper presents the results of reliability models based on accelerated testing, field data and theoretical calculations that were undertaken in order to determine the cost model of reliability of PV systems of different system architectures. Three examples for PV modules are presented here (bypass diodes, solder joints and microinverters) and are used to show how understanding of the reliability of systems based upon materials properties can be used to formulate models for lifetime and costs.

RAIDShield

Modern storage systems orchestrate a group of disks to achieve their performance and reliability goals. Even though such systems are designed to withstand the failure of individual disks, failure of multiple disks poses a unique set of challenges. We empirically investigate disk failure data from a large number of production systems, specifically focusing on the impact of disk failures on RAID storage systems. Our data covers about one million SATA disks from six disk models for periods up to 5 years. We show how observed disk failures weaken the protection provided by RAID. The count of reallocated sectors correlates strongly with impending failures. With these findings we designed RAIDS hield , which consists of two components. First, we have built and evaluated an active defense mechanism that monitors the health of each disk and replaces those that are predicted to fail imminently. This proactive protection has been incorporated into our product and is observed to eliminate 88% of triple disk errors, which are 80% of all RAID failures. Second, we have designed and simulated a method of using the joint failure probability to quantify and predict how likely a RAID group is to face multiple simultaneous disk failures, which can identify disks that collectively represent a risk of failure even when no individual disk is flagged in isolation. We find in simulation that RAID-level analysis can effectively identify most vulnerable RAID-6 systems, improving the coverage to 98% of triple errors. We conclude with discussions of operational considerations in deploying RAIDS hield more broadly and new directions in the analysis of disk errors. One interesting approach is to combine multiple metrics, allowing the values of different indicators to be used for predictions. Using newer field data that reports an additional metric, medium errors , we find that the relative efficacy of reallocated sectors and medium errors varies across disk models, offering an additional way to predict failures.

IMPROVEMENT IN RELIABILITY INDICES OF A POWER DISTRIBUTION SYSTEM: A CASE STUDY

Frequent occurrence of failures is common in Electrical Power Distribution Systems. The consequences of failure include high cost of maintenance, undesirable effects and risks which affect the power consumers. The important goals of reliability and maintainability of distribution systems are availability of continuous power and meeting the load requirements. The Power Distribution System at SIPRA Labs (BALANAGAR FACILITY) consists of three phase and single phase loads. In this work Reliability Analysis is conducted for each component like Miniature Circuit Breaker (MCB), Moulded Case Circuit Breaker (MCCB) and other different components by calculating failure rate and repair rate individually on yearly basis. Mean Time To Failure (MTTF), Mean Time To Repair (MTTR), Mean Time Between Failure (MTBF) of the overall system are calculated from failure rate and repair rate of each component. Customerand Load-Oriented indices of overall Power Distribution System are predicted from load details, failure rate and Unavailability under each feeder line. MATLAB Programming is developed for overall system reliability analysis.

In the quantitative automata zoo

Quantitative model checking and performance evaluation deal with the analysis of complex systems that must not only satisfy correctness requirements, but also meet performance and reliability goals. Models of such systems therefore need to represent the necessary quantitative information about probabilistic decisions, real-time phenomena, or continuous dynamics. At the same time, nondeterminism needs to be properly captured as in classical verification, so as to enable abstraction and compositional modelling. These aspects span a large spectrum of automata-based quantitative models which have been studied in the verification and performance evaluation literature. In this paper, we embark on a guided tour through this zoo of quantitative models. Starting from the basic formalisms of labelled transition systems and also Markov chains, we look at how timed and hybrid automata add real-time aspects as well as continuous dynamics, and we study extensions that provide for behaviour governed by discrete and continuous probability distributions. For each of the automata models, we outline its definition, provide a small illustrative example, summarise its expressive power, and survey available formal analysis techniques as well as selected practical applications.

Criterion‐Related Validity: Assessing the Value of Subscores

Criterion‐related profile analysis (CPA) can be used to assess whether subscores of a test or test battery account for more criterion variance than does a single total score. Application of CPA to subscore evaluation is described, compared to alternative procedures, and illustrated using SAT data. Considerations other than validity and reliability are discussed, including broad societal goals (e.g., affirmative action), fairness, and ties in expected criterion predictions. In simulation data, CPA results were sensitive to subscore correlations, sample size, and the proportion of criterion‐related variance accounted for by the subscores. CPA can be a useful component in a thorough subscore evaluation encompassing subscore reliability, validity, distinctiveness, fairness, and broader societal goals.

RELIABILITY-BASED SELECTION OF STANDARD STEEL BEAMS

A reliability-based design approach using sensitivity analysis is presented for the selection of standard steel beams subjected to concentrated and or distributed loads, assuming lognormal probability density function. Serviceability criteria of bending stress, transverse deflection, and web maximum shear stress are considered. The load, strength, and geometric parameters are considered to be log normal in distribution. Equations are developed for the coefficients of variation for the mentioned serviceability criteria so as to determine design reliability. Deterministic design equations are transformed into probabilistic ones by replacing the traditional “safety factor” with a “reliability factor”. The reliability factor is determined from a specified reliability goal and the coefficients of variation in design models and parameters. Design examples are presented and results are compared with solutions based on the traditional ASD (Allowable Stress Design) method. Two of the four design examples have identical solutions with the ASD method. The third example result is practically the same as that of ASD method, except that the beam is slightly lighter. The fourth example has a similar result as the ASD method but the beam is deeper. The deeper beam solution stems from the use of both bending stress and deflection serviceability criteria in the new approach while only the bending stress criterion was used in the ASD method. All the chosen beams indicate a reliability of at least 99.73% for bending stress and at least 95.22% reliability for deflection. In all the chosen beams, the web maximum shear stress has a reliability factor of at least 4.91, making shear failure improbable. The agreement between the results of these different methods is amazingly interesting. All computations in the study were done on Microsoft Excel Spreadsheet, demonstrating that probabilistic design can be done with inexpensive computer resource and not too advanced analytical skills. This study shows that acceptable design solutions can be achieved by modification of deterministic or traditional design method through probabilistic consideration of “design or safety factor”. From the very favorable comparison of the results between the new approach and ASD method, it appears reasonable to conclude that the method proposed in this paper is satisfactory for the probabilistic design of standard steel beams. The covs for practical design applications should be based on data from material vendors and historical data on loads. Engineering companies providing design services would have such data and a simple statistical analysis will give realistic cov values for use in their design practice.

전자패키지 신뢰성 예측을 위한 최적 구간중도절단 시험 설계

Qualification includes all activities to demonstrate that a product meets and exceeds the reliability goals. Manufacturers need to spend time and resources for the qualification processes under the pressure of reducing time to market, as well as offering a competitive price. Failure to qualify a product could result in economic loss such as warranty and recall claims and the manufacturer could lose the reputation in the market. In order to provide valid and reliable qualification results, manufacturers are required to make extra effort based on the operational and environmental characteristics of the product. This paper discusses optimal interval censoring design for reliability prediction of electronic packages under limited time and resources. This design should provide more accurate assessment of package capability and thus deliver better reliability prediction.

Bus Transit Service Reliability and Improvement Strategies: Integrating the Perspectives of Passengers and Transit Agencies in North America

Transit agencies are consistently trying to improve service reliability and attract new passengers by employing various strategies. Previous literature reviews have focused on either passengers' or transit agencies' perspectives on service reliability. However, none of the earlier reviews have simultaneously addressed these differing perspectives on service reliability in an integrated manner. In response to this gap in the literature, this paper first reviews previous work on passengers' perspectives of transit service reliability and their response to service adjustments made by different agencies. Second, it analyzes transit agencies' plans and reports regarding their reliability goals and used strategies in order to improve service reliability, while looking at the impacts of these strategies on service. Reviewing these two parts together provides a needed contribution to the literature from a practical viewpoint since it allows for the identification of gaps in the public transit planning and operations field in the area of reliability and provides transit planners and decision makers with effective and valuable policy-relevant information.

Prediction of software inter-failure times using artificial neural network and particle swarm optimisation models

Knowledge of time between failures is required for achieving certain reliability goal in a given amount of testing to determine release time of a software. In practice, existing artificial neural network (ANN) models to predict time between failures utilise complex and variable architecture. In this paper, an ANN model and an ANN-PSO model with fixed and simple architecture are proposed to predict time between failures. Effects of scaling time between failures data have been analysed using logarithmic function. In ANN model, the scaling parameter of logarithmic function is determined by varying maximum scaled value in a certain range. In ANN-PSO model, the scaling parameter is determined automatically during ANN training using particle swarm optimisation (PSO) algorithm. Proposed models are applied on literature reported datasets and found that ANN-PSO model provides better performance than ANN model trained using back propagation algorithm in terms of normalised mean square error.

Development of 2.5D and 3D IC Fabrication and Assembly Technologies

2.5D/3D IC assembly is where the traditional foundry and assembly house model breaks down. The greatly reduced feature sizes of microbumps in combination with very large, thin interposers and ICs present many challenges for assembly. With densely integrated packages and stacked thin dies, warpage at various steps of assembly process can lead to die crack, weak or open interconnection, and delamination. Microbump die with copper pillar and solder cap lacks the flexibility of conventional BGA solder balls in warpage compensation. Low temperature dielectric materials for interposer backside passivation lack chemical, thermal stability and mechanical strength compared to similar materials cured at higher temperatures. Ultra- low stand-off between dies creates new challenge for flux residue removal and underfill processing, adhesion and reliability. In this paper, we present learning and results from building two Invensas 2.5D interposer test vehicles with rectangular (19mmx27mm) and square (24mmx24 mm) silicon interposers. Since the industry is still debating where the MEOL processes will take place, these two test vehicles use both assembly centric and fab centric flows. We conducted comprehensive material and process compatibility studies to meet our goal of process capability and product reliability. We explored three different interposer fabrication/ assembly flows that includes copper-to-copper bonding as well as solder capped copper pillar microbumps for microbump die to interposer connection. We optimized the interposer fabrication process to improve interposer quality and warpage. We instituted 100% bump inspection and tight control on microbump die quality and co-planarity to improve assembly yield. We developed robust soldering and cleaning processes to achieve high soldering process yield. We evaluated several methods of flux clean and developed a procedure to achieve optimal flux residue removal without causing mechanical damage to solder joints. We explored vacuum and pressure curing process for underfill and adopted advance underfill cure technology to eliminate voids in underfill. The impact of these factors on assembly yield and reliability will be presented.

Fluid resuscitation in severe sepsis and septic shock: Shifting goalposts.

Fluid resuscitation in severe sepsis and septic shock: Shifting goalposts.