Multi-State System Reliability: A New and Systematic Review

AbstractReliability analysis considering multiple possible states is known as multi-state (MS) reliability analysis. Multi-state system reliability models allow both the system and its components to assume more than two levels of performance. Through multi-state reliability models provide more realistic and more precise representations of engineering systems, they are much more complex and present major difficulties in system definition and performance evaluation. MSS reliability has received a substantial amount of attention in the past four decades. This article presents a new and systematic review about multi-state system reliability. A timely review is an effective work related to improving the development of MSS theory. The review about the latest studies and advances about multi-state system reliability evaluation, multi-state systems optimization and multi-state systems maintenance is summarized in this paper

The safety case and the lessons learned for the reliability and maintainability case

This paper examine the safety case and the lessons learned for the reliability and maintainability case

Reliability-Oriented Design of Vehicle Electric Propulsion System Based on the Multilevel Hierarchical Reliability Model

This chapter describes a methodology of evaluation of the various sustainability indicators, such as reliability, availability, fault tolerance, and reliability-associated cost of the electric propulsion systems, based on a multilevel hierarchical reliability model (MLHRM) of the life cycles of electric vehicles. Considering that the vehicle propulsion systems are safety-critical systems, to each of their components, the strict requirements on reliability indices are imposed. The practical application of the proposed technique for reliability-oriented development of the icebreaking ship’s electric propulsion system and the results of computation are presented. The opportunities of improvement of reliability and fault tolerance are investigated. The results of the study, allowing creating highly reliable electric vehicles and choosing the most appropriate traction electric drive design, are discussed

Multistate analysis and design : case studies in aerospace design and long endurance systems

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, September 2011.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections."September 2011." Cataloged from student submitted PDF version of thesis.Includes bibliographical references (p. 221-230).This research contributes to the field of aerospace engineering by proposing and demonstrating an integrated process for the early-stage, multistate design of aerospace systems. The process takes into early consideration the many partially degraded states that real-world systems experience throughout their operation. Despite advancing efforts aimed at maintaining operation in a state of optimum performance, most systems spend very substantial amounts of time operating in degraded or off-nominal states (e.g. Hubble space telescope, Mars Spirit rover, or aircraft flying under minimum-equipment-list restrictions). There exist relatively few methods and tools to address this at the beginning of the design process. At one end of the spectrum is design optimization, but this typically concentrates on the system in its nominal state of operation, only infrequently considering failure states through piecemeal application of constraints. There is reliability analysis, which focuses on component failure rates and the benefits of redundancy but does not consider how well or poorly the system performs with partial failures. Finally, there is controls theory, where control laws are optimized but the plant is typically assumed to be given a priori. The methodology described within this thesis coordinates elements from each of these three areas into an effective integrated framework. It allows the designer deeper insight into the complex problem of designing cost effective systems that must operate for long durations with little or expensive opportunity for repair or intervention. Specific contributions include: 1) the above methodology, which evaluates responses in system expected performance and availability to changes in static design variables (geometry) and component failure rates, accounting for control design variables (gains) where appropriate, 2) the demonstration of the cost and benefits associated with a multistate design approach as compared to reliability analysis and the nominal design approach, and 3) a multilayer extension of Markov analysis, for translating single sortie vehicle level metrics into measures of multistate campaign performance. The process is demonstrated through three application case studies. The first of these establishes the feasibility of the approach through the multistate analysis of performance for an existing twin-engine aircraft. This analysis was enabled through the development of a multidisciplinary simulation based design model for evaluation of multistate aircraft performance. A medium-altitude long endurance unmanned aerial vehicle is designed in the second case study, first from a single-sortie, ultra long endurance perspective and then from a multiple sortie, mission campaign perspective. Finally, the third case study demonstrates applicability of the approach to a lower level subsystem, that of the lubrication system for a geared turbofan engine. Several major findings result from these case studies, including that: 1) multistate performance output spaces have distinctly unique shapes and boundaries, depending on whether formed through variation of component failure rates, static design variables (geometry), or a multistate combination of both, 2) a region of multistate performance results from the combined variation of failure rates and static design variables that is unachievable through the independent variation of either one, 3) small changes in static design variables may be used to significantly improve system availability, and 4) the general multistate design problem is one of competing objectives between system availability, expected performance, nominal performance, and cost.by Jeremy S. Agte.Ph.D

Integration of maintenance optimization in process design and operation under uncertainty.

Imperial Users onl

Study on New Sampling Plans and Optimal Integration with Proactive Maintenance in Production Systems

Sampling plans are statistical process control (SPC) tools used mainly in production processes. They are employed to control processes by monitoring the quality of produced products and alerting for necessary adjustments or maintenance. Sampling is used when an undesirable change (shift) in a process is unobservable and needs time to discover. Basically, the shift occurs when an assignable cause affects the process. Wrong setups, defective raw materials, degraded components are examples of assignable causes. The assignable cause causes a variable (or attribute) quality characteristic to shift from the desired state to an undesired state. The main concern of sampling is to observe a process shift quickly by signaling a true alarm, at which, maintenance is performed to restore the process to its normal operating conditions. While responsive maintenance is performed if a shift is detected, proactive maintenance such as age-replacement is integrated with the design of sampling. A sampling plan is designed economically or economically-statistically. An economical design does not assess the system performance, whereas the economic-statistical design includes constraints on system performance such as the average outgoing quality and the effective production rate. The objective of this dissertation is to study sampling plans by attributes. Two studies are conducted in this dissertation. In the first study, a sampling model is developed for attribute inspection in a multistage system with multiple assignable causes that could propagate downstream. In the second study, an integrated model of sampling and maintenance with maintenance at the time of the false alarm is proposed. Most of the sampling plans are designed based on the occurrence of one assignable cause. Therefore, a sampling plan that allows two assignable causes to occur is developed in the first study. A multistage serial system of two unreliable machines with one assignable cause that could occur on each machine is assumed where the joint occurrence of assignable causes propagates the process\u27s shift to a higher value. As a result, the system state at any time is described by one in-control and three out-of-control states where the evolution from a state to another depends on the competencies between shifts. A stochastic methodology to model all competing scenarios is developed. This methodology forms a base that could be used if the number of machines and/or states increase. In the second study, an integrated model of sampling and scheduled maintenance is proposed. In addition to the two opportunities for maintenance at the true alarm and scheduled maintenance, an additional opportunity for preventive maintenance at the time of a false alarm is suggested. Since a false alarm could occur at any sampling time, preventive maintenance is assumed to increase with time. The effectiveness of the proposed model is compared to the effectiveness of separate models of scheduled maintenance and sampling. Inspired by the conducted studies, different topics of sampling and maintenance are proposed for future research. Two topics are suggested for integrating sampling with selective maintenance. The third topic is an extension of the first study where more than two shifts can occur simultaneously

ACCIDENT ANALYSIS, RISK AND RELIABILITY MODELING OF MARINE TRANSPORTATION SYSTEMS

Ph.DDOCTOR OF PHILOSOPH

Propriedades termodinâmicas e de transporte de metano e dióxido de carbono : um estudo por simulação molecular

Orientador: Charlles Rubber de Almeida AbreuTese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia QuímicaResumo: Os combustíveis fósseis representam a maior fatia das fontes energéticas utilizadas mundialmente e o crescimento da demanda desses combustíveis impulsiona a necessidade de atividades exploratórias e o crescimento da produção de óleo e gás. Nesse cenário, as descobertas de grandes acumulações de hidrocarbonetos na área do pré-sal, localizada fora da costa sudeste brasileira, abriram novas fronteiras com o potencial de colocar o país entre os maiores detentores de reservas de óleo e gás do mundo. Entretanto, a produção nessa área requer a superação de desafios tecnológicos, como as grandes profundidades, a distância da costa e a extensa presença de dióxido de carbono (CO2) como contaminante. De maneira a reduzir a emissão atmosférica de CO2, a produção de óleo e gás na área do pré-sal requer a separação e injeção de altos volumes desse contaminante de volta ao reservatório, promovendo também a recuperação melhorada de petróleo. Dessa forma, o conhecimento completo das propriedades termofísicas dos fluidos, frequentemente em condições extremas de temperatura e pressão, é fundamental para assegurar operações eficientes e seguras. Este trabalho apresenta uma investigação abrangente das propriedades termofísicas de dióxido de carbono, metano, e suas misturas binárias através do uso de simulações moleculares. Modelagem molecular teórica, juntamente com cálculos estatísticos eficientes, foram empregados na estimativa de propriedades termodinâmicas, de transporte, e de coexistência de fases, em amplas faixas de temperatura, pressão e composição. Estimativas de propriedades através de simulações moleculares foram atingidas com alta exatidão, mesmo considerando faixas estendidas de condições onde dados experimentais não estão disponíveis. As estimativas obtidas com simulações moleculares foram utilizadas ainda na validação de extrapolações de modelos empíricos, avaliados fora de suas faixas normais de validade. Em geral, simulação molecular pode ser considerada uma ferramenta confiável e exata para a solução de problemas da indústria. A aplicação de simulação molecular como uma ferramenta de engenharia de uso diário é limitada pelos recursos computacionais disponíveis atualmente, sendo esperados o aumento na disponibilidade e a queda do preço desses recursos com o tempoAbstract: As fossil fuels continue to represent by far the largest share of energy sources used globally, their increasing demand drives the need for exploration activities and the growing action of oil and gas production. In this scenario, the discoveries of large hydrocarbon accumulations in the pre-salt area, located offshore from southern Brazil, have opened a new frontier with the potential to put Brazil among the countries with the largest reserves of oil and gas in the world. However, production in this area requires new technological developments to outpace challenges such as the large water depths, the great distances from the coast and the extensive presence of carbon dioxide (CO2) as a contaminant. In order to reduce the atmospheric emissions of CO2, the oil and gas production in the pre-salt area requires the separation and injection of high volumes of this contaminant back to the reservoir, for both enhanced oil recovery and mitigation purposes. Therefore, thorough knowledge of the thermophysical properties of fluids, often at extreme conditions of temperature and pressure, is key to ensure efficient and safe operations. This work presents a comprehensive investigation of thermophysical properties of carbon dioxide, methane, and their binary mixtures through the use of molecular simulations. Theoretical molecular modeling, along with statistical-efficient calculation methods were employed to estimate thermodynamic, transport, and phase coexistence properties, in a vast range of temperature, pressure and composition conditions. Highly accurate property predictions were attained with molecular simulations, and estimates were extended to ranges were no reference data is currently available. The physically meaningful estimates from molecular simulations were also utilized to validate extrapolations of empirical models, outside their normal range of validity. Molecular simulation has proven to be a reliable and accurate tool to help resolve common problems in the industry. Its application as a daily engineering tool is limited by the computational resources currently available, which are expected to only increase and become cheaper with timeDoutoradoEngenharia QuímicaDoutor em Engenharia Químic

An Integrated Framework to Evaluate Off-Nominal Requirements and Reliability of Novel Aircraft Architectures in Early Design

One of the barriers to the development of novel aircraft architectures and technologies is the uncertainty related to their reliability and the safety risk they pose. In the conceptual and preliminary design stages, traditional system safety techniques rely on heuristics, experience, and historical data to assess these requirements. The limitations and off-nominal operational considerations generally postulated during traditional safety analysis may not be complete or correct for new concepts. Additionally, dearth of available reliability data results in poor treatments of epistemic and aleatory uncertainty for novel aircraft architectures. Two performance-based methods are demonstrated to solve the problem of improving the identification and characterization of safety related off-nominal requirements in early design. The problem of allocating requirements to the unit level is solved using a network-based bottom-up analysis algorithm combined with the Critical Flow Method. A Bayesian probability approach is utilized to better deal with epistemic and aleatory uncertainty while assessing unit level failure rates. When combined with a Bayesian decision theoretic approach, it provides a mathematically backed framework for compliance finding under uncertainty. To estimate multi-state reliability of complex systems, this dissertation contributes a modified Monte-Carlo algorithm that uses the Bayesian failure rate posteriors previously generated. Finally, multi-state importance measures are introduced to determine the sensitivity of different hazard severity to unit reliability. The developed tools, techniques, and methods of this dissertation are combined into an integrated framework with the capability to perform trade-studies informed by safety and reliability considerations for novel aircraft architectures in early preliminary design. A test distributed electric propulsion (T-DEP) aircraft inspired by the X-57 is utilized as a test problem to demonstrate this frameworkPh.D

Comparison of surrogate measures for the reliability and redundancy of water distribution systems

An investigation into the effectiveness of surrogate measures for the hydraulic reliability and/or redundancy of water distribution systems is presented. The measures considered are statistical flow entropy, resilience index, network resilience and surplus power factor. Looped network designs that are maximally noncommittal to the surrogate reliability measures were considered. In other words, the networks were designed by multi-objective evolutionary optimization free of any influence from the surrogate measures. The designs were then assessed using each surrogate measure and two accurate but computationally intensive measures namely hydraulic reliability and pipe-failure tolerance. The results indicate that by utilising statistical flow entropy, the reliability of the network can be reasonably approximated, with substantial savings in computational effort. The results for the other surrogate measures were often inconsistent. Two networks in the literature were considered. One example involved a range of alternative network topologies. In the other example, based on whole-life cost accounting, alternative design and upgrading schemes for a 20-year design horizon were considered. Pressure-dependent hydraulic modelling was used to simulate pipe failures for the reliability calculations