Optimization of systems reliability by metaheuristic approach

The application of metaheuristic approaches in addressing the reliability of systems through optimization is of greater interest to researchers and designers in recent years. Reliability optimization has become an essential part of the design and operation of largescale manufacturing systems. This thesis addresses the optimization of system-reliability for series–parallel systems to solve redundant, continuous, and combinatorial optimization problems in reliability engineering by using metaheuristic approaches (MAs). The problem is to select the best redundancy strategy, component, and redundancy level for each subsystem to maximize the system reliability under system-level constraints. This type of problem involves the selection of components with multiple choices and redundancy levels that yield the maximum benefits, and it is subject to the cost and weight constraints at the system level. These are very common and realistic problems faced in the conceptual design of numerous engineering systems. The development of efficient solutions to these problems is becoming progressively important because mechanical systems are becoming increasingly complex, while development plans are decreasing in size and reliability requirements are rapidly changing and becoming increasingly difficult to adhere to. An optimal design solution can be obtained very frequently and more quickly by using genetic algorithm redundancy allocation problems (GARAPs). In general, redundancy allocation problems (RAPs) are difficult to solve for real cases, especially in large-scale situations. In this study, the reliability optimization of a series–parallel by using a genetic algorithm (GA) and statistical analysis is considered. The approach discussed herein can be applied to address the challenges in system reliability that includes redundant numbers of carefully chosen modules, overall cost, and overall weight. Most related studies have focused only on the single-objective optimization of RAP. Multiobjective optimization has not yet attracted much attention. This research project examines the multiobjective situation by focusing on multiobjective formulation, which is useful in maximizing system reliability while simultaneously minimizing system cost and weight to solve the RAP. The present study applies a methodology for optimizing the reliability of a series–parallel system based on multiobjective optimization and multistate reliability by using a hybrid GA and a fuzzy function. The study aims to determine the strategy for selecting the degree of redundancy for every subsystem to exploit the general system reliability depending on the overall cost and weight limitations. In addition, the outcomes of the case study for optimizing the reliability of the series–parallel system are presented, and the relationships with previously investigated phenomena are presented to determine the performance of the GA under review. Furthermore, this study established a new metaheuristic-based technique for resolving multiobjective optimization challenges, such as the common reliability redundancy allocation problem. Additionally, a new simulation process was developed to generate practical tools for designing reliable series–parallel systems. Hence, metaheuristic methods were applied for solving such difficult and complex problems. In addition, metaheuristics provide a useful compromise between the amount of computation time required and the quality of the approximated solution space. The industrial challenges include the maximization of system reliability subject to limited system cost and weight, minimization of system weight subject to limited system cost and the system reliability requirements and increasing of quality components through optimization and system reliability. Furthermore, a real-life situation research on security control of a gas turbine in the overspeed state was explored in this study with the aim of verifying the proposed algorithm from the context of system optimization

Reliability enhanced electrical power system for nanosatellites

Dissertação (mestrado) - Universidade Federal de Santa Catarina, Centro Tecnológico, Programa de Pós-Graduação em Engenharia Elétrica, Florianópolis, 2023.A baixa confiabilidade dos subsistemas elétricos de potência (EPS) é um dos principais fatores responsáveis pelo alto número de falhas em missões de nanossatélites. Embora diversas técnicas de melhoria de confiabilidade tenham sido propostas no passado, a maior parte destes estudos não considera sua aplicabilidade, ignorando o custo, a energia e a área da placa requerida para que estas técnicas sejam implementadas. Em vista disto, o presente trabalho propõe uma arquitetura de EPS que incorpora quatro técnicas de melhoria de confiabilidade em um projeto de baixo custo e tamanho reduzido, a saber: seleção metódica de componentes de prateleira, projeto sem processador, redundância passiva parcial, e monitoramento e controle de cargas. Cada uma destas técnicas foi cuidadosamente selecionada para aprimorar a confiabilidade do EPS sem que outras áreas do projeto fossem comprometidas. Para melhor assegurar a viabilidade da arquitetura, três estratégias de projeto para redução de consumo energia foram também colocadas em prática. A mais importante delas é o uso de conversores de carga customizados, de alta eficiência e baseados em transistores de nitreto de gálio (GaN). Além disto, a arquitetura utiliza majoritariamente componentes de baixo consumo de energia e disponibiliza suporte para modos de operação de baixa dissipação, o que pode reduzir significativamente o desperdício de energia durante períodos de eclipse ou de inatividade. Toda a proposta foi fundamentada por diagramas de blocos, análises teóricas, equações de projeto e pelo esquema elétrico da placa de circuito impresso (PCB). A eficiência dos conversores de ponto de carga, o mecanismo de ativação das redundâncias passivas e todas as outras principais funcionalidades do EPS foram verificadas e validadas através de simulações de circuito SPICE. Ademais, um sistema de três métricas para avaliar e comparar a confiabilidade de arquiteturas de EPS também foi proposto. Baseado neste modelo de avaliação, foi possível comparar a arquitetura aqui apresentada, com aquela utilizada na versão anterior da mesma plataforma e com a NanoPower P31U, que é projetada pela GomSpace. Resultados comparativos confirmaram a efetividade das técnicas que foram incorporadas ao EPS, indicando que ele apresenta a arquitetura mais confiável dentre as três que foram consideradas para esta análise.Abstract: The low reliability of the Electrical Power Systems (EPS) is one of the major factors responsible for the high number of nanosatellite mission failures. Although several reliability-enhancing techniques have been proposed in the past, most studies do not take into account their applicability, overlooking the cost, power, and board area required for them to be implemented. In light of this, the present work proposes an EPS architecture that incorporates four reliability-enhancing techniques into a low-cost, small-footprint design. Namely, methodical COTS selection, processor-less design, partial standby redundancy, and load monitoring and control. Each technique was thoughtfully chosen to enhance the EPS reliability without compromising other design areas. To further ensure the viability of the architecture, three power reduction design strategies were also put in place. The most important of which was the use of customized high-efficiency GaN-based point-of-load (PoL) converters. In addition, the architecture features mostly low-power components and provides support for low-power modes of operation, which can greatly reduce the power wasted during an eclipse or an idle period. The entire proposal was backed up by block diagrams, theoretical analysis, design equations, and a printed circuit board (PCB) schematic design. The efficiency of the PoL converters, the standby redundancy activation mechanism, and all other main EPS functionalities, were verified and validated through SPICE circuit simulations. Furthermore, this work also proposes a three-metric system for evaluating and comparing the reliability of different EPS architectures. Based on this evaluation method, it was possible to compare the EPS architecture presented herein with its previous version and with the NanoPower P31U, which is designed by GomSpace. Comparison results confirmed the effectiveness of the techniques that were incorporated into this EPS, indicating that it exhibits the highest architecture reliability among the three candidates that were considered for this analysis

Condition Based Maintenance Optimization for Multi-Component Systems Based on Neural Network Health Prediction

Condition-based maintenance (CBM) is an effective maintenance approach to prioritize and optimize maintenance resources based on condition monitoring information. A well established and effective CBM program can eliminate unnecessary maintenance actions, lower maintenance costs, reduce system downtime and minimize unexpected catastrophic failures. Most existing work reported in the literature only focuses on determining the optimal CBM policy for single units. Replacement and other maintenance decisions are made independently for each component, based on the component’s age, condition monitoring data and the CBM policy. In this thesis, a CBM optimization method is proposed for multi-component systems, where economic dependency exists among the components subject to condition monitoring. The proposed multi-component systems CBM policy is based on a method using artificial neural network (ANN) for remaining useful life (RUL) prediction which is proposed by Tian et al. (2009). Deterioration of a multi-component system is represented by a conditional failure probability value, which is calculated based on the predicted failure time distributions of components. The proposed CBM policy is defined by a two-level failure probability threshold. A simulation method is developed to obtain the optimal threshold values in order to minimize the long-term maintenance cost. We conduct a case study using real-world vibration monitoring data to validate the proposed CBM approach. These data are collected from bearings on a group of Gould pumps at a Canadian Kraft pulp mill company and help to demonstrate the effectiveness of the proposed CBM approach for multi-component systems. The proposed CBM approach is also demonstrated using simulated degradation data for multi-component systems. The proposed maintenance policy can fulfill the requirements of a real plant environment where multiple components are under condition monitoring. By using the proposed CBM policy, maintenance managers can easily and quickly adjust the maintenance schedule according to the working condition of the system

Availability estimation and management for complex processing systems

“Availability” is the terminology used in asset intensive industries such as petrochemical and hydrocarbons processing to describe the readiness of equipment, systems or plants to perform their designed functions. It is a measure to suggest a facility’s capability of meeting targeted production in a safe working environment. Availability is also vital as it encompasses reliability and maintainability, allowing engineers to manage and operate facilities by focusing on one performance indicator. These benefits make availability a very demanding and highly desired area of interest and research for both industry and academia. In this dissertation, new models, approaches and algorithms have been explored to estimate and manage the availability of complex hydrocarbon processing systems. The risk of equipment failure and its effect on availability is vital in the hydrocarbon industry, and is also explored in this research. The importance of availability encouraged companies to invest in this domain by putting efforts and resources to develop novel techniques for system availability enhancement. Most of the work in this area is focused on individual equipment compared to facility or system level availability assessment and management. This research is focused on developing an new systematic methods to estimate system availability. The main focus areas in this research are to address availability estimation and management through physical asset management, risk-based availability estimation strategies, availability and safety using a failure assessment framework, and availability enhancement using early equipment fault detection and maintenance scheduling optimization

State-of-the-Art of the Flywheel/Li-ion Battery Hybrid Storage System for Stationary Applications

This thesis presents the State-of-the-Art of a flywheel/Li-ion battery Hybrid Energy Storage System for stationary applications. As Renewable Energy Sources increase in the grid so do the stability problems associated with their intermittency. Here the importance of Energy Storage Systems that aim to provide many grid services. The complementary features of the two devices in terms of power, energy and discharge time candidate this hybrid system as an optimal solution to support future grids

Contributions au développement de politiques de remplacement préventif pour des sytèmes multi-composants

Dans cette thèse, nous proposons de développer des politiques de remplacement préventif pour des systèmes multi-composants. Ces systèmes sont composés de plusieurs composants selon une configuration bien déterminée et dont l’état se dégrade d’une manière aléatoire. Les politiques de remplacement définissent les actions à entreprendre en fonction de l'état du système ou de ses composants et ont pour objectif de retarder l'apparition des pannes et de prolonger la durée de vie du système. Sur le plan théorique, la généralisation des modèles de remplacement des systèmes mono-composants à des systèmes multi-composants n'est pas évidente. La difficulté réside essentiellement dans l’existence d’interaction ou de dépendance entre les différents composants du système. Nous nous sommes concentrés dans cette thèse sur les dépendances stochastique et économique entre les composants. Pour la dépendance stochastique, la propagation de la panne a été modélisée par l’effet domino pour un système parallèle à deux composants. Nous avons proposé deux politiques de remplacement de type Age. Dans la première politique, nous avons supposé que la structure des coûts est constante alors que dans la deuxième politique cette hypothèse a été modifiée en prenant une structure de coûts variable. Nous avons aussi proposé dans le cadre de la dépendance stochastique un modèle de remplacement bi-objectif qui optimise à la fois le coût espéré du remplacement et la disponibilité du système. Pour la dépendance économique, nous avons proposé une politique de remplacement basée sur le comptage des pannes pour un système parallèle et nous l’avons intégrée dans un modèle d’allocation de la redondance d’un système série-parallèle. Le modèle mathématique a été résolu par une approche heuristique basée sur l’algorithme du recuit simulé.The aim of this thesis is to develop preventive replacement policies for multi-component systems. Systems are composed of several components connected under a known configuration and subject to random failures. Each replacement policy defines the actions to be taken according to the state of the system or its components and it is intended to delay the occurrence of failures and extend the lifetime of the system. From the theoretical point of view, the extension of replacement models from single-component systems to multi-component systems is not obvious. The difficulty is due primarily to the interaction or dependence between the different components of the system. In this thesis the focus has been put on the stochastic and economic dependencies between components. For stochastic dependence the propagation of the failure is modeled by the domino effect for a two-component parallel system, and two age replacement policies are investigated. In the first policy, we assumed that the cost structure is constant whereas in the second policy a variable cost structure is assumed. We proposed also a bi-objective replacement model that optimizes both expected replacement cost rate and system availability. For economic dependence, we proposed a failure counting replacement policy for a parallel system and we integrated it in a redundancy allocation model for a serie-parallel system. The mathematical model has been built taking account of this policy and Simulated Annealing algorithm has been used as resolution approach

On Information-centric Resiliency and System-level Security in Constrained, Wireless Communication

The Internet of Things (IoT) interconnects many heterogeneous embedded devices either locally between each other, or globally with the Internet. These things are resource-constrained, e.g., powered by battery, and typically communicate via low-power and lossy wireless links. Communication needs to be secured and relies on crypto-operations that are often resource-intensive and in conflict with the device constraints. These challenging operational conditions on the cheapest hardware possible, the unreliable wireless transmission, and the need for protection against common threats of the inter-network, impose severe challenges to IoT networks. In this thesis, we advance the current state of the art in two dimensions. Part I assesses Information-centric networking (ICN) for the IoT, a network paradigm that promises enhanced reliability for data retrieval in constrained edge networks. ICN lacks a lower layer definition, which, however, is the key to enable device sleep cycles and exclusive wireless media access. This part of the thesis designs and evaluates an effective media access strategy for ICN to reduce the energy consumption and wireless interference on constrained IoT nodes. Part II examines the performance of hardware and software crypto-operations, executed on off-the-shelf IoT platforms. A novel system design enables the accessibility and auto-configuration of crypto-hardware through an operating system. One main focus is the generation of random numbers in the IoT. This part of the thesis further designs and evaluates Physical Unclonable Functions (PUFs) to provide novel randomness sources that generate highly unpredictable secrets, on low-cost devices that lack hardware-based security features. This thesis takes a practical view on the constrained IoT and is accompanied by real-world implementations and measurements. We contribute open source software, automation tools, a simulator, and reproducible measurement results from real IoT deployments using off-the-shelf hardware. The large-scale experiments in an open access testbed provide a direct starting point for future research

Safety and Reliability - Safe Societies in a Changing World

The contributions cover a wide range of methodologies and application areas for safety and reliability that contribute to safe societies in a changing world. These methodologies and applications include: - foundations of risk and reliability assessment and management - mathematical methods in reliability and safety - risk assessment - risk management - system reliability - uncertainty analysis - digitalization and big data - prognostics and system health management - occupational safety - accident and incident modeling - maintenance modeling and applications - simulation for safety and reliability analysis - dynamic risk and barrier management - organizational factors and safety culture - human factors and human reliability - resilience engineering - structural reliability - natural hazards - security - economic analysis in risk managemen