Novel models and algorithms for systems reliability modeling and optimization

Recent growth in the scale and complexity of products and technologies in the defense and other industries is challenging product development, realization, and sustainment costs. Uncontrolled costs and routine budget overruns are causing all parties involved to seek lean product development processes and treatment of reliability, availability, and maintainability of the system as a true design parameter . To this effect, accurate estimation and management of the system reliability of a design during the earliest stages of new product development is not only critical for managing product development and manufacturing costs but also to control life cycle costs (LCC). In this regard, the overall objective of this research study is to develop an integrated framework for design for reliability (DFR) during upfront product development by treating reliability as a design parameter. The aim here is to develop the theory, methods, and tools necessary for: 1) accurate assessment of system reliability and availability and 2) optimization of the design to meet system reliability targets. In modeling the system reliability and availability, we aim to address the limitations of existing methods, in particular the Markov chains method and the Dynamic Bayesian Network approach, by incorporating a Continuous Time Bayesian Network framework for more effective modeling of sub-system/component interactions, dependencies, and various repair policies. We also propose a multi-object optimization scheme to aid the designer in obtaining optimal design(s) with respect to system reliability/availability targets and other system design requirements. In particular, the optimization scheme would entail optimal selection of sub-system and component alternatives. The theory, methods, and tools to be developed will be extensively tested and validated using simulation test-bed data and actual case studies from our industry partners

On Dependable Wireless Communications through Multi-Connectivity

The realization of wireless ultra-reliable low-latency communications (URLLC) is one of the key challenges of the fifth generation (5G) of mobile communications systems and beyond. Ensuring ultra-high reliability together with a latency in the (sub-)millisecond range is expected to enable self-driving cars, wireless factory automation, and the Tactile Internet. In wireless communications, reliability is usually only considered as percentage of successful packet delivery, aiming for 1 − 10⁻⁵ up to 1 − 10⁻⁹ in URLLC

Increasing the reliability and the profit in a redundancy allocation problem

This paper proposes a new mathematical model for multi-objective redundancy allocation problem (RAP) without component mixing in each subsystem when the redundancy strategy can be chosen for individual subsystems. Majority of the mathematical model for the multi-objective redundancy allocation problems (MORAP) assume that the redundancy strategy for each subsystem is predetermined and fixed. In general, active redundancy has received more attention in the past. However, in practice both active and cold-standby redundancies may be used within a particular system design and the choice of the redundancy strategy becomes an additional decision variable. The proposed model for MORAP simultaneously maximizes the reliability and the net profit of the system. And finally, to clarify the proposed mathematical model a numerical example will be solved. Keywords: Redundancy Allocation Problem, Serial-Parallel System, Redundancy Strategies, MORAP

Genetic Algorithm and Simulated Annealing for Redundancy Allocation Problem with Cold-standby Strategy

This paper presents a new mathematical model for a redundancyallocation problem (RAP) withcold-standby redundancy strategy and multiple component choices.The applications of the proposed model arecommon in electrical power, transformation,telecommunication systems,etc.Manystudies have concentrated onone type of time-to-failure, butin thispaper, two components of time-to-failures which follow hypo-exponential and exponential distributionare investigated. The goal of the RAP is to select available components and redundancy level for each subsystem for maximizing system reliability under cost and weight constraints.Sincethe proposed model belongs to NP-hard class, we proposed two metaheuristic algorithms; namely, simulated annealing and genetic algorithm to solve it. In addition, a numerical example is presented to demonstrate the application of the proposed solution methodology.</p

Enhancement in Reliability for Multi-core system consisting of One Instruction Cores

Rapid CMOS device size reduction resulted in billions of transistors on a chip have led to integration of many cores leading to many challenges such as increased power dissipation, thermal dissipation, occurrence of transient faults and permanent faults. The mitigation of transient faults and permanent faults at the core level has become an important design parameter in a multi-core scenario. Core level techniques is a redundancy-based fault mitigation technique that improves the lifetime reliability of multi-core systems. In an asymmetric multi-core system, the smaller cores provide fault tolerance to larger cores is a core level fault mitigation technique that has gained momentum and focus from many researchers. The paper presents an economical, asymmetric multi-core system with one instruction cores (MCSOIC). The term Hardware Cost Estimation signifies power and area estimation for MCS-OIC. In MCSOIC, OIC is a warm standby redundant core. OICs provide functional support to conventional cores for shorter periods of time. To evaluate the idea, different configurations of MCSOIC is synthesized using FPGA and ASIC. The maximum power overhead and maximum area overhead are 0.46% and 11.4% respectively. The behavior of OICs in MCS-OIC is modelled using a One-Shot System (OSS) model for reliability analysis. The model parameters namely, readiness, wakeup probability and start-up-strategy for OSS are mapped to the multi-core systems with OICs. Expressions for system reliability is derived. System reliability is estimated for special cases.Comment: 46 page

FRAMEWORK FOR RELIABILITY, MAINTAINABILITY AND AVAILABILITY ANALYSIS OF GAS PROCESSING SYSTEM DURING OPERATION PHASE

In facing many operation challenges such as increased expectation in bottom line performances and escalating overhead costs, petrochemical plants nowadays need to continually strive for higher reliability and availability by means of effective improvement tools. Reliability, maintainability and availability (RAM) analysis has been recognised as one of the strategic tools to improve plant's reliability at operation phase. Nevertheless, the application of RAM among industrial practitioners is still limited generally due to the impracticality and complexity of existing approaches. Hence, it is important to enhance the approaches so that they can be practically applied by companies to assist them in achieving their operational goals. The objectives of this research are to develop frameworks for applying reliability, maintainability and availability analysis of gas processing system at operation phase to improve system operational and maintenance performances. In addition, the study focuses on ways to apply existing statistical approach and incorporate inputs from field experts for prediction of reliability related measures. Furthermore, it explores and highlights major issues involved in implementing RAM analysis in oil and gas industry and offers viable solutions. In this study, systematic analysis on each RAM components are proposed and their roles as strategic improvement and decision making tools are discussed and demonstrated using case studies of two plant systems. In reliability and maintainability (R&M) analysis, two main steps; exploratory and inferential are proposed. Tools such as Pareto, trend plot and hazard functions; Kaplan Meier (KM) and proportional hazard model (PHM), are used in exploratory phase to identify critical elements to system's R&M performances. In inferential analysis, a systematic methodology is presented to assess R&M related measures

Evolutionary Algorithms in Engineering Design Optimization

Evolutionary algorithms (EAs) are population-based global optimizers, which, due to their characteristics, have allowed us to solve, in a straightforward way, many real world optimization problems in the last three decades, particularly in engineering fields. Their main advantages are the following: they do not require any requisite to the objective/fitness evaluation function (continuity, derivability, convexity, etc.); they are not limited by the appearance of discrete and/or mixed variables or by the requirement of uncertainty quantification in the search. Moreover, they can deal with more than one objective function simultaneously through the use of evolutionary multi-objective optimization algorithms. This set of advantages, and the continuously increased computing capability of modern computers, has enhanced their application in research and industry. From the application point of view, in this Special Issue, all engineering fields are welcomed, such as aerospace and aeronautical, biomedical, civil, chemical and materials science, electronic and telecommunications, energy and electrical, manufacturing, logistics and transportation, mechanical, naval architecture, reliability, robotics, structural, etc. Within the EA field, the integration of innovative and improvement aspects in the algorithms for solving real world engineering design problems, in the abovementioned application fields, are welcomed and encouraged, such as the following: parallel EAs, surrogate modelling, hybridization with other optimization techniques, multi-objective and many-objective optimization, etc

Contribution to reliable control of dynamic systems

Aplicat embargament des de la data de defensa fins al maig 2020This thesis presents sorne contributions to the field of Health-Aware Control (HAC) of dynamic systems. In the first part of this thesis, a review of the concepts and methodologies related to reliability versus degradation and fault tolerant control versus health-aware control is presented. Firstly, in an attempt to unify concepts, an overview of HAC, degradation, and reliability modeling including some of the most relevant theoretical and applied contributions is given. Moreover, reliability modeling is formalized and exemplified using the structure function, Bayesian networks (BNs) and Dynamic Bayesian networks (DBNs) as modeling tools in reliability analysis. In addition, some Reliability lmportance Measures (RIMs) are presented. In particular, this thesis develops BNs models for overall system reliability analysis through the use of Bayesian inference techniques. Bayesian networks are powerful tools in system reliability assessment due to their flexibility in modeling the reliability structure of complex systems. For the HAC scheme implementation, this thesis presents and discusses the integration of actuators health information by means of RIMs and degradation in Model Predictive Control (MPC) and Linear Quadratic Regulator algorithms. In the proposed strategies, the cost function parameters are tuned using RIMs. The methodology is able to avoid the occurrence of catastrophic and incipient faults by monitoring the overall system reliability. The proposed HAC strategies are applied to a Drinking Water Network (DWN) and a multirotor UAV system. Moreover, a third approach, which uses MPC and restricts the degradation of the system components is applied to a twin rotor system. Finally, this thesis presents and discusses two reliability interpretations. These interpretations, namely instantaneous and expected, differ in the manner how reliability is evaluated and how its evolution along time is considered. This comparison is made within a HAC framework and studies the system reliability under both approaches.Aquesta tesi presenta algunes contribucions al camp del control basat en la salut dels components "Health-Aware Control" (HAC) de sistemes dinàmics. A la primera part d'aquesta tesi, es presenta una revisió dels conceptes i metodologies relacionats amb la fiabilitat versus degradació, el control tolerant a fallades versus el HAC. En primer lloc, i per unificar els conceptes, s'introdueixen els conceptes de degradació i fiabilitat, models de fiabilitat i de HAC incloent algunes de les contribucions teòriques i aplicades més rellevants. La tesi, a més, el modelatge de la fiabilitat es formalitza i exemplifica utilitzant la funció d'estructura del sistema, xarxes bayesianes (BN) i xarxes bayesianes dinamiques (DBN) com a eines de modelat i anàlisi de la fiabilitat com també presenta algunes mesures d'importància de la fiabilitat (RIMs). En particular, aquesta tesi desenvolupa models de BNs per a l'anàlisi de la fiabilitat del sistema a través de l'ús de tècniques d'inferència bayesiana. Les xarxes bayesianes són eines poderoses en l'avaluació de la fiabilitat del sistema gràcies a la seva flexibilitat en el modelat de la fiabilitat de sistemes complexos. Per a la implementació de l?esquema de HAC, aquesta tesi presenta i discuteix la integració de la informació sobre la salut i degradació dels actuadors mitjançant les RIMs en algoritmes de control predictiu basat en models (MPC) i control lineal quadràtic (LQR). En les estratègies proposades, els paràmetres de la funció de cost s'ajusten utilitzant els RIMs. Aquestes tècniques de control fiable permetran millorar la disponibilitat i la seguretat dels sistemes evitant l'aparició de fallades a través de la incorporació d'aquesta informació de la salut dels components en l'algoritme de control. Les estratègies de HAC proposades s'apliquen a una xarxa d'aigua potable (DWN) i a un sistema UAV multirrotor. A més, un tercer enfocament fent servir la degradació dels actuadors com a restricció dins l'algoritme de control MPC s'aplica a un sistema aeri a dos graus de llibertat (TRMS). Finalment, aquesta tesi també presenta i discuteix dues interpretacions de la fiabilitat. Aquestes interpretacions, nomenades instantània i esperada, difereixen en la forma en què s'avalua la fiabilitat i com es considera la seva evolució al llarg del temps. Aquesta comparació es realitza en el marc del control HAC i estudia la fiabilitat del sistema en tots dos enfocaments.Esta tesis presenta algunas contribuciones en el campo del control basado en la salud de los componentes “Health-Aware Control” (HAC) de sistemas dinámicos. En la primera parte de esta tesis, se presenta una revisión de los conceptos y metodologíasrelacionados con la fiabilidad versus degradación, el control tolerante a fallos versus el HAC. En primer lugar, y para unificar los conceptos, se introducen los conceptos de degradación y fiabilidad, modelos de fiabilidad y de HAC incluyendo algunas de las contribuciones teóricas y aplicadas más relevantes. La tesis, demás formaliza y ejemplifica el modelado de fiabilidad utilizando la función de estructura del sistema, redes bayesianas (BN) y redes bayesianas diná-micas (DBN) como herramientas de modelado y análisis de fiabilidad como también presenta algunas medidas de importancia de la fiabilidad (RIMs). En particular, esta tesis desarrolla modelos de BNs para el análisis de la fiabilidad del sistema a través del uso de técnicas de inferencia bayesiana. Las redes bayesianas son herramientas poderosas en la evaluación de la fiabilidad del sistema gracias a su flexibilidad en el modelado de la fiabilidad de sistemas complejos. Para la implementación del esquema de HAC, esta tesis presenta y discute la integración de la información sobre la salud y degradación de los actuadores mediante las RIMs en algoritmos de control predictivo basado en modelos (MPC) y del control cuadrático lineal (LQR). En las estrategias propuestas, los parámetros de la función de coste se ajustan utilizando las RIMs. Estas técnicas de control fiable permitirán mejorar la disponibilidad y la seguridad de los sistemas evitando la aparición de fallos a través de la incorporación de la información de la salud de los componentes en el algoritmo de control. Las estrategias de HAC propuestas se aplican a una red de agua potable (DWN) y a un sistema UAV multirotor. Además, un tercer enfoque que usa la degradación de los actuadores como restricción en el algoritmo de control MPC se aplica a un sistema aéreo con dos grados de libertad (TRMS). Finalmente, esta tesis también presenta y discute dos interpretaciones de la fiabilidad. Estas interpretaciones, llamadas instantánea y esperada, difieren en la forma en que se evalúa la fiabilidad y cómo se considera su evolución a lo largo del tiempo. Esta comparación se realiza en el marco del control HAC y estudia la fiabilidad del sistema en ambos enfoques.Postprint (published version