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Modern Dynamic Reliability Analysis for Multi-state Systems: Stochastic Processes and the Lz-Transform PDF

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Springer Series in Reliability Engineering Anatoly Lisnianski Ilia Frenkel Lev Khvatskin Modern Dynamic Reliability Analysis for Multi-state Systems Stochastic Processes and the L -Transform z Springer Series in Reliability Engineering Series Editor Hoang Pham, Department of Industrial and Systems Engineering, Rutgers University, Piscataway, NJ, USA More information about this series at http://www.springer.com/series/6917 Anatoly Lisnianski Ilia Frenkel (cid:129) (cid:129) Lev Khvatskin Modern Dynamic Reliability Analysis for Multi-state Systems Stochastic Processes and the L -Transform Z 123 AnatolyLisnianski Ilia Frenkel TheReliability Department CenterforReliabilityandRiskManagement Israel Electric Corporation Ltd,Haifa, SCE-Shamoon Collegeof Engineering Israel andCenterfor Reliability andRisk Beer Sheva,Israel Management, SCE-Shamoon College of Engineering Beer Sheva,Israel LevKhvatskin CenterforReliabilityandRiskManagement andIndustrialEngineeringandManagement Department SCE-Shamoon Collegeof Engineering Beer Sheva,Israel ISSN 1614-7839 ISSN 2196-999X (electronic) SpringerSeries inReliability Engineering ISBN978-3-030-52487-6 ISBN978-3-030-52488-3 (eBook) https://doi.org/10.1007/978-3-030-52488-3 ©SpringerNatureSwitzerlandAG2021 Thisworkissubjecttocopyright.AllrightsarereservedbythePublisher,whetherthewholeorpart of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission orinformationstorageandretrieval,electronicadaptation,computersoftware,orbysimilarordissimilar methodologynowknownorhereafterdeveloped. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publicationdoesnotimply,evenintheabsenceofaspecificstatement,thatsuchnamesareexemptfrom therelevantprotectivelawsandregulationsandthereforefreeforgeneraluse. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained hereinorforanyerrorsoromissionsthatmayhavebeenmade.Thepublisherremainsneutralwithregard tojurisdictionalclaimsinpublishedmapsandinstitutionalaffiliations. ThisSpringerimprintispublishedbytheregisteredcompanySpringerNatureSwitzerlandAG Theregisteredcompanyaddressis:Gewerbestrasse11,6330Cham,Switzerland To my son Roma and his wife Rima my daughter Masha and her husband Igal my beautiful granddaughters Yael, Liora, Noa, Gaya and Maya —Anatoly Lisnianski To my grandchildren Idan, Sofia, Anastasia, Thomas and Liam —Ilia Frenkel To my granddaughter Tomer —Lev Khvatskin Preface This book is considered as a dynamic analysis of multi-state system (MSS) with focus on reliability, availability and performability analysis of aging MSS, com- ponentsimportancechanging(variety)duringthetime,initialconditionsimpacton these issues, etc. Using traditional methods for solving such problems for real-world multi-state systemsleads toexplosion ofnumberofstatesthatshouldbeanalysed. Inorderto avoidthisproblem,aspecialtypeoftransformforMarkovstochasticprocessthatis called L -transform was suggested. By using this transform, the Universal Z Generating Function technique, which is widely used for steady-state MSS relia- bility analysis, may be extended to dynamic reliability analysis and applied to randomprocesses.RecentlytherearemanysuccessiveapplicationsofL -transform Z method to dynamic analysis of different real-world multi-state systems. L -trans- Z form was applied to determining age replacement policy in MSS, to provide reli- ability, availability and performability analysis for different specific MSSs such as power systems, refrigerating systems, air conditioning systems, different technical systems in aviation and maritime engineering. The aim of this book is to provide a comprehensive, up-to-date presentation of anMSSdynamicanalysisbyusingL -transformandinverseL -transformbasedon Z Z currentachievementsin this field. For these purposes thebook is logicallydivided into two parts. In the first part (Chaps. 1–3) theoretical issues are presented with correspondingmethodologicalexamples.Thesecondpart(Chaps.4–8)presentsthe method of implementation to solving practical problems. The authors anticipate that the book will be attractive for researchers and practical engineers in addressing issues related to reliability, availability and per- formability analysis. In addition, it will be a helpful textbook for graduate courses inappliedmathematics,industrial,electrical,mechanicalandcomputerengineering. It should be noticed that it is impossible to describe all the achievements in the field in a single book. Naturally some interesting results remained outside of the book’sscope.Insuchcasestheauthorsprovidethereaderswiththecorresponding references. vii viii Preface The book is organized as follows. Chapter 1 presents the generic MSS model as a set of models of stochastic pro- cesses for every MSS’s element and the system structure function. There were described indices for MSS reliability, availability and performability assessment. In Chap. 2 in order to make the book self-contained, we have presented to the reader a basic knowledge about Markov processes. It was considered a method- ology of Markov models building for reliability, availability and performability assessment. Chapter 3 presents the approach for computation reliability, availability and per- formabilityofMSSindynamicmodes.Forthispurpose,therewereintroducedand mathematically defined L -transform and inverse L -transform for discrete-state Z Z continuous-time Markov process. The technique of their application for computa- tion of MSS reliability, availability and performability indices was described in detail. Corresponding methodological examples were presented. Chapter4presentstheapplicationsofL -transformmethodtoashort-termanalysis Z of power systems. Here availability and performability assessment for coal-fired power units as well as for combine cycle units were considered. By using inverse L -transform for coal-fired power plant a short-term risk function and reliability Z evaluationandestimatingofmeantimetofailurewereperformed.Itisshownhow these parameters may be used in power system dispatch for making important operating decisions in real time. In Chap. 5, the L -transform method is applied for the analysis of a redundant Z multi-stateairconditioningsystemforchemicallaboratorythatmustfunctionunder different cases of hood functioning. Its availability is investigated when in the system there are some aging elements. In Chap. 6 a reserved cold-water supply system for a factory, specialized in pro- ducingrawmaterialsfortheplasticsindustryisconsidered.Watercoolingsystems often have aging components and so, one should consider in general a non-homogeneous Markov model because some transition rates (intensities) are being time-dependent. Such a model is complex—even in simple cases it has hundredsofstates.Therefore,itisratherdifficulttobuildthemodelandtosolvethe corresponding system of differential equations by using straightforward Markov method.So,inordertomakeadynamicMSSreliabilityanalysisL -transformwill Z be used. InChap.7themethodforanalysisofimpactofchangingdifferentfailuresorrepair rates in different elements in aging MSS is presented. There were introduced sen- sitivitymeasuresthatareusefulforinvestigationofanagingMSSandpresentedthe methodfortheirevaluation,basedonusingL -transform.Themethodwasapplied Z to sensitivity analysis of real water cooling system. As sensitivity measures there were proposed derivations of MSS life time with respect to restriction of avail- ability, mean output performance and accumulated performance deficiency. Preface ix In Chap. 8 the method for computation of the Birnbaum B-availability importance measure for components in an aging MSS under minimal repair was considered. ThemethodisbasedontheL -transform.ItwasshownthatdynamicB-availability Z importance assessment for aging MSS is especially important, because the relative importance of MSS’s components is changing over the time and strongly depends on the system demand. We would like to express our sincere gratitude and appreciation to our col- leagues from The Israel Electric Corporation, Dr. G. Levitin, Dr. D. Elmakias, Dr.H.BenHaimandDr.D.LaredoandourcolleaguesandstudentsfromShamoon College of Engineering, Israel for providing a supportive and intellectually stim- ulating environment. We also are very thankful to Prof. Yi Ding from Zhejiang University, China for his collaboration and very interesting discussions. We are especially thankful to our teachers and friends Prof. Ilya Gertsbakh and Prof. Igor Ushakov that, unfortunately, recently have left us. Their fruitful ideas have a great impact on our work. We hope that their ideas will be very helpful for reliability researchers and engineers for a long time in the future. Finally,itisindeedourpleasuretoworkwitheditorialstafffromSpringer,who has assisted in the book publication. Beer Sheva, Israel Anatoly Lisnianski May 2020 Ilia Frenkel Lev Khvatskin Contents 1 Generic Model of Multi-state System. Reliability, Availability and Performability in Dynamic Modes . . . . . . . . . . . . . . . . . . . . . . . 1 1.1 Generic Multi-state System Model. . . . . . . . . . . . . . . . . . . . . . . . 2 1.2 Reliability, Availability and Performability of Multi-state System. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 1.2.1 Reliability Measures of Multi-state Systems . . . . . . . . . . . 9 1.2.2 Availability Measures of Multi-state Systems . . . . . . . . . . 10 1.2.3 Performability Measures of Multi-state Systems. . . . . . . . . 12 1.3 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 2 Stochastic Processes Methods for MSS Reliability, Availability and Performability Assessment. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 2.1 General Concepts of Stochastic Processes Theory. . . . . . . . . . . . . 17 2.2 Markov Models: Discrete-Time Markov Chains . . . . . . . . . . . . . . 21 2.2.1 Basic Definitions and Properties . . . . . . . . . . . . . . . . . . . . 21 2.2.2 Computation of n-Step Transition Probabilities and State Probabilities . . . . . . . . . . . . . . . . . . . . . . . . . . . 23 2.3 Markov Models: Continuous-Time Markov Chains. . . . . . . . . . . . 27 2.3.1 Basic Definitions and Properties . . . . . . . . . . . . . . . . . . . . 27 2.3.2 Markov Models for Evaluating Reliability of Multi-state Elements . . . . . . . . . . . . . . . . . . . . . . . . . . 33 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50 3 LZ-Transform and Inverse LZ-Transform of a Discrete-State Continuous-Time Markov Process . . . . . . . . . . . . . . . . . . . . . . . . . . 53 3.1 L -Transform . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54 Z 3.1.1 L -Transform Definition. . . . . . . . . . . . . . . . . . . . . . . . . . 56 Z 3.1.2 Existence and Uniqueness . . . . . . . . . . . . . . . . . . . . . . . . 57 xi

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