rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Engineering reliability and risk assessment
  name:
    name part: Garg, Harish
    role:
      role term: editor.
  name:
    name part: Ram, Mangey
    role:
      role term: editor.
  name:
    name part: ScienceDirect (Online service)
  type of resource: text
  genre: Electronic books.
  origin info:
    place:
      place term: ne
    date issued: 2022
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: remote
    extent: 1 online resource : illustrations.
  abstract: Engineering Reliability and Risk Assessment explains how to improve the performance of a system using the latest risk and reliability models. Against a backdrop of increasing availability of industrial data, and ever-increasing global commercial competition, the standards for optimal efficiency with minimum hazards keep improving. Topics explained include Effective strategies for the maintenance of the mechanical components of a system, How to schedule necessary interventions throughout the product life cycle, How to understand the structure and cost of complex systems, Planning a schedule to improve the reliability and life of the system, software, system safety and risk informed asset management, and more.
  table of contents: Front Cover -- Engineering Reliability and Risk Assessment -- Advances in Reliability Science: Engineering Reliability and Risk Assessment -- Copyright -- CONTENTS -- Contributors -- 1 -- Bayesian networks for failure analysis of complex systems using different data sources -- 1. Introduction -- 2. Risk, reliability, and uncertainty -- 3. Bayesian networks (BNs) -- 4. Probabilistic failure analysis of hydropower dams -- 5. Summary and conclusions -- References -- 2 -- Failure modes and effect analysis model for the reliability and safety evaluation of a pressurized steam trap -- 1. Introduction -- 2. Hybrid failure modes and effects analysis model -- 2.1 Complex intuitionistic fuzzy set (CIFS) -- 2.2 Complex intuitionistic fuzzy Bonferroni mean (CIFBM) operator -- 2.3 Complex intuitionistic Fuzzy-VIKOR model -- 2.4 Algorithm of the hybrid failure modes and effects analysis model -- 3. Numerical illustration -- 3.1 Results and discussion -- 3.2 Observation from the model implementation -- 4. Conclusions -- References -- 3 -- Reliability and availability analysis of a standby system with activation time and varying demand -- Nomenclature -- 1. Introduction -- 2. Assumptions for proposed model -- 3. Proposed system (model) -- 4. Description of model -- 4.1 Mean sojourn times and transition probabilities -- 4.2 Mean time to system failure (MTSF) -- 4.3 Availability analysis -- 4.3.1 A single unit is operative -- 4.3.1.1 Production made by a single unit is greater than demand -- 4.3.1.2 Demand≥production by a single unit and "&lt -- " that by two units -- 4.3.1.3 Production by two units is not greater than demand -- 4.3.2 Two units are operative -- 4.3.2.1 Demand≥production by a single unit and "&lt -- " that by two units -- 4.3.2.2 Production by two units is not greater than demand -- 5. Graphical interpretations -- 6. Conclusions -- References.
  table of contents: 4 -- Fuzzy attack tree analysis of security threat assessment in an internet security system using algebraic t-norm ... -- 1. Introduction -- 2. Preliminary concepts -- 2.1 Intuitionistic fuzzy set(IFS) -- 2.2 Triangle intuitionistic fuzzy set(TIFS) -- 2.3 Algebraic t-norm(TA) and t-conorm(SA) -- 2.4 The fuzzy arithmetic operations defined on TIFS [29] -- 2.5 Failure probability evaluation for OR and AND nodes [6,30] -- 3. Proposed FATA method -- 4. An illustrative application -- 4.1 Results obtained from proposed FATA method -- 4.2 Comparative analysis and discussion -- 5. Conclusions and future scope -- References -- 5 -- A new flexible extension to a lifetime distributions, properties, inference, and applications in engineering sc ... -- Symbols -- Abbreviations -- 1. Introduction -- 2. Special model -- 2.1 The LE-inverse exponential (LE-IE) model -- 2.2 Quantile function (QF) -- 3. Reliability measures -- 3.1 Failure function -- 3.2 Reliability function -- 3.3 Hazard function -- 3.4 Mills ratio -- 3.5 Cumulative hazard rate function -- 3.6 Mean time to failure (MTTF) and mean time to repair (MTTR) -- 4. Estimation inference via simulation -- 4.1 Maximum likelihood estimation (MLE) -- 4.2 Least square estimation (LSE) -- 4.3 Simulation study -- 5. Real data applications -- 6. Conclusion -- References -- 6 -- Markov and semi-Markov models in system reliability -- 1. The reliability in systems -- 2. Failure process of systems -- 3. Markov and semi-Markov models in systems reliability -- 4. Conclusions and future research -- References -- 7 -- Emerging trends and future directions in software reliability growth modeling -- 1. Introduction -- 2. Software reliability growth models -- 2.1 Nonhomogeneous poisson process -- 2.1.1 Goel-Okumoto model (GO model) -- 2.2 SRGMs development with various associated factors.
  table of contents: 2.2.1 Perfect and imperfect debugging environment -- 2.2.2 Fault detection rate -- 2.2.3 SRGMs with environmental factors -- 3. Method of model formulation -- 4. Emerging trends -- 5. Future direction -- 6. Conclusions -- Acknowledgments -- References -- 8 -- Reliability and profit analysis of a markov model having cost-free warranty with waiting repair facility -- 1. Introduction -- 2. Background and literature review -- 2.1 Concept of warranty -- 2.1.1 Role of warranty -- 2.1.1.1 Role to consumer/customer -- 2.1.1.2 Role to manufacture -- 2.2 Warranty cost analysis -- 2.3 Shortcoming and overcoming of the literature -- 3. Description of the system -- 3.1 Assumptions -- 3.2 State specifications -- 3.3 Notations -- 4. Analysis of the system -- 4.1 Mathematical formulation of the model -- 4.2 Solution of the equations -- 4.3 Reliability of the system R(t) [29] -- 4.4 Availability of the system Av (t) -- 4.5 Busy period of the repairman BW period -- 4.6 Profit analysis of the system -- 5. Numerical results -- 5.1 Interpretations of the numerical results -- 6. Conclusion -- 7. Future research directions -- Acknowledgment -- References -- 9 -- Semi-Markov modeling applications in system availability analysis -- 1. System availability -- 2. Motivation -- 3. Availability assessment -- 4. Availability assessment methods -- 4.1 Markov method -- 4.2 Semi-Markov method -- 5. System availability modeling and analysis -- 5.1 Steady-state solution -- 5.1.1 Stage 1: EMC state probabilities -- 5.1.2 Stage 2: SMP state probabilities -- 6. Application of SMP for engineering systems -- 6.1 Illustration 1: pumping system under preventive maintenance -- 6.1.1 System availability modeling and analysis -- 6.2 Vertical milling center under run-to-failure-maintenance -- 6.2.1 System description -- 6.2.2 Illustration -- 6.3 Pumping system under condition-based maintenance.
  table of contents: 12 -- Risk assessment and management of fire-induced domino effects in chemical industrial park -- 1. Introduction -- 2. Fire synergistic effect model (FSEM) -- 2.1 Failure criterion of equipment -- 2.2 Fire synergistic effect model -- 3. Spatial-temporal evolution modeling of fire-induced domino effects based on FSEM -- 3.1 Approach overview -- 3.2 Approach procedures -- 3.3 Model validation -- 4. Risk management of fire-induced domino effects -- 4.1 Approach overview -- 4.2 Approach procedures -- 5. Combining uncertainty reasoning and deterministic modeling -- 5.1 Approach overview -- 5.2 Approach procedures -- 6. Conclusions -- References -- 13 -- Stability assessment using Bayesian network control for inverters in smart grid -- 1. Introduction -- 2. The TAN classifier and its AdaBoost algorithm -- 3. The controller structure of dynamic Bayesian network-based model predictive control -- 3.1 Model predictive control -- 3.2 Dynamic Bayesian networks -- 4. Controller of dynamic Bayesian network-based model predictive control for three-phase grid-connected inverter system -- 4.1 Modeling of three-phase grid-connected inverter system -- 4.2 Dynamic Bayesian networks for predictive modeling -- 4.3 Optimization for generating the switching signals -- 5. Experimentation and results -- 5.1 Test scenario descriptions -- 5.2 Steady-state performance study -- 5.3 Dynamic state performance study -- 5.4 The case study of new England IEEE 39-bus benchmark power system integrated with the battery energy storage system -- 5.5 The robustness analysis of using the DBN-MPC method in the grid-connected inverter based power system -- 6. Discussion and conclusion -- References -- Index -- A -- B -- C -- D -- E -- F -- G -- H -- I -- J -- K -- L -- M -- N -- O -- P -- Q -- R -- S -- T -- U -- V -- W -- Back Cover.
  note: edited by Harish Garg, Mangey Ram.
  subject:
    topic: Reliability (Engineering)
  subject:
    topic: Risk management
  subject:
    topic: Fiabilité
  subject:
    topic: Gestion du risque
  subject:
    topic: risk management
  subject:
    topic: Reliability (Engineering)
  subject:
    topic: Risk management
  classification: TA169 .E54 2022
  classification: 620.00452
  related item:
    title info:
      title: Advances in reliability science
  identifier: 9780323913836
  identifier: 0323913830
  identifier: 9780323919432
  identifier: 9780323913836 Ingram Content Group
  identifier: http://proxy.library.tamu.edu/login
  record info:
    record content source: UKMGB
    record creation date: 220701
    record change date: 20260327173922.9
    record identifier: in00005771207
    language of cataloging:
      language term: eng