Engineering Reliability and Risk Assessment

Description

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. Cover Advances in Reliability Science: Engineering Reliability and Risk Assessment Copyright 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 “