Semi Markov processes applications in system reliability and maintenance 1st Edition by Franciszek Grabski ISBN 0128006595 9780128006597

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Product details:

ISBN 10: 0128006595 
ISBN 13: 9780128006597
Author: Franciszek Grabski

Semi-Markov Processes: Applications in System Reliability and Maintenance is a modern view of discrete state space and continuous time semi-Markov processes and their applications in reliability and maintenance. The book explains how to construct semi-Markov models and discusses the different reliability parameters and characteristics that can be obtained from those models. The book is a useful resource for mathematicians, engineering practitioners, and PhD and MSc students who want to understand the basic concepts and results of semi-Markov process theory.

Semi Markov processes applications in system reliability and maintenance 1st Table of contents:

Chapter 1: Introduction to Semi-Markov Processes

• Overview of Stochastic Processes

• Markov vs. Semi-Markov Processes

• Key Properties and Definitions

• Applications in Engineering and Reliability

Chapter 2: Mathematical Foundations

• Probability Theory Essentials

• Renewal Theory and Its Role

• Transition Probability Functions

• Sojourn Time Distributions

Chapter 3: Modeling System Reliability

• Reliability Concepts and Metrics

• Semi-Markov Models for System Failures

• Time-Dependent Reliability Analysis

• Case Studies in Mechanical and Electrical Systems

Chapter 4: Maintenance Modeling with Semi-Markov Processes

• Corrective vs. Preventive Maintenance

• Modeling Repair and Replacement Strategies

• Optimal Maintenance Policies

• Practical Applications in Industry

Chapter 5: Availability and Performability Analysis

• Definitions of System Availability

• Semi-Markov Approach to Availability Modeling

• Performability Metrics

• Examples in Complex Systems

Chapter 6: Queueing Systems and Semi-Markov Processes

• Introduction to Queueing Theory

• Semi-Markov Queue Models

• Application in Manufacturing and Service Systems

• Performance Evaluation Metrics

Chapter 7: Estimation and Inference

• Parameter Estimation for Semi-Markov Models

• Maximum Likelihood Methods

• Bayesian Approaches

• Model Validation Techniques

Chapter 8: Optimization in Reliability and Maintenance

• Cost Models for Maintenance Strategies

• Optimization Techniques Using Semi-Markov Models

• Case Studies in Cost-Effective Maintenance Planning

• Sensitivity Analysis

Chapter 9: Computational Methods and Simulation

• Numerical Methods for Semi-Markov Processes

• Monte Carlo Simulation Approaches

• Software Tools and Implementation

• Illustrative Examples

Chapter 10: Advanced Topics and Recent Developments

• Multi-State and Multi-Component Systems

• Non-Homogeneous Semi-Markov Processes

• Applications in Modern Engineering Systems

• Future Trends in Reliability Modeling

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Tags: Franciszek Grabski, Semi Markov, maintenance