Igor A. Ushakov – författare

Proven statistical reliability analysis methods-available for the first time to engineers in the West While probabilistic methods of system reliability analysis have reached an unparalleled degree of refinement, Russian engineers have concentrated on developing more advanced statistical methods. Over the past several decades, their efforts have yielded highly evolved statistical models that have proven to be especially valuable in the estimation of reliability based upon tests of individual units of systems. Now Statistical Reliability Engineering affords engineers a unique opportunity to learn both the theory behind and applications of those statistical methods. Written by three leading innovators in the field, Statistical Reliability Engineering:* Covers all mathematical models for statistical reliability analysis, including Bayesian estimation, accelerated testing, and Monte Carlo simulation* Focuses on the estimation of various measures of system reliability based on the testing of individual units* Contains new theoretical results available for the first time in print* Features numerous examples demonstrating practical applications of the theory presentedStatistical Reliability Engineering is an important professional resource for reliability and design engineers, especially those in the telecommunications and electronics industries. It is also an excellent course text for advanced courses in reliability engineering.

With the growing complexity of engineered systems, reliability hasincreased in importance throughout the twentieth century. Initiallydeveloped to meet practical needs, reliability theory has become anapplied mathematical discipline that permits a priori evaluationsof various reliability indices at the design stages. Theseevaluations help engineers choose an optimal system structure,improve methods of maintenance, and estimate the reliability on thebasis of special testing. Probabilistic Reliability Engineeringfocuses on the creation of mathematical models for solving problemsof system design. Broad and authoritative in its content, Probabilistic ReliabilityEngineering covers all mathematical models associated withprobabilistic methods of reliability analysis, including--unique tothis book--maintenance and cost analysis, as well as many newresults of probabilistic testing. To provide readers with all necessary background material, thistext incorporates a thorough review of the fundamentals ofprobability theory and the theory of stochastic processes. Itoffers clear and detailed treatment of reliability indices, thestructure function, load-strength reliability models, distributionswith monotone intensity functions, repairable systems, the Markovmodels, analysis of performance effectiveness, two-pole networks,optimal redundancy, optimal technical diagnosis, and heuristicmethods in reliability. Throughout the text, an abundance of realworld examples and case studies illustrate and illuminate thetheoretical points under consideration. For engineers in design, operations research, and maintenance, aswell as cost analysts and R&D managers, ProbabilisticReliability Engineering offers the most lucid, comprehensivetreatment of the subject available anywhere. About the editor JAMES A. FALK is Professor and Chairman of the Department ofOperations Research at George Washington University. In addition tohis numerous publications, Dr. Falk has lectured internationally asa Fulbright Lecturer. Of related interest... The reliability-testing "bible" for three generations of EasternEuropean scientists, adapted for Western scientists andengineers... HANDBOOK OF RELIABILITY ENGINEERING Originally published in the USSR, Handbook of ReliabilityEngineering set the standard for the reliability testing oftechnical systems for nearly three generations of appliedscientists and engineers. Authored by a group of prominent Sovietspecialists in reliability, it provides professionals and studentswith a comprehensive reference covering mathematical formulas andtechniques for incorporating reliability into engineering designsand testing procedures. Divided into twenty-four self-containedchapters, the Handbook details reliability fundamentals, examinescommon reliability problems and solutions, provides a collection ofcomputation formulas, and illustrates practical applications. The Handbook's Russian editor and internationally recognized expertIgor A. Ushakov has joined with American engineering professionalsto bring this indispensable resource to English-speaking engineersand scientists. 1994 (0-471-57173-3) 663 pp.

Handbook for the computation and empirical estimation of reliability. Introduces an incomparable volume of easily applicable, cutting-edge results originated by prominent Russian reliability specialists. Completely covers probabilistic reliability, statistical reliability and optimization with simple, step-by-step, numerical examples. Offers a broad range of applications in engineering, operations research, cost analysis and project management. Explores reliability software extensively. Includes appendices with summary reviews of mathematical and statistical fundamentals.

Practical Approaches to Reliability Theory in Cutting-Edge ApplicationsProbabilistic Reliability Models helps readers understand and properly use statistical methodsand optimal resource allocation to solve engineering problems.The author supplies engineers with a deeper understanding of mathematical models while alsoequipping mathematically oriented readers with a fundamental knowledge of the engineeringrelatedapplications at the center of model building. The book showcases the use of probabilitytheory and mathematical statistics to solve common, real-world reliability problems. Followingan introduction to the topic, subsequent chapters explore key systems and models including:• Unrecoverable objects and recoverable systems• Methods of direct enumeration• Markov models and heuristic models• Performance effectiveness• Time redundancy• System survivability• Aging units and their related systems• Multistate systemsDetailed case studies illustrate the relevance of the discussed methods to real-world technicalprojects including software failure avalanches, gas pipelines with underground storage, andintercontinental ballistic missile (ICBM) control systems. Numerical examples and detailedexplanations accompany each topic, and exercises throughout allow readers to test theircomprehension of the presented material.Probabilistic Reliability Models is an excellent book for statistics, engineering, and operationsresearch courses on applied probability at the upper-undergraduate and graduate levels. Thebook is also a valuable reference for professionals and researchers working in industry whowould like a mathematical review of reliability models and the relevant applications.

Practical Approaches to Reliability Theory in Cutting-Edge Applications

Probabilistic Reliability Models helps readers understand and properly use statistical methods

and optimal resource allocation to solve engineering problems.

The author supplies engineers with a deeper understanding of mathematical models while also

equipping mathematically oriented readers with a fundamental knowledge of the engineeringrelated

applications at the center of model building. The book showcases the use of probability

theory and mathematical statistics to solve common, real-world reliability problems. Following

an introduction to the topic, subsequent chapters explore key systems and models including:

• Unrecoverable objects and recoverable systems

• Methods of direct enumeration

• Markov models and heuristic models

• Performance effectiveness

• Time redundancy

• System survivability

• Aging units and their related systems

• Multistate systems

Detailed case studies illustrate the relevance of the discussed methods to real-world technical

projects including software failure avalanches, gas pipelines with underground storage, and

intercontinental ballistic missile (ICBM) control systems. Numerical examples and detailed

explanations accompany each topic, and exercises throughout allow readers to test their

comprehension of the presented material.

Probabilistic Reliability Models is an excellent book for statistics, engineering, and operations

research courses on applied probability at the upper-undergraduate and graduate levels. The

book is also a valuable reference for professionals and researchers working in industry who

would like a mathematical review of reliability models and the relevant applications.

Practical Approaches to Reliability Theory in Cutting-Edge Applications

Probabilistic Reliability Models helps readers understand and properly use statistical methods

and optimal resource allocation to solve engineering problems.

The author supplies engineers with a deeper understanding of mathematical models while also

equipping mathematically oriented readers with a fundamental knowledge of the engineeringrelated

applications at the center of model building. The book showcases the use of probability

theory and mathematical statistics to solve common, real-world reliability problems. Following

an introduction to the topic, subsequent chapters explore key systems and models including:

• Unrecoverable objects and recoverable systems

• Methods of direct enumeration

• Markov models and heuristic models

• Performance effectiveness

• Time redundancy

• System survivability

• Aging units and their related systems

• Multistate systems

Detailed case studies illustrate the relevance of the discussed methods to real-world technical

projects including software failure avalanches, gas pipelines with underground storage, and

intercontinental ballistic missile (ICBM) control systems. Numerical examples and detailed

explanations accompany each topic, and exercises throughout allow readers to test their

comprehension of the presented material.

Probabilistic Reliability Models is an excellent book for statistics, engineering, and operations

research courses on applied probability at the upper-undergraduate and graduate levels. The

book is also a valuable reference for professionals and researchers working in industry who

would like a mathematical review of reliability models and the relevant applications.

A UNIQUE ENGINEERING AND STATISTICAL APPROACH TO OPTIMAL RESOURCE ALLOCATION Optimal Resource Allocation: With Practical Statistical Applications and Theory features the application of probabilistic and statistical methods used in reliability engineering during the different phases of life cycles of technical systems.Bridging the gap between reliability engineering and applied mathematics, the book outlines different approaches to optimal resource allocation and various applications of models and algorithms for solving real-world problems. In addition, the fundamental background on optimization theory and various illustrative numerical examples are provided. The book also features: An overview of various approaches to optimal resource allocation, from classical Lagrange methods to modern algorithms based on ideas of evolution in biologyNumerous exercises and case studies from a variety of areas, including communications, transportation, energy transmission, and counterterrorism protectionThe applied methods of optimization with various methods of optimal redundancy problem solutions as well as the numerical examples and statistical methods needed to solve the problemsPractical thoughts, opinions, and judgments on real-world applications of reliability theory and solves practical problems using mathematical models and algorithmsOptimal Resource Allocation is a must-have guide for electrical, mechanical, and reliability engineers dealing with engineering design and optimal reliability problems. In addition, the book is excellent for graduate and PhD-level courses in reliability theory and optimization.

A UNIQUE ENGINEERING AND STATISTICAL APPROACH TO OPTIMAL RESOURCE ALLOCATION

Optimal Resource Allocation: With Practical Statistical Applications and Theory features the application of probabilistic and statistical methods used in reliability engineering during the different phases of life cycles of technical systems.

Bridging the gap between reliability engineering and applied mathematics, the book outlines different approaches to optimal resource allocation and various applications of models and algorithms for solving real-world problems. In addition, the fundamental background on optimization theory and various illustrative numerical examples are provided. The book also features:

An overview of various approaches to optimal resource allocation, from classical Lagrange methods to modern algorithms based on ideas of evolution in biology Numerous exercises and case studies from a variety of areas, including communications, transportation, energy transmission, and counterterrorism protection The applied methods of optimization with various methods of optimal redundancy problem solutions as well as the numerical examples and statistical methods needed to solve the problems Practical thoughts, opinions, and judgments on real-world applications of reliability theory and solves practical problems using mathematical models and algorithms

Optimal Resource Allocation is a must-have guide for electrical, mechanical, and reliability engineers dealing with engineering design and optimal reliability problems. In addition, the book is excellent for graduate and PhD-level courses in reliability theory and optimization.