Engineers commonly encounter problems that require them to make decisions under conditions of uncertainty. The uncertainty can be in the definition of the problem, the available information, the alternative solutions and their results, or the random nature of the solution outcomes. As engineers are required to solve increasingly complex design problems with limited resources, they must rely more and more on the proper treatment of uncertainty to make the best decisions. Probability, Statistics, and Reliability for Engineers will assist both engineering students and practicing engineers in understanding the fundamentals of probability, statistics, and reliability methods, especially their applications, limitations, and potentials.
Full of examples, this practical guide allows engineers to model very complex situations and predict an array of possible outcomes. It will also show readers how to write computational algorithms to solve probability and statistical problems.
Among the many examples cited are:
Time to Failure of Cranes
Discharge and Flow of Rivers
Hydraulic Pump Reliability
Predicting Defects in Manufacturing
Nuclear Reactor Reliability
Traffic Flow Patterns
For each chapter in the book, computational examples are given in individual sections, and more detailed engineering applications are presented in a concluding section. Each chapter also includes exercise problems covering the material presented, which will assist readers in practicing the fundamental concepts. Probability, Statistics, and Reliability for Engineers provides a well-rounded introduction to these methods for students in engineering, mathematics, and statistics; practicing engineers in all disciplines; and mathematicians and scientists.Engineers commonly encounter problems that require them to make decisions under conditions of uncertainty. The uncertainty can be in the definition of the problem, the available information, the alternative solutions and their results, or the random nature of the solution outcomes. As engineers are required to solve increasingly complex design problems with limited resources, they must rely more and more on the proper treatment of uncertainty to make the best decisions. Probability, Statistics, and Reliability for Engineers will assist both engineering students and practicing engineers in understanding the fundamentals of probability, statistics, and reliability methods, especially their applications, limitations, and potentials.
Full of examples, this practical guide allows engineers to model very complex situations and predict an array of possible outcomes. It will also show readers how to write computational algorithms to solve probability and statistical problems.
Among the many examples cited are:
Time to Failure of Cranes
Discharge and Flow of Rivers
Hydraulic Pump Reliability
Predicting Defects in Manufacturing
Nuclear Reactor Reliability
Traffic Flow Patterns
For each chapter in the book, computational examples are given in individual sections, and more detailed engineering applications are presented in a concluding section. Each chapter also includes exercise problems covering the material presented, which will assist readers in practicing the fundamental concepts. Probability, Statistics, and Reliability for Engineers provides a well-rounded introduction to these methods for students in engineering, mathematics, and statistics; practicing engineers in all disciplines; and mathematicians and scientists.
