Applied Probability and Stochastic Processes, Second Edition presents a self-contained introduction to elementary probability theory and stochastic processes with a special emphasis on their applications in science, engineering, finance, computer science, and operations research. It covers the theoretical foundations for modeling time-dependent random phenomena in these areas and illustrates applications through the analysis of numerous practical examples. The author draws on his 50 years of experience in the field to give your students a better understanding of probability theory and stochastic processes and enable them to use stochastic modeling in their work. New to the Second Edition Completely rewritten part on probability theory-now more than double in size New sections on time series analysis, random walks, branching processes, and spectral analysis of stationary stochastic processes Comprehensive numerical discussions of examples, which replace the more theoretically challenging sections Additional examples, exercises, and figures Presenting the material in a student-friendly, application-oriented manner, this non-measure theoretic text only assumes a mathematical maturity that applied science students acquire during their undergraduate studies in mathematics. Many exercises allow students to assess their understanding of the topics. In addition, the book occasionally describes connections between probabilistic concepts and corresponding statistical approaches to facilitate comprehension. Some important proofs and challenging examples and exercises are also included for more theoretically interested readers.

Reliability and Maintenance: Networks and Systems gives an up-to-date presentation of system and network reliability analysis as well as maintenance planning with a focus on applicable models. Balancing theory and practice, it presents state-of-the-art research in key areas of reliability and maintenance theory and includes numerous examples and exercises. Every chapter starts with theoretical foundations and basic models and leads to more sophisticated models and ongoing research.

The first part of the book introduces structural reliability theory for binary coherent systems. Within the framework of these systems, the second part covers network reliability analysis. The third part presents simply structured maintenance policies that may help with the cost-optimal scheduling of preventive maintenance. Each part can be read independently of one another.

Suitable for researchers, practitioners, and graduate students in engineering, operations research, computer science, and applied mathematics, this book offers a thorough guide to the mathematical modeling of reliability and maintenance. It supplies the necessary theoretical and practical details for readers to perform reliability analyses and apply maintenance policies in their organizations.

Reliability and Maintenance: Networks and Systems gives an up-to-date presentation of system and network reliability analysis as well as maintenance planning with a focus on applicable models. Balancing theory and practice, it presents state-of-the-art research in key areas of reliability and maintenance theory and includes numerous examples and exercises. Every chapter starts with theoretical foundations and basic models and leads to more sophisticated models and ongoing research. The first part of the book introduces structural reliability theory for binary coherent systems. Within the framework of these systems, the second part covers network reliability analysis. The third part presents simply structured maintenance policies that may help with the cost-optimal scheduling of preventive maintenance. Each part can be read independently of one another. Suitable for researchers, practitioners, and graduate students in engineering, operations research, computer science, and applied mathematics, this book offers a thorough guide to the mathematical modeling of reliability and maintenance. It supplies the necessary theoretical and practical details for readers to perform reliability analyses and apply maintenance policies in their organizations.

Applied Probability and Stochastic Processes, Second Edition presents a self-contained introduction to elementary probability theory and stochastic processes with a special emphasis on their applications in science, engineering, finance, computer science, and operations research. It covers the theoretical foundations for modeling time-dependent random phenomena in these areas and illustrates applications through the analysis of numerous practical examples. The author draws on his 50 years of experience in the field to give your students a better understanding of probability theory and stochastic processes and enable them to use stochastic modeling in their work. New to the Second Edition Completely rewritten part on probability theory-now more than double in size New sections on time series analysis, random walks, branching processes, and spectral analysis of stationary stochastic processes Comprehensive numerical discussions of examples, which replace the more theoretically challenging sections Additional examples, exercises, and figures Presenting the material in a student-friendly, application-oriented manner, this non-measure theoretic text only assumes a mathematical maturity that applied science students acquire during their undergraduate studies in mathematics. Many exercises allow students to assess their understanding of the topics. In addition, the book occasionally describes connections between probabilistic concepts and corresponding statistical approaches to facilitate comprehension. Some important proofs and challenging examples and exercises are also included for more theoretically interested readers.

This book presents stochastic processes in a comprehensive, user-friendly and accessible way containing numerous worked examples. The large number of exercises allows readers to check their understanding of the underlying theory, along with their ability to apply stochastic modelling in their own fields, making the book an excellent basis for self-study. It assumes basic knowledge of calculus and probability theory. The authors also include important proofs and theoretically challenging examples and exercises, thus making the book attractive to those whose interest is more mathematical.

Dieses umfassende Lehr-und Nachschlagewerk fur Naturwissenschaftler und Ingenieure vermittelt dem Leser zentrale Teile der Wahrscheinlichkeitstheorie, der Theorie stochastischer Prozesse sowie der mathematischen Statistik.

Das Buch ist eine Einfuhrung in die Theorie der stochastischen Prozesse fur Studierende technischer und technomathematischer Studienrichtungen an Fach-und Technischen Hoch schulen. Es liefert theoretische Grundlagen fur die Modeliierung von zeit-und zufallsabhan gigen Vorgangen, wie sie in der Physik, Elektrotechnik, Elektronik, Kommunikations-und Systemtheorie sowie Informatik auftreten. Gleichrangig berucksichtigt das Buch Anwen dungen von stochastischen Prozessen im Operations Research, insbesondere in der Bedie nungs-, Instandhaltungs-und Zuverlassigkeitstheorie. Daher wird es auch Technologen und Wirtschaftswissenschaftlern von Interesse sein. Der Stoff wird anband zahlreicher Beispiele anschaulich und anwendungsorientiert dargestellt. Die leicht fassliche Darstellung ermog licht auch dem Autodidakten, sich im Selbststudium das benotigte Grundwissen uber sto chastische Prozesse anzueignen. Das Buch bildet inhaltlich und formal eine Einheit mit dem Lehrbuch des Autors Stochastik ftir Ingenieure -Eine Einfiihrung in die Wahrscheinlich keitstheorie und Mathematische Statistik, das 1995 im gleichen Verlag erschienen ist. Trotz dem ist es unabhangig von diesem Werk lesbar, wenn der Leser die Grundausbildung zur Wahrscheinlichkeitstheorie abgeschlossen hat. Es wird ihm dann im Bedarfsfalle leicht fal len, das erforderliche Basiswissen anband von Kapitel 1 wieder aufzufrischen, eventuell mit einigen Erganzungen uber mehrdimensionale Verteilungen sowie Summen und Folgen von Zufallsgrossen. Eine mathematisch genaue Behandlung, insbesondere der in den Kapiteln 7 und 8 behandelten Gegenstande, ist ohne Nutzung von Grundlagen aus der Mass-und Funk tionentheorie sowie aus der Theorie verallgemeinerter Funktionen nicht moglich. Anderer seits hat der dort vermittelte Stoff eminente Bedeutung fur zahlreiche technische Anwen dungen."

Mit dem Anwachsen des Potentials an teehnisehen Systemen und Anlagen in allen Bereiehen der Volkswirt- sehaft erhohen sieh zwangslaufig die materiellen Auf- wendungen fUr deren Instandhaltung. Daher gewinnt das Problem der effektiven Organisation von Instandhaltungs- prozessen zunehmend an Bedeutung. Ein Hauptweg zur Losung dieser Problematik ist die Durehsetzung des Prinzips der planmaBig vorbeugenden Instandhaltung. Denn auf Grund der Tatsaehe, daB der Betriebsablauf, insbesondere das Ausfallverhalten teeh- nischer Systeme i. a. keinen deterministisehen Gesetz- ma/3igkeiten gentigt, schtitzt die vorbeugende Instand- haltung weitgehend vor unerwarteten Ausfallen bzw. Havarien und erhoht so die Planbarkeit der Instand- haltungsprozesse. Damit sind aber wesentliehe Voraus- setzungen fUr eine effektive Organisation der Instand- haltungsprozesse dureh Fixierung gtinstiger Zeitpunkte fUr die DurehfUhrung prophylaktiseher MaBnahmen sowie des Umfangs und des Standorts von Instandhaltungs- kapazitaten gegeben. Wissensehaftlieh begrtindete Entseheidungen in dieser Hinsieht konnen in vielen Fallen mit Hilfe mathemati- scher Modellbildung getroffen werden. In dieser Riehtung liegen in der DDR gute Erfahrungen vor allem aus der ehemisehen Industrie, der Braunkohlenindustrie und dem Verkehrswesen vor.