Probabilistic Design for Optimization and Robustness for Engineers

Safety and Health for Engineers, 3rd Edition, addresses the fundamentals of safety, legal aspects, hazard recognition and control, and techniques for managing safety decisions, as well as: Completely revises and updates all 38 chapters in the book New edition adds more than 110 stories and cases from practice to illustrate various topics or issues New topics on adapting to new safety concerns that arise from technology innovations; convergence of safety, health and environmental departments in many organizations; the concept of prevention through design; and emphasis on safety management systems and risk management and analysis Includes learning exercises and computational examples based on real world situations along with in-depth references for each chapter Includes a detailed solutions manual for academic adopters Covers the primary topics included in certification exams for professional safety, such as CSP/ASP

Discover the proven process for maximizing the potential value of any project. Showing readers how to apply value optimization techniques to project and performance management, dramatically increasing results and efficiency, Value Optimization for Project and Performance Management is written to compliment the Project Management Body of Knowledge, the guidance published by the Project Management Institute (PMI®), making it readily applicable for any project manager. Presents methodology applied with hundreds of clients across a range of industries Filled with practical facilitation and implementation tips Presents a cohesive theory, structured framework, and diverse toolset Walks you through the value optimization process, showing you how to transform the way a product or process is perceived Brimming with examples, Value Optimization for Project and Performance Management provides a link to a free software demo for you to get started in applying value optimization in your own organization. (PMI is a registered mark of Project Management Institute, Inc.)

Learn to fully harness the power of Microsoft Excel® to perform scientific and engineering calculations With this text as your guide, you can significantly enhance Microsoft Excel's® capabilities to execute the calculations needed to solve a variety of chemical, biochemical, physical, engineering, biological, and medicinal problems. The text begins with two chapters that introduce you to Excel's Visual Basic for Applications (VBA) programming language, which allows you to expand Excel's® capabilities, although you can still use the text without learning VBA. Following the author's step-by-step instructions, here are just a few of the calculations you learn to perform: Use worksheet functions to work with matrices Find roots of equations and solve systems of simultaneous equations Solve ordinary differential equations and partial differential equations Perform linear and non-linear regression Use random numbers and the Monte Carlo method This text is loaded with examples ranging from very basic to highly sophisticated solutions. More than 100 end-of-chapter problems help you test and put your knowledge to practice solving real-world problems. Answers and explanatory notes for most of the problems are provided in an appendix. The CD-ROM that accompanies this text provides several useful features: All the spreadsheets, charts, and VBA code needed to perform the examples from the text Solutions to most of the end-of-chapter problems An add-in workbook with more than twenty custom functions This text does not require any background in programming, so it is suitable for both undergraduate and graduate courses. Moreover, practitioners in science and engineering will find that this guide saves hours of time by enabling them to perform most of their calculations with one familiar spreadsheet package

Illustrates how R may be used successfully to solve problems in quantitative finance Applied Probabilistic Calculus for Financial Engineering: An Introduction Using R provides R recipes for asset allocation and portfolio optimization problems. It begins by introducing all the necessary probabilistic and statistical foundations, before moving on to topics related to asset allocation and portfolio optimization with R codes illustrated for various examples. This clear and concise book covers financial engineering, using R in data analysis, and univariate, bivariate, and multivariate data analysis. It examines probabilistic calculus for modeling financial engineering—walking the reader through building an effective financial model from the Geometric Brownian Motion (GBM) Model via probabilistic calculus, while also covering Ito Calculus. Classical mathematical models in financial engineering and modern portfolio theory are discussed—along with the Two Mutual Fund Theorem and The Sharpe Ratio. The book also looks at R as a calculator and using R in data analysis in financial engineering. Additionally, it covers asset allocation using R, financial risk modeling and portfolio optimization using R, global and local optimal values, locating functional maxima and minima, and portfolio optimization by performance analytics in CRAN. Covers optimization methodologies in probabilistic calculus for financial engineering Answers the question: What does a «Random Walk» Financial Theory look like? Covers the GBM Model and the Random Walk Model Examines modern theories of portfolio optimization, including The Markowitz Model of Modern Portfolio Theory (MPT), The Black-Litterman Model, and The Black-Scholes Option Pricing Model Applied Probabilistic Calculus for Financial Engineering: An Introduction Using R s an ideal reference for professionals and students in economics, econometrics, and finance, as well as for financial investment quants and financial engineers.

Presents a probabilistic and information-theoretic framework for a search for static or moving targets in discrete time and space. Probabilistic Search for Tracking Targets uses an information-theoretic scheme to present a unified approach for known search methods to allow the development of new algorithms of search. The book addresses search methods under different constraints and assumptions, such as search uncertainty under incomplete information, probabilistic search scheme, observation errors, group testing, search games, distribution of search efforts, single and multiple targets and search agents, as well as online or offline search schemes. The proposed approach is associated with path planning techniques, optimal search algorithms, Markov decision models, decision trees, stochastic local search, artificial intelligence and heuristic information-seeking methods. Furthermore, this book presents novel methods of search for static and moving targets along with practical algorithms of partitioning and search and screening. Probabilistic Search for Tracking Targets includes complete material for undergraduate and graduate courses in modern applications of probabilistic search, decision-making and group testing, and provides several directions for further research in the search theory. The authors: Provide a generalized information-theoretic approach to the problem of real-time search for both static and moving targets over a discrete space. Present a theoretical framework, which covers known information-theoretic algorithms of search, and forms a basis for development and analysis of different algorithms of search over probabilistic space. Use numerous examples of group testing, search and path planning algorithms to illustrate direct implementation in the form of running routines. Consider a relation of the suggested approach with known search theories and methods such as search and screening theory, search games, Markov decision process models of search, data mining methods, coding theory and decision trees. Discuss relevant search applications, such as quality-control search for nonconforming units in a batch or a military search for a hidden target. Provide an accompanying website featuring the algorithms discussed throughout the book, along with practical implementations procedures.

Focuses on rapid implementation of practical, real-world cost reduction solutions In today's economic climate, the need to cut costs can be the difference between success and failure. Cost Reduction and Optimization for Manufacturing and Industrial Companies covers all major cost reduction areas, providing easy to read examples and advice on steps to take. It provides the roadmap for implementing recommended actions with true and tried methods by taking a modern, all-inclusive look at manufacturing processes. Based on the author's cost reduction experience gained during 30 years of senior operations and consulting engagements with hundreds of organizations, this book includes easy-to-understand and easy-to-implement cost reduction concepts organized into five general areas –labor, material, design, process, and overhead. Each chapter: Dives into a cost reduction area and starts with the bottom line first by summarizing key points Provides proven tactics for cutting costs without a lot of extraneous data Follows a qualitative and design-oriented approach Emphasizes quick implementation and measurable cost reduction Identifies who in the organization should do the work Outlines risks and suggested risk mitigation actions Contains numerous tables, graphs, and photos to show the concepts described in the book Praise for Cost Reduction and Optimization for Manufacturing and Industrial Companies «In this introductory book, Berk not only takes a modern, all-inclusive look at manufacturing processes but also provides substantial coverage of engineering materials and production systems. It follows a more qualitative and design-oriented approach than other texts in the market, helping readers gain a better understanding of important concepts. They'll also discover how micro-economic conditions relate to the process variables in a given process as well as how to perform manufacturing science and quantitative engineering analysis of manufacturing processes.» —Fred Silverman, Director Engineering of Hi-Shear Technology Corporation «Joe Berk has created a unique, practical and straightforward approach to cost reduction in manufacturing. This work provides valuable insights and concrete techniques, based on real-world experiences, to any manufacturing organization undertaking change to position itself to compete successfully in the global marketplace.» —Joe Carleone, President and COO of American Pacific Corporation Check out author Joseph Berk's blog at http://manufacturingtraining.wordpress.com/

Focuses on rapid implementation of practical, real-world cost reduction solutions In today's economic climate, the need to cut costs can be the difference between success and failure. Cost Reduction and Optimization for Manufacturing and Industrial Companies covers all major cost reduction areas, providing easy to read examples and advice on steps to take. It provides the roadmap for implementing recommended actions with true and tried methods by taking a modern, all-inclusive look at manufacturing processes. Based on the author's cost reduction experience gained during 30 years of senior operations and consulting engagements with hundreds of organizations, this book includes easy-to-understand and easy-to-implement cost reduction concepts organized into five general areas –labor, material, design, process, and overhead. Each chapter: Dives into a cost reduction area and starts with the bottom line first by summarizing key points Provides proven tactics for cutting costs without a lot of extraneous data Follows a qualitative and design-oriented approach Emphasizes quick implementation and measurable cost reduction Identifies who in the organization should do the work Outlines risks and suggested risk mitigation actions Contains numerous tables, graphs, and photos to show the concepts described in the book Praise for Cost Reduction and Optimization for Manufacturing and Industrial Companies «In this introductory book, Berk not only takes a modern, all-inclusive look at manufacturing processes but also provides substantial coverage of engineering materials and production systems. It follows a more qualitative and design-oriented approach than other texts in the market, helping readers gain a better understanding of important concepts. They'll also discover how micro-economic conditions relate to the process variables in a given process as well as how to perform manufacturing science and quantitative engineering analysis of manufacturing processes.» —Fred Silverman, Director Engineering of Hi-Shear Technology Corporation «Joe Berk has created a unique, practical and straightforward approach to cost reduction in manufacturing. This work provides valuable insights and concrete techniques, based on real-world experiences, to any manufacturing organization undertaking change to position itself to compete successfully in the global marketplace.» —Joe Carleone, President and COO of American Pacific Corporation Check out author Joseph Berk's blog at http://manufacturingtraining.wordpress.com/

A detailed review of a wide range of meta-heuristic and evolutionary algorithms in a systematic manner and how they relate to engineering optimization problems This book introduces the main metaheuristic algorithms and their applications in optimization. It describes 20 leading meta-heuristic and evolutionary algorithms and presents discussions and assessments of their performance in solving optimization problems from several fields of engineering. The book features clear and concise principles and presents detailed descriptions of leading methods such as the pattern search (PS) algorithm, the genetic algorithm (GA), the simulated annealing (SA) algorithm, the Tabu search (TS) algorithm, the ant colony optimization (ACO), and the particle swarm optimization (PSO) technique. Chapter 1 of Meta-heuristic and Evolutionary Algorithms for Engineering Optimization provides an overview of optimization and defines it by presenting examples of optimization problems in different engineering domains. Chapter 2 presents an introduction to meta-heuristic and evolutionary algorithms and links them to engineering problems. Chapters 3 to 22 are each devoted to a separate algorithm— and they each start with a brief literature review of the development of the algorithm, and its applications to engineering problems. The principles, steps, and execution of the algorithms are described in detail, and a pseudo code of the algorithm is presented, which serves as a guideline for coding the algorithm to solve specific applications. This book: Introduces state-of-the-art metaheuristic algorithms and their applications to engineering optimization; Fills a gap in the current literature by compiling and explaining the various meta-heuristic and evolutionary algorithms in a clear and systematic manner; Provides a step-by-step presentation of each algorithm and guidelines for practical implementation and coding of algorithms; Discusses and assesses the performance of metaheuristic algorithms in multiple problems from many fields of engineering; Relates optimization algorithms to engineering problems employing a unifying approach. Meta-heuristic and Evolutionary Algorithms for Engineering Optimization is a reference intended for students, engineers, researchers, and instructors in the fields of industrial engineering, operations research, optimization/mathematics, engineering optimization, and computer science. OMID BOZORG-HADDAD, PhD, is Professor in the Department of Irrigation and Reclamation Engineering at the University of Tehran, Iran. MOHAMMAD SOLGI, M.Sc., is Teacher Assistant for M.Sc. courses at the University of Tehran, Iran. HUGO A. LO?ICIGA, PhD, is Professor in the Department of Geography at the University of California, Santa Barbara, United States of America.

Exploring methods and techniques to optimize processing energy efficiency in process plants, Energy and Process Optimization for the Process Industries provides a holistic approach that considers optimizing process conditions, changing process flowschemes, modifying equipment internals, and upgrading process technology that has already been used in a process plant with success. Field tested by numerous operating plants, the book describes technical solutions to reduce energy consumption leading to significant returns on capital and includes an 8-point Guidelines for Success. The book provides managers, chemical and mechanical engineers, and plant operators with methods and tools for continuous energy and process improvements.

A thorough introduction to the fundamentals of probability theory This book offers a detailed explanation of the basic models and mathematical principles used in applying probability theory to practical problems. It gives the reader a solid foundation for formulating and solving many kinds of probability problems for deriving additional results that may be needed in order to address more challenging questions, as well as for proceeding with the study of a wide variety of more advanced topics. Great care is devoted to a clear and detailed development of the ‘conceptual model' which serves as the bridge between any real-world situation and its analysis by means of the mathematics of probability. Throughout the book, this conceptual model is not lost sight of. Random variables in one and several dimensions are treated in detail, including singular random variables, transformations, characteristic functions, and sequences. Also included are special topics not covered in many probability texts, such as fuzziness, entropy, spherically symmetric random variables, and copulas. Some special features of the book are: a unique step-by-step presentation organized into 86 topical Sections, which are grouped into six Parts over 200 diagrams augment and illustrate the text, which help speed the reader's comprehension of the material short answer review questions following each Section, with an answer table provided, strengthen the reader's detailed grasp of the material contained in the Section problems associated with each Section provide practice in applying the principles discussed, and in some cases extend the scope of that material an online separate solutions manual is available for course tutors. The various features of this textbook make it possible for engineering students to become well versed in the ‘machinery' of probability theory. They also make the book a useful resource for self-study by practicing engineers and researchers who need a more thorough grasp of particular topics.