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Statistical Process Control For Quality Improvement- Hardcover Version
by J. Koronacki J.R. ThompsonThe first edition of this groundbreaking text showed that the Statistical Process Control (SPC) paradigm of W. Edwards Deming was not at all the same as the Quality Control paradigm that has dominated American manufacturing since World War II. Its philosophy of good management is rooted in a paradigm as process-oriented as physics, yet produces a friendly and fulfilling work environment. This second edition broadens its view to reveal even more of Deming's philosophy and provides more techniques for use at the managerial level. It shows readers that CEOs and service industries need SPC at least as much as production lines, and it offers precise methods and guidelines for their use.
Statistical Process Control for Real-World Applications
by William A. LevinsonThe normal or bell curve distribution is far more common in statistics textbooks than it is in real factories, where processes follow non-normal and often highly skewed distributions. Statistical Process Control for Real-World Applications shows how to handle non-normal applications scientifically and explain the methodology to suppliers and custom
Statistical Process Control in Automated Manufacturing
by Bert KeatsThis book provides an introduction to statistical process control in automated manufacturing and suggests implementation strategies. It focuses on time series applications in statistical process control and explores the role of knowledge-based systems in process control.
Statistical Process Control in Manufacturing Practice
by Fred W. KearEmphasizing the importance of understanding and reducing process variation to achieve quality manufacturing performance, this work establishes how statistical process control (SPC) provides powerful tools for measuring and regulating manufacturing processes. It presents information derived from time-tested applications of SPC techniques at on-site process situations in manufacturing. It is designed to assist manufacturing organizations in explaining and implementing successful SPC programmes.
Statistical Process Monitoring and Optimization (Statistics: A Series of Textbooks and Monographs)
by Sung H. Park G. Geoffrey ViningDemonstrates ways to track industrial processes and performance, integrating related areas such as engineering process control, statistical reasoning in TQM, robust parameter design, control charts, multivariate process monitoring, capability indices, experimental design, empirical model building, and process optimization. The book covers a range o
Statistical Pronunciation Modeling for Non-Native Speech Processing
by Rainer E. Gruhn Wolfgang Minker Satoshi NakamuraIn this work, the authors present a fully statistical approach to model non--native speakers' pronunciation. Second-language speakers pronounce words in multiple different ways compared to the native speakers. Those deviations, may it be phoneme substitutions, deletions or insertions, can be modelled automatically with the new method presented here. The methods is based on a discrete hidden Markov model as a word pronunciation model, initialized on a standard pronunciation dictionary. The implementation and functionality of the methodology has been proven and verified with a test set of non-native English in the regarding accent. The book is written for researchers with a professional interest in phonetics and automatic speech and speaker recognition.
Statistical Quality Control
by M. Jeya ChandraIt has recently become apparent that "quality" is quickly becoming the single most important factor for success and growth in business. Companies achieving higher quality in their products through effective quality improvement programs enjoy a significant competitive advantage. It is, therefore, essential for engineers responsible for design, devel
Statistical Quality Control: Using MINITAB, R, JMP and Python
by Bhisham C. GuptaSTATISTICAL QUALITY CONTROL Provides a basic understanding of statistical quality control (SQC) and demonstrates how to apply the techniques of SQC to improve the quality of products in various sectorsThis book introduces Statistical Quality Control and the elements of Six Sigma Methodology, illustrating the widespread applications that both have for a multitude of areas, including manufacturing, finance, transportation, and more. It places emphasis on both the theory and application of various SQC techniques and offers a large number of examples using data encountered in real life situations to support each theoretical concept.Statistical Quality Control: Using MINITAB, R, JMP and Python begins with a brief discussion of the different types of data encountered in various fields of statistical applications and introduces graphical and numerical tools needed to conduct preliminary analysis of the data. It then discusses the basic concept of statistical quality control (SQC) and Six Sigma Methodology and examines the different types of sampling methods encountered when sampling schemes are used to study certain populations. The book also covers Phase 1 Control Charts for variables and attributes; Phase II Control Charts to detect small shifts; the various types of Process Capability Indices (CPI); certain aspects of Measurement System Analysis (MSA); various aspects of PRE-control; and more. This helpful guide alsoFocuses on the learning and understanding of statistical quality control for second and third year undergraduates and practitioners in the fieldDiscusses aspects of Six Sigma MethodologyTeaches readers to use MINITAB, R, JMP and Python to create and analyze chartsRequires no previous knowledge of statistical theoryIs supplemented by an instructor-only book companion site featuring data sets and a solutions manual to all problems, as well as a student book companion site that includes data sets and a solutions manual to all odd-numbered problemsStatistical Quality Control: Using MINITAB, R, JMP and Python is an excellent book for students studying engineering, statistics, management studies, and other related fields and who are interested in learning various techniques of statistical quality control. It also serves as a desk reference for practitioners who work to improve quality in various sectors, such as manufacturing, service, transportation, medical, oil, and financial institutions. It‘s also useful for those who use Six Sigma techniques to improve the quality of products in such areas.
Statistical Reliability Engineering: Methods, Models and Applications (Springer Series in Reliability Engineering)
by Hoang PhamThis book presents the state-of-the-art methodology and detailed analytical models and methods used to assess the reliability of complex systems and related applications in statistical reliability engineering. It is a textbook based mainly on the author’s recent research and publications as well as experience of over 30 years in this field. The book covers a wide range of methods and models in reliability, and their applications, including: statistical methods and model selection for machine learning; models for maintenance and software reliability; statistical reliability estimation of complex systems; and statistical reliability analysis of k out of n systems, standby systems and repairable systems. Offering numerous examples and solved problems within each chapter, this comprehensive text provides an introduction to reliability engineering graduate students, a reference for data scientists and reliability engineers, and a thorough guide for researchers and instructors in the field.
Statistical Robust Beamforming for Broadcast Channels and Applications in Satellite Communication (Foundations in Signal Processing, Communications and Networking #22)
by Andreas GründingerThis book investigates adaptive physical-layer beamforming and resource allocation that ensure reliable data transmission in the multi-antenna broadcast channel. The book provides an overview of robust optimization techniques and modelling approximations to deal with stochastic performance metrics. One key contribution of the book is a closed-form description of the achievable rates with unlimited transmit power for a rank-one channel error model. Additionally, the book provides a concise duality framework to transform mean square error (MSE) based beamformer designs, e.g., quality of service and balancing optimizations, into equivalent uplink filter designs. For the algorithmic solution, the book analyses the following paradigm: transmission to receivers with large MSE targets (low demands) is switched off if the transmit power is low. The book also studies chance constrained optimizations for limiting the outage probability. In this context, the book provides two novel conservative outage probability approximations, that result in convex beamformer optimizations. To compensate for the remaining inaccuracy, the book introduces a post-processing power allocation. Finally, the book applies the introduced beamformer designs for SatCom, where interference from neighboring spotbeams and channel fading are the main limitations.
Statistical Signal Processing: Frequency Estimation (Springerbriefs In Statistics Ser.)
by Swagata Nandi Debasis KunduThis book introduces readers to various signal processing models that have been used in analyzing periodic data, and discusses the statistical and computational methods involved. Signal processing can broadly be considered to be the recovery of information from physical observations. The received signals are usually disturbed by thermal, electrical, atmospheric or intentional interferences, and due to their random nature, statistical techniques play an important role in their analysis. Statistics is also used in the formulation of appropriate models to describe the behavior of systems, the development of appropriate techniques for estimation of model parameters and the assessment of the model performances. Analyzing different real-world data sets to illustrate how different models can be used in practice, and highlighting open problems for future research, the book is a valuable resource for senior undergraduate and graduate students specializing in mathematics or statistics.
Statistical Signal Processing in Engineering
by Umberto SpagnoliniA problem-solving approach to statistical signal processing for practicing engineers, technicians, and graduate students This book takes a pragmatic approach in solving a set of common problems engineers and technicians encounter when processing signals. In writing it, the author drew on his vast theoretical and practical experience in the field to provide a quick-solution manual for technicians and engineers, offering field-tested solutions to most problems engineers can encounter. At the same time, the book delineates the basic concepts and applied mathematics underlying each solution so that readers can go deeper into the theory to gain a better idea of the solution’s limitations and potential pitfalls, and thus tailor the best solution for the specific engineering application. Uniquely, Statistical Signal Processing in Engineering can also function as a textbook for engineering graduates and post-graduates. Dr. Spagnolini, who has had a quarter of a century of experience teaching graduate-level courses in digital and statistical signal processing methods, provides a detailed axiomatic presentation of the conceptual and mathematical foundations of statistical signal processing that will challenge students’ analytical skills and motivate them to develop new applications on their own, or better understand the motivation underlining the existing solutions. Throughout the book, some real-world examples demonstrate how powerful a tool statistical signal processing is in practice across a wide range of applications. Takes an interdisciplinary approach, integrating basic concepts and tools for statistical signal processing Informed by its author’s vast experience as both a practitioner and teacher Offers a hands-on approach to solving problems in statistical signal processing Covers a broad range of applications, including communication systems, machine learning, wavefield and array processing, remote sensing, image filtering and distributed computations Features numerous real-world examples from a wide range of applications showing the mathematical concepts involved in practice Includes MATLAB code of many of the experiments in the book Statistical Signal Processing in Engineering is an indispensable working resource for electrical engineers, especially those working in the information and communication technology (ICT) industry. It is also an ideal text for engineering students at large, applied mathematics post-graduates and advanced undergraduates in electrical engineering, applied statistics, and pure mathematics, studying statistical signal processing.
The Statistical Stability Phenomenon
by Igor I. GorbanThis monograph investigates violations of statistical stability of physical events, variables, and processes and develops a new physical-mathematical theory taking into consideration such violations - the theory of hyper-random phenomena. There are five parts. The first describes the phenomenon of statistical stability and its features, and develops methods for detecting violations of statistical stability, in particular when data is limited. The second part presents several examples of real processes of different physical nature and demonstrates the violation of statistical stability over broad observation intervals. The third part outlines the mathematical foundations of the theory of hyper-random phenomena, while the fourth develops the foundations of the mathematical analysis of divergent and many-valued functions. The fifth part contains theoretical and experimental studies of statistical laws where there is violation of statistical stability. The monograph should be of particular interest to engineers and scientists in general who study the phenomenon of statistical stability and use statistical methods for high-precision measurements, prediction, and signal processing over long observation intervals.
Statistical Techniques for Project Control (Systems Innovation Book Series)
by Adedeji B. Badiru Tina AgustiadyWinner of the IIE Book of the Month for June 2012A project can be simple or complex. In each case, proven project management processes must be followed. In all cases of project management implementation, control must be exercised in order to assure that project objectives are achieved. Statistical Techniques for Project Control seamlessly integrate
Statistical Techniques in Geographical Analysis
by Gareth Shaw Stewart Barr Dennis WheelerThis volume includes changes in the switch from DOS-based to Windows-based, menu-driven forms of SPSS and MINITAB is the most important. The other change shows availability of data in digital form from websites or via CD-ROMs. The book is useful for teachers and students.
Statistical Thermodynamics: An Engineering Approach
by John W. DailyStatistical Thermodynamics: An Engineering Approach covers in a practical, readily understandable manner the underlying meaning of entropy, temperature and other thermodynamic concepts, the foundations of quantum mechanics, and the physical basis of gas, liquid and solid phase properties. It presents simply the relationship between macroscopic and microscopic thermodynamics. In addition, the molecular basis of transport phenomena and chemical kinetics are explored as are basic concepts in spectroscopy. Modern computational tools for solving thermodynamic problems are explored, and the student is assured that he or she will gain knowledge of practical usefulness. This essential text is suitable for mechanical or aerospace engineering graduate students who have a strong background in engineering thermodynamics, those entering advanced fields such as combustion, high temperature gas dynamics, environmental sciences, or materials processing and those who wish to build a background for understanding advanced experimental diagnostic techniques in these or similar fields.
Statistical Thermodynamics: Basics and Applications to Chemical Systems
by Iwao TeraokaThis textbook introduces chemistry and chemical engineering students to molecular descriptions of thermodynamics, chemical systems, and biomolecules. Equips students with the ability to apply the method to their own systems, as today's research is microscopic and molecular and articles are written in that language Provides ample illustrations and tables to describe rather difficult concepts Makes use of plots (charts) to help students understand the mathematics necessary for the contents Includes practice problems and answers
Statistical Thermodynamics for Pure and Applied Sciences: Statistical Thermodynamics
by Frederick Richard McCourtThis textbook concerns thermal properties of bulk matter and is aimed at advanced undergraduate or first-year graduate students in a range of programs in science or engineering. It provides an intermediate level presentation of statistical thermodynamics for students in the physical sciences (chemistry, nanosciences, physics) or related areas of applied science/engineering (chemical engineering, materials science, nanotechnology engineering), as they are areas in which statistical mechanical concepts play important roles. The book enables students to utilize microscopic concepts to achieve a better understanding of macroscopic phenomena and to be able to apply these concepts to the types of sub-macroscopic systems encountered in areas of nanoscience and nanotechnology.
Statistical Tools for the Comprehensive Practice of Industrial Hygiene and Environmental Health Sciences
by David L. JohnsonReviews and reinforces concepts and techniques typical of a first statistics course with additional techniques useful to the IH/EHS practitioner. Includes both parametric and non-parametric techniques described and illustrated in a worker health and environmental protection practice context Illustrated through numerous examples presented in the context of IH/EHS field practice and research, using the statistical analysis tools available in Excel® wherever possible Emphasizes the application of statistical tools to IH/EHS-type data in order to answer IH/EHS-relevant questions Includes an instructor’s manual that follows in parallel with the textbook, including PowerPoints to help prepare lectures and answers in the text as for the Exercises section of each chapter.
Statistics: A Practical Approach for Process Control Engineers
by Myke KingThe first statistics guide focussing on practical application to process control design and maintenance Statistics for Process Control Engineers is the only guide to statistics written by and for process control professionals. It takes a wholly practical approach to the subject. Statistics are applied throughout the life of a process control scheme – from assessing its economic benefit, designing inferential properties, identifying dynamic models, monitoring performance and diagnosing faults. This book addresses all of these areas and more. The book begins with an overview of various statistical applications in the field of process control, followed by discussions of data characteristics, probability functions, data presentation, sample size, significance testing and commonly used mathematical functions. It then shows how to select and fit a distribution to data, before moving on to the application of regression analysis and data reconciliation. The book is extensively illustrated throughout with line drawings, tables and equations, and features numerous worked examples. In addition, two appendices include the data used in the examples and an exhaustive catalogue of statistical distributions. The data and a simple-to-use software tool are available for download. The reader can thus reproduce all of the examples and then extend the same statistical techniques to real problems. Takes a back-to-basics approach with a focus on techniques that have immediate, practical, problem-solving applications for practicing engineers, as well as engineering students Shows how to avoid the many common errors made by the industry in applying statistics to process control Describes not only the well-known statistical distributions but also demonstrates the advantages of applying the large number that are less well-known Inspires engineers to identify new applications of statistical techniques to the design and support of control schemes Provides a deeper understanding of services and products which control engineers are often tasked with assessing This book is a valuable professional resource for engineers working in the global process industry and engineering companies, as well as students of engineering. It will be of great interest to those in the oil and gas, chemical, pulp and paper, water purification, pharmaceuticals and power generation industries, as well as for design engineers, instrument engineers and process technical support.
Statistics and Data Analysis for Engineers and Scientists (Transactions on Computer Systems and Networks)
by Tanvir Mustafy Md. Tauhid RahmanThis textbook summarizes the different statistical, scientific, and financial data analysis methods for users ranging from a high school level to a professional level. It aims to combine the data analysis methods using three different programs—Microsoft Excel, SPSS, and MATLAB. The book combining the different data analysis tools is a unique approach. The book presents a variety of real-life problems in data analysis and machine learning, delivering the best solution. Analysis methods presented in this book include but are not limited to, performing various algebraic and trigonometric operations, regression modeling, and correlation, as well as plotting graphs and charts to represent the results. Fundamental concepts of applied statistics are also explained here, with illustrative examples. Thus, this book presents a pioneering solution to help a wide range of students, researchers, and professionals learn data processing, interpret different findings derived from the analyses, and apply them to their research or professional fields. The book also includes worked examples of practical problems. The primary focus behind designing these examples is understanding the concepts of data analysis and how it can solve problems. The chapters include practice exercises to assist users in enhancing their skills to execute statistical analysis calculations using software instead of relying on tables for probabilities and percentiles in the present world.
Statistics and Probability Theory
by Michael Havbro FaberThis book provides the reader with the basic skills and tools of statistics and probability in the context of engineering modeling and analysis. The emphasis is on the application and the reasoning behind the application of these skills and tools for the purpose of enhancing decision making in engineering. The purpose of the book is to ensure that the reader will acquire the required theoretical basis and technical skills such as to feel comfortable with the theory of basic statistics and probability. Moreover, in this book, as opposed to many standard books on the same subject, the perspective is to focus on the use of the theory for the purpose of engineering model building and decision making. This work is suitable for readers with little or no prior knowledge on the subject of statistics and probability.
Statistics and Scaling in Turbulent Rayleigh-Bénard Convection
by Emily S.C. ChingThis Brief addresses two issues of interest of turbulent Rayleigh-Bénard convection. The rst issue is the characterization and understanding of the statistics of the velocity and temperature uctuations in the system. The second issue is the revelation and understanding of the nature of the scaling behavior of the velocity temperature structure functions. The problem under the Oberbeck-Boussinesq approximation is formulated. The statistical tools, including probability density functions (PDF) and conditional statistics, for studying fluctuations are introduced, and implicit PDF formulae for fluctuations obeying certain statistical symmetries are derived. Applications of these PDF formulae to study the fluctuations in turbulent Rayleigh-Bénard convection are then discussed. The phenomenology of the different types of scaling behavior: the Bolgiano-Obhukov scaling behavior when buoyancy effects are significant and the Kolmogorov-Obukhov-Corrsin scaling behavior when they are not, is introduced. A crossover between the two types of scaling behavior is expected to occur at the Bolgiano length scale above which buoyancy is important. The experimental observations are reviewed. In the central region of the convective cell, the Kolmogorov-Obukhov-Corrsin scaling behavior has been observed. On the other hand, the Bolgiano-Obukhov scaling remains elusive only until recently. By studying the dependence of the conditional temperature structure functions on the locally averaged thermal dissipation rate, evidence for the Bolgiano-Obukhov scaling has recently been found near the bottom plate. The different behaviors observed in the two regions could be attributed to the different size of the Bolgiano scale. What physics determines the relative size of the Bolgiano scale remains to be understood. The Brief is concluded by a discussion of these outstanding issues.
Statistics for Aquaculture (United States Aquaculture Society series)
by Ram C. BhujelPublished in cooperation with the United States Aquaculture Society A strong background in statistics is essential for researchers in any scientific field in order to design experiments, survey research, analyze data, and present findings accurately. To date, there has been no single text to address these concepts in the context of aquaculture research. Statistics for Aquaculture fills that gap by providing user-friendly coverage of statistical principles and methods geared specifically toward the aquaculture community. Statistics for Aquaculture begins with an introduction to basic concepts such as experimental units and data collection, transitions through the fundamentals of experimental design and hypothesis formulation, and culminates with a discussion of experimental analysis and advanced topics in the latest research. Well-illustrated with examples from around the world, each chapter ends with practical exercises to better apply the information covered. Statistics for Aquaculture is a must-have title for students, researchers, professors, and industry personnel alike. Applicable as an introduction to aquaculture or a valuable refresher, this textbook is the first of its kind in this field.
Statistics for Chemical and Process Engineers
by Yuri A. W. ShardtA coherent, concise and comprehensive course in the statistics needed for a modern career in chemical engineering; covers all of the concepts required for the American Fundamentals of Engineering examination. This book shows the reader how to develop and test models, design experiments and analyse data in ways easily applicable through readily available software tools like MS Excel® and MATLAB®. Generalized methods that can be applied irrespective of the tool at hand are a key feature of the text. The reader is given a detailed framework for statistical procedures covering: · data visualization; · probability; · linear and nonlinear regression; · experimental design (including factorial and fractional factorial designs); and · dynamic process identification. Main concepts are illustrated with chemical- and process-engineering-relevant examples that can also serve as the bases for checking any subsequent real implementations. Questions are provided (with solutions available for instructors) to confirm the correct use of numerical techniques, and templates for use in MS Excel and MATLAB can also be downloaded from extras. springer. com. With its integrative approach to system identification, regression and statistical theory, Statistics for Chemical and Process Engineers provides an excellent means of revision and self-study for chemical and process engineers working in experimental analysis and design in petrochemicals, ceramics, oil and gas, automotive and similar industries and invaluable instruction to advanced undergraduate and graduate students looking to begin a career in the process industries.