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This chapter is from Statistics for Six Sigma Made Easy, a simple guide to using the powerful statistical tools of Six Sigma to solve real-world problems. Warren Brussee, a Six Sigma manager who helped his teams generate millions of dollars in savings, shows how to plot, interpret, and validate data for a Six Sigma project. The basic statistical tools in the book can be applied to manufacturing, sales, marketing, process, equipment design, and more. Best of all, no background in statistics is required to start improving quality and initiating cost-saving improvements right away.
"This book is about the use of modern statistical methods for quality control and improvement. It provides comprehensive coverage of the subject from basic principles to state-of-the-art concepts. and applications. The objective is to give the reader a sound understanding of the principles and the basis for applying them in a variety of situations. Although statistical techniques are emphasized. throughout, the book has a strong engineering and management orientation. Extensive knowledge. of statistics is not a prerequisite for using this book. Readers whose background includes a basic course in statistical methods will find much of the material in this book easily accessible"--
Das bewährte Handbuch zum Statistiktool Six Sigma - jetzt in neuer, aktualisierter Auflage! - besprochen werden täglich benötigte Verfahren und deren Implementation - erweiterte Behandlung u.a. des Benchmarkings - mit vielen praxisnahen Übungen - enthält Pläne, Checklisten und Übersichten häufig auftretender Fehler
Increasing pressures to produce new products faster and cheaper are resulting in huge efforts to streamline and restructure the traditional new product development (NPD) process. The purpose of the book is to describe, assess and apply the latest constructs, methods, techniques and processes to enable managers, professionals, and practitioners to be more effective in designing, developing and commercializing new products and services. It provides guidance and support in formulating and executing NPD programs for business practitioners and MBA students. The book is written from an Integrated Product Development (IPD) perspective, linking all aspects of marketing, costing and manufacturing into the development process even before the first prototype is built. It covers the advanced tools necessary to achieve this such as virtual prototyping and fully integrated business systems, and explains the changes needed to organizational structure and thinking.
This book helps professionals to turn their own Six Sigma projects into reality. Using a sample project, the book guides readers through all aspects of Six Sigma, from identifying and defining a suitable project topic, to sustainably managing its success in the control phase. By demonstrating all the necessary steps supported by a DMAIC software guide, it makes the application of the sequentially linked DMAIC tools easy to understand and directly transferable to typical Six Sigma business projects. Further, each chapter provides numerous questions and answers, tasks and the framework for an environmental standard project. This book is an essential part of the author’s teaching material on the topic, which also includes the software ‘sigmaGuide’, a template for project documentation and several hours of video content featuring course materials on edX Learning Community.
Lean production, has long been regarded as critical to business success in many industries. Over the last ten years, instruction in six sigma has been increasingly linked with learning about the elements of lean production. Introduction to Engineering Statistics and Lean Sigma builds on the success of its first edition (Introduction to Engineering Statistics and Six Sigma) to reflect the growing importance of the "lean sigma" hybrid. As well as providing detailed definitions and case studies of all six sigma methods, Introduction to Engineering Statistics and Lean Sigma forms one of few sources on the relationship between operations research techniques and lean sigma. Readers will be given the information necessary to determine which sigma methods to apply in which situation, and to predict why and when a particular method may not be effective. Methods covered include: • control charts and advanced control charts, • failure mode and effects analysis, • Taguchi methods, • gauge R&R, and • genetic algorithms. The second edition also greatly expands the discussion of Design For Six Sigma (DFSS), which is critical for many organizations that seek to deliver desirable products that work first time. It incorporates recently emerging formulations of DFSS from industry leaders and offers more introductory material on the design of experiments, and on two level and full factorial experiments, to help improve student intuition-building and retention. The emphasis on lean production, combined with recent methods relating to Design for Six Sigma (DFSS), makes Introduction to Engineering Statistics and Lean Sigma a practical, up-to-date resource for advanced students, educators, and practitioners.
Now with SAGE Publishing! Timothy S. Hatten’s Small Business Management: Creating a Sustainable Competitive Advantage, Seventh Edition equips students with the tools they need to navigate the important financial, legal, marketing, managerial, and operational decisions to help them create and maintain a sustainable competitive advantage in small business. Strong emphasis is placed on application with Experiential Learning Activities and application of technology and social media throughout. New cases, real-world examples, and illuminating features spotlight the diverse, innovative contributions of small business owners to the economy. Whether your students dream of launching a new venture, purchasing a franchise, managing a lifestyle business, or joining the family company, they will learn important best practices for competing in the modern business world. New to this Edition Experiential Learning Activities provide students with hands-on opportunities to practice their small business management skills. Tech in Action boxes highlight how small business owners can leverage technology, big data, and social media. Issues in Small Business boxes prompt critical thinking on current issues. Small Business in Action videos showcase stories and interviews from a wide variety of small business owners. How To. . . videos provide students with instructions and examples of basic business tasks such as performing a breakeven analysis, understanding income statements, and forecasting demand.
This undergraduate statistical quality assurance textbook clearly shows with real projects, cases and data sets how statistical quality control tools are used in practice. Among the topics covered is a practical evaluation of measurement effectiveness for both continuous and discrete data. Gauge Reproducibility and Repeatability methodology (including confidence intervals for Repeatability, Reproducibility and the Gauge Capability Ratio) is thoroughly developed. Process capability indices and corresponding confidence intervals are also explained. In addition to process monitoring techniques, experimental design and analysis for process improvement are carefully presented. Factorial and Fractional Factorial arrangements of treatments and Response Surface methods are covered. Integrated throughout the book are rich sets of examples and problems that help readers gain a better understanding of where and how to apply statistical quality control tools. These large and realistic problem sets in combination with the streamlined approach of the text and extensive supporting material facilitate reader understanding. Second Edition Improvements Extensive coverage of measurement quality evaluation (in addition to ANOVA Gauge R&R methodologies) New end-of-section exercises and revised-end-of-chapter exercises Two full sets of slides, one with audio to assist student preparation outside-of-class and another appropriate for professors’ lectures Substantial supporting material Supporting Material Seven R programs that support variables and attributes control chart construction and analyses, Gauge R&R methods, analyses of Fractional Factorial studies, Propagation of Error analyses and Response Surface analyses Documentation for the R programs Excel data files associated with the end-of-chapter problem sets, most from real engineering settings
This highly popular introduction to confidence intervals has been thoroughly updated and expanded. It includes methods for using confidence intervals, with illustrative worked examples and extensive guidelines and checklists to help the novice.
The Book of R is a comprehensive, beginner-friendly guide to R, the world’s most popular programming language for statistical analysis. Even if you have no programming experience and little more than a grounding in the basics of mathematics, you’ll find everything you need to begin using R effectively for statistical analysis. You’ll start with the basics, like how to handle data and write simple programs, before moving on to more advanced topics, like producing statistical summaries of your data and performing statistical tests and modeling. You’ll even learn how to create impressive data visualizations with R’s basic graphics tools and contributed packages, like ggplot2 and ggvis, as well as interactive 3D visualizations using the rgl package. Dozens of hands-on exercises (with downloadable solutions) take you from theory to practice, as you learn: –The fundamentals of programming in R, including how to write data frames, create functions, and use variables, statements, and loops –Statistical concepts like exploratory data analysis, probabilities, hypothesis tests, and regression modeling, and how to execute them in R –How to access R’s thousands of functions, libraries, and data sets –How to draw valid and useful conclusions from your data –How to create publication-quality graphics of your results Combining detailed explanations with real-world examples and exercises, this book will provide you with a solid understanding of both statistics and the depth of R’s functionality. Make The Book of R your doorway into the growing world of data analysis.