Six Sigma With R

Six Sigma has arisen in the last two decades as a breakthrough Quality Management Methodology. With Six Sigma, we are solving problems and improving processes using as a basis one of the most powerful tools of human development: the scientific method. For the analysis of data, Six Sigma requires the use of statistical software, being R an Open Source option that fulfills this requirement. R is a software system that includes a programming language widely used in academic and research departments. Nowadays, it is becoming a real alternative within corporate environments. The aim of this book is to show how R can be used as the software tool in the development of Six Sigma projects. The book includes a gentle introduction to Six Sigma and a variety of examples showing how to use R within real situations. It has been conceived as a self contained piece. Therefore, it is addressed not only to Six Sigma practitioners, but also to professionals trying to initiate themselves in this management methodology. The book may be used as a text book as well.

Presenting a practitioner's guide to capabilities and best practices of quality control systems using the R programming language, this volume emphasizes accessibility and ease-of-use through detailed explanations of R code as well as standard statistical methodologies. In the interest of reaching the widest possible audience of quality-control professionals and statisticians, examples throughout are structured to simplify complex equations and data structures, and to demonstrate their applications to quality control processes, such as ISO standards. The volume balances its treatment of key aspects of quality control, statistics, and programming in R, making the text accessible to beginners and expert quality control professionals alike. Several appendices serve as useful references for ISO standards and common tasks performed while applying quality control with R.

One of Six SigmaOCOs founding fathers shares his trademarked process for ensuring total quality."

An implementation blueprint for SIX SIGMA! "The Six Sigma Way demystifies Six Sigma with a real-world 'how-to 'guide. A good investment for any business planning to launch Six Sigma." John Biedry, VP Quality & Compliance, Sears Home Services. Cost reduction...productivity improvement...customer retention...these are the promises of the Six Sigma quality management system. The Six Sigma Way reveals how GE, Motorola, and numerous other companies are successfully using Six Sigma to fine-tune products and processes, improve performance, and increase profits. Now you can read the roadmap for implementing Six Sigma in your manufacturing or service organization. The authorswho have worked with some of the most visible Six Sigma companies including GEprovide step-by-step guidance and practical implementation guidelines. Whether your goal is to fix a process problem or implement Six Sigma company-wide, The Six Sigma Way will help you develop an approach customized for your company's needs and the challenges of the twenty-first century business environment. The Six Sigma Way: Addresses the challenges and politics of launching, leading, and training people for Six Sigma. Focuses on implementing the major steps and quality improvement tools in the Six Sigma system. Features insights, comments, and examples from business leaders and managers using Six Sigma in their organizations.

Six Sigma is a data-driven management system with near-perfect performance that is a statistical target of operating with no more that 3.4 defects per one million chances. Six sigma has both created avid interest and raised concerns among executives and its practioners. This is all very well for multinationals like Motorola or General Electric but how can it help small and medium-sized enterprises or the service industry? How do you ensure that solutions stick? Quality Beyond Six Sigma responds to this challenge and provides a practical implementation of the issues of Six Sigma, Lean Enterprise and Total Quality and aligns the 'hard' sigma message with the softer sustainable 'strategic issues'. The result is FIT SIGMA. The authors utilize major and minor case studies to support principles and learnings of FIT SIGMA and include review examples and self-assessment that underpin the sustainable process. The three major case studies are contributed by General Electric, Dow Chemical and Seagate Technology. Senior Executives and Managers of organizations of all types and sizes, Management Consultants and Students of all disciplines will find this book a stimulating guide to quality and operational excellence.

Recent advances in the measurement and management of customer value now make it a powerful tool for identifying and prioritizing Six Sigma projects. No longer do champions or black belts have to rely solely on costs to justify the selection of Six Sigma projects. Now the real power and potential of Six Sigma can be turned to its strategic purpose – create and sustain value differences that will translate into greater market share and enhanced profitability.This book has two objectives. The first is to provide the reader with an approach for using the voice of the customer to identify Six Sigma projects and to guide their conduct. The second objective is to show the reader how to obtain the correct voice of the customer – customer value.Customer value is not new. What is new is our ability to measure it. And with this newly discovered ability to measure customer value comes an opportunity to inform Six Sigma projects and initiatives to make them more responsive to customer needs and more responsive to the organization’s bottom line. Let the voice be heard!

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.

Reducing the variation in process outputs is a key part of process improvement. For mass produced components and assemblies, reducing variation can simultaneously reduce overall cost, improve function and increase customer satisfaction with the product. The authors have structured this book around an algorithm for reducing process variation that they call "Statistical Engineering." The algorithm is designed to solve chronic problems on existing high to medium volume manufacturing and assembly processes. The fundamental basis for the algorithm is the belief that we will discover cost effective changes to the process that will reduce variation if we increase our knowledge of how and why a process behaves as it does. A key way to increase process knowledge is to learn empirically, that is, to learn by observation and experimentation. The authors discuss in detail a framework for planning and analyzing empirical investigations, known by its acronym QPDAC (Question, Plan, Data, Analysis, Conclusion). They classify all effective ways to reduce variation into seven approaches. A unique aspect of the algorithm forces early consideration of the feasibility of each of the approaches. Also includes case studies, chapter exercises, chapter supplements, and six appendices. PRAISE FOR Statistical Engineering "I found this book uniquely refreshing. Don't let the title fool you. The methods described in this book are statistically sound but require very little statistics. If you have ever wanted to solve a problem with statistical certainty (without being a statistician) then this book is for you. - A reader in Dayton, OH "This is the most comprehensive treatment of variation reduction methods and insights I’ve ever seen."- Gary M. Hazard Tellabs "Throughout the text emphasis has been placed on teamwork, fixing the obvious before jumping to advanced studies, and cost of implementation. All this makes the manuscript !attractive for real-life application of complex techniques." - Guru Chadhabr Comcast IP Services COMMENTS FROM OTHER CUSTOMERS Average Customer Rating (5 of 5 based on 1 review) "This is NOT a typical book on statistical tools. It is a strategy book on how to search for cost-effective changes to reduce variation using empirical means (i.e. observation and experiment). The uniqueness of this book: Summarizes the seven ways to reduce variation so we know the goal of the data gathering and analysis, present analysis results using graphs instead of P-value, and integrates Taguchi, Shainin methods, and classical statistical approach. It is a must read for those who are in the business of reducing variation using data, in particular for the Six Sigma Black Belts and Master Black Belts. Don't forget to read the solutions to exercises and supplementary materials to each chapter on the enclosed CD-ROM." - A. Wong, Canada