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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.
A PLAIN ENGLISH GUIDE TO SOLVING REAL-WORLD PROBLEMS WITH SIX SIGMA Six Sigma is one of the most effective strategies for improving processes, creating better products, and boosting customer satisfaction, but business leaders often balk at its reputation for being too complex. Don't fall into that trap. Six Sigma is simple to understand and implement--if you have Statistics for Six Sigma Made Easy! Warren Brussee has helped businesses save millions of dollars with Six Sigma, and he explains how you can achieve similar results in this step-by-step guide. He presents a thorough overview of the Six Sigma methodology and techniques for successful implementation, as well as a clear explanation of DMAIC--the problem-solving method used by Six Sigma Greenbelts. Statistics for Six Sigma Made Easy! provides: A simplified form of the most common Six Sigma tools All the basic Six Sigma formulas and tables Dozens of Six Sigma statistical problem-solving case studies A matrix for finding the right statistical tool to meet your needs Basic Greenbelt training in one concise reference Best of all, no background in statistics is required--you can start improving quality and initiating costsaving improvements right away. Statistics for Six Sigma Made Easy! is the only reference you need to facilitate real-world application of Six Sigma tools.
The evolution of knowledge management theory and the special emphasis on human and social capital sets new challenges for knowledge-driven and technology-enabled innovation. Emerging technologies including big data and analytics have significant implications for sustainability, policy making, and competitiveness. This edited volume promotes scientific research into the potential contributions knowledge management can make to the new era of innovation and social inclusive economic growth. We are grateful to all the contributors of this edition for their intellectual work. The organization of the relevant debate is aligned around three pillars: SECTION A. DATA, KNOWLEDGE, HUMAN AND SOCIAL CAPITAL FOR INNOVATION We elaborate on the new era of knowledge types and the emerging forms of social capital and their impact on technology-driven innovation. Topics include: · Social Networks · Smart Education · Social Capital · Corporate Innovation · Disruptive Innovation · Knowledge integration · Enhanced Decision-Making. SECTION B. KNOWLEDGE MANAGEMENT & BIG DATA ENABLED INNOVATION In this section, knowledge management and big data applications and systems are presented. Selective topic include: · Crowdsourcing Analysis · Natural Language Processing · Data Governance · Knowledge Extraction · Ontology Design Semantic Modeling SECTION C. SUSTAINABLE DEVELOPMENT In the section, the debate on the impact of knowledge management and big data research to sustainability is promoted with integrative discussion of complementary social and technological factors including: · Big Social Networks on Sustainable Economic Development · Business Intelligence
Organizations today have access to vast stores of data that come in a wide variety of forms and may be stored in places ranging from file cabinets to databases, and from library shelves to the Internet. The enormous growth in the quantity of data, however, has brought with it growing problems with the quality of information, further complicated by the struggles many organizations are experiencing as they try to improve their systems for knowledge management and organizational memory. Failure to manage information properly, or inaccurate data, costs businesses billions of dollars each year. This volume presents cutting-edge research on information quality. Part I seeks to understand how data can be measured and evaluated for quality. Part II deals with the problem of ensuring quality while processing data into information a company can use. Part III presents case studies, while Part IV explores organizational issues related to information quality. Part V addresses issues in information quality education.
The only radiation therapy text written by radiation therapists, Principles and Practice of Radiation Therapy, 4th Edition helps you understand cancer management and improve clinical techniques for delivering doses of radiation. A problem-based approach makes it easy to apply principles to treatment planning and delivery. New to this edition are updates on current equipment, procedures, and treatment planning. Written by radiation therapy experts Charles Washington and Dennis Leaver, this comprehensive text will be useful throughout your radiation therapy courses and beyond. Comprehensive coverage of radiation therapy includes a clear introduction and overview plus complete information on physics, simulation, and treatment planning. Spotlights and shaded boxes identify the most important concepts. End-of-chapter questions provide a useful review. Chapter objectives, key terms, outlines, and summaries make it easier to prioritize, understand, and retain key information. Key terms are bolded and defined at first mention in the text, and included in the glossary for easy reference. UPDATED chemotherapy section, expansion of What Causes Cancer, and inclusions of additional cancer biology terms and principles provide the essential information needed for clinical success. UPDATED coverage of post-image manipulation techniques includes new material on Cone beam utilization, MR imaging, image guided therapy, and kV imaging. NEW section on radiation safety and misadministration of treatment beams addresses the most up-to-date practice requirements. Content updates also include new ASRT Practice Standards and AHA Patient Care Partnership Standards, keeping you current with practice requirements. UPDATED full-color insert is expanded to 32 pages, and displays images from newer modalities.
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
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.
This book offers a comprehensive guide to implementing a company-wide management system (CWMS), utilising up-to-date methodologies of lean-six sigma in order to achieve high levels of business excellence. It builds the foundation for quality and continuous improvement, which can be implemented in any organization. The book begins with an introduction to and an overview of CWMSs, and reviews the existing literature on various management systems. It then discusses the integration and implementation of lean-six sigma in supply chain management. The integration approach presented highlights the link between the existing management systems and shows how continuous improvement methodologies are incorporated. The book then examines the components of CWMS, comparing them to other systems. It also explores Kano-based six sigma and concludes with further recommendations for reading. This book covers five management systems integrated into one novel approach that can be followed by organizations wishing to achieve quality and business excellence. Covering lean-six sigma – an essential element of management systems – it is a valuable resource for practitioners and academics alike.
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
Introductory Business Statistics 2e aligns with the topics and objectives of the typical one-semester statistics course for business, economics, and related majors. The text provides detailed and supportive explanations and extensive step-by-step walkthroughs. The author places a significant emphasis on the development and practical application of formulas so that students have a deeper understanding of their interpretation and application of data. Problems and exercises are largely centered on business topics, though other applications are provided in order to increase relevance and showcase the critical role of statistics in a number of fields and real-world contexts. The second edition retains the organization of the original text. Based on extensive feedback from adopters and students, the revision focused on improving currency and relevance, particularly in examples and problems. This is an adaptation of Introductory Business Statistics 2e by OpenStax. You can access the textbook as pdf for free at openstax.org. Minor editorial changes were made to ensure a better ebook reading experience. Textbook content produced by OpenStax is licensed under a Creative Commons Attribution 4.0 International License.