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LSSx.0™ provides an integrated, unified and comprehensive approach to Lean Six Sigma as a general method for statistical problem solving. This first volume teaches the fundamentals of flow problem solving and the basic principles of Lean Management. The book is intended for students and teachers in Lean Six Sigma as well as managers who wish to go beyond the acquisition of recipes and develop their practices on a solid theoretical basis. While respecting the historical roots, spirit and "consecrated" jargon of Lean Six Sigma, the book seeks to identify, unify and formalize the underlying fundamental principles.
LSSx.0™ provides an integrated, unified and comprehensive approach to Lean Six Sigma as a general method for statistical problem solving. This second volume presents the business deployment of the approach and the generic DMAIC methodological protocol. Based on an original definition of statistical problems, it teaches the fundamentals of "discernible" statistical problems solving and the basic principles of Six Sigma. The book is intended for students and teachers in Lean Six Sigma as well as operational improvement practitioners who wish to go beyond the acquisition of recipes and develop their practices on a solid theoretical basis.
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.
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
"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"--
Six Sigma has taken the corporate world by storm and represents the thrust of numerous efforts in manufacturing and service organizations to improve products, services, and processes. Although Six Sigma brings a new direction to quality and productivity improvement, its underlying tools and philosophy are grounded in the fundamental principles of total quality and continuous improvement that have been used for many decades. Nevertheless, Six Sigma has brought a renewed interest in quality and improvement that few can argue with, and has kept alive the principles of total quality developed in the latter part of the 20th Century.
Mounting failures of replication in social and biological sciences give a new urgency to critically appraising proposed reforms. This book pulls back the cover on disagreements between experts charged with restoring integrity to science. It denies two pervasive views of the role of probability in inference: to assign degrees of belief, and to control error rates in a long run. If statistical consumers are unaware of assumptions behind rival evidence reforms, they can't scrutinize the consequences that affect them (in personalized medicine, psychology, etc.). The book sets sail with a simple tool: if little has been done to rule out flaws in inferring a claim, then it has not passed a severe test. Many methods advocated by data experts do not stand up to severe scrutiny and are in tension with successful strategies for blocking or accounting for cherry picking and selective reporting. Through a series of excursions and exhibits, the philosophy and history of inductive inference come alive. Philosophical tools are put to work to solve problems about science and pseudoscience, induction and falsification.