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Here is a chapter from Design for Six Sigma Statistics, written by a Six Sigma practitioner with more than two decades of DFSS experience who provides a detailed, goal-focused roadmap. It shows you how to execute advanced mathematical procedures specifically aimed at implementing, fine-tuning, or maximizing DFSS projects to yield optimal results. For virtually every instance and situation, you are shown how to select and use appropriate mathematical methods to meet the challenges of today's engineering design for quality.
More than an introduction to statistical concepts and methods; this comprehensive resource provides sophisticated Six Sigma practitioners with the statistical tools necessary for rooting out and solving problems associated with product or service design. --
This book contains precise descriptions of all of the many related six sigma methods. It also includes many case studies that detail how these methods have been applied in engineering and business to achieve millions of dollars of savings. This book will help readers to determine exactly which methods to apply in which situations and to predict how and when the methods might not be effective. Illustrative examples are provided for all the methods presented and exercises based on the case studies help build associations between techniques and industrial problems.
Here is a chapter from an updated Design for Six Sigma, Second Edition, which has extensive new chapters and learning modules on innovation, lean product development, computer simulation, and critical parameter management--plus new thread-through case studies. This updated edition provides unrivalled real-world product development experience and priceless walk-throughs that help you choose the right design tools at every stage of product and service development. The book includes detailed directions, careful comparisons, and work-out calculations that make every step of the Design for Six Sigma process easier.
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 addresses many new topical areas for the development of 6 Sigma performance. The text is structured to demonstrate how 6 Sigma methods can be used as a very powerful tool within System Engineering and integration evaluations to help enable the process of Critical Parameter Management. The case studies and examples used throughout the book come from recent successful applications of the material developed in the text.
Six Sigma for Medical Device Design is the first book to apply Six Sigma principles to the design of medical devices. Authored by experienced professionals, it uses real world examples and sample plans to provide a practical how-to guide for implementation. This volume also links the Six Sigma philosophy with the FDA's Design Control and ISO regulations, useful for companies that must be compliant as well as for those in the process of implementing a quality system for design control. This book is an excellent tool for technical and scientific personnel to understand the realities of business and markets, to comply with stringent quality and safety standards, and to optimize the product realization process.
This book focuses on the basics of the six sigma methodology. It targets on both manufacturing as well as non-manufacturing organizations and demystifies the Six Sigma methodology. The book addresses the concepts of the Six Sigma philosophy and explains the methodologies involved in it.
"Once solely the domain of engineers, quality control has become a vital business operation used to increase productivity and secure competitive advantage. Introduction to Statistical Quality Control offers a detailed presentation of the modern statistical methods for quality control and improvement. Thorough coverage of statistical process control (SPC) demonstrates the efficacy of statistically-oriented experiments in the context of process characterization, optimization, and acceptance sampling, while examination of the implementation process provides context to real-world applications. Emphasis on Six Sigma DMAIC (Define, Measure, Analyze, Improve and Control) provides a strategic problem-solving framework that can be applied across a variety of disciplines.Adopting a balanced approach to traditional and modern methods, this text includes coverage of SQC techniques in both industrial and non-manufacturing settings, providing fundamental knowledge to students of engineering, statistics, business, and management sciences.A strong pedagogical toolset, including multiple practice problems, real-world data sets and examples, provides students with a solid base of conceptual and practical knowledge."--
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.