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The Quality Toolbox is a comprehensive reference to a variety of methods and techniques: those most commonly used for quality improvement, many less commonly used, and some created by the author and not available elsewhere. The reader will find the widely used seven basic quality control tools (for example, fishbone diagram, and Pareto chart) as well as the newer management and planning tools. Tools are included for generating and organizing ideas, evaluating ideas, analyzing processes, determining root causes, planning, and basic data-handling and statistics. The book is written and organized to be as simple as possible to use so that anyone can find and learn new tools without a teacher. A...
This book provides tools that are less commonly used and some tools that the author, Nancy Tague, created. Inside you’ll find tools for generating and organizing ideas, evaluating ideas, analyzing processes, determining root causes, planning, basic data handling, and statistics. In this third edition, six new tools were added (i.e., DFMEA and PMFEA) along with a section on Quality 4.0 and suggested quality tools that can help facilitate practitioners looking to implement Quality 4.0 concepts. The use of icons with each tool description tells the reader at a glance what kind of tool it is and where it is used within the improvement process.
Established by Congress in 1901, the National Bureau of Standards (NBS), now the National Institute of Standards and Technology (NIST), has a long and distinguished history as the custodian and disseminator of the United States' standards of physical measurement. Having reached its centennial anniversary, the NBS/NIST reflects on and celebrates its first century with this book describing some of its seminal contributions to science and technology. Within these pages are 102 vignettes that describe some of the Institute's classic publications. Each vignette relates the context in which the publication appeared, its impact on science, technology, and the general public, and brief details about...
This book aims to achieve the following goals: (1) to provide a high-level survey of key analytics models and algorithms without going into mathematical details; (2) to analyze the usage patterns of these models; and (3) to discuss opportunities for accelerating analytics workloads using software, hardware, and system approaches. The book first describes 14 key analytics models (exemplars) that span data mining, machine learning, and data management domains. For each analytics exemplar, we summarize its computational and runtime patterns and apply the information to evaluate parallelization and acceleration alternatives for that exemplar. Using case studies from important application domains...