Statistical Process Control in Automated Manufacturing


Book Description

This book provides an introduction to statistical process control in automated manufacturing and suggests implementation strategies. It focuses on time series applications in statistical process control and explores the role of knowledge-based systems in process control.




Statistical Process Control in Automated Manufacturing


Book Description

This book provides an introduction to statistical process control in automated manufacturing and suggests implementation strategies. It focuses on time series applications in statistical process control and explores the role of knowledge-based systems in process control.




Statistical Process Control for Real-World Applications


Book Description

The normal or bell curve distribution is far more common in statistics textbooks than it is in real factories, where processes follow non-normal and often highly skewed distributions. Statistical Process Control for Real-World Applications shows how to handle non-normal applications scientifically and explain the methodology to suppliers and custom




Practical Statistical Process Control


Book Description

The tools and technique used in Statistical Process Control have been used around the world to monitor and measure process variation and allow real positive changes to be made. The majority of engineers and scientists have had some exposure to this important technique but in many cases this has been badly taught and they fail to see the usefulness of it properly applied. This book has been written with the authors 30 years experience in practical Statistical Process Control and is aimed squarely at practising engineers and scientists rather than statisticians and mathematicians. Practical Statistical Process Control takes a graphical approach using a software tool called Minitab. The author concentrates on each step of using the technique with explanations along the way of each decision point. Readers will find this guide both practical and useful, with copious screenshots of the software in use and clear precise explanations. The emphasis is on understanding the technique and being able to use it in real world applications. Key points: * Provides tools and techniques for practical business and process improvement. * Introduces screenshots and explanations for each step of SPC including the importance of assessing the measurement system and constructing control charts. * A worked example, using Minitab sample data with clear explanations of the variables and analyses. This book will be extremely useful to engineers and scientists who want to solve quality, process and manufacturing problems quickly and easily.







Creating Innovation Spaces


Book Description

This book offers fresh impulses from different industries on how to deal with innovation processes. Authors from different backgrounds, such as artificial intelligence, mechanical engineering, medical technology and law, share their experiences with enabling and managing innovation. The ability of companies to innovate functions as a benchmark to attract investors long-term. While each company has different preconditions and environments to adapt to, the authors give guidance in the fields of digitalization, workspaces and business model innovation.




Introduction to Statistical Quality Control


Book Description

"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."--




Multivariate Analysis in the Pharmaceutical Industry


Book Description

Multivariate Analysis in the Pharmaceutical Industry provides industry practitioners with guidance on multivariate data methods and their applications over the lifecycle of a pharmaceutical product, from process development, to routine manufacturing, focusing on the challenges specific to each step. It includes an overview of regulatory guidance specific to the use of these methods, along with perspectives on the applications of these methods that allow for testing, monitoring and controlling products and processes. The book seeks to put multivariate analysis into a pharmaceutical context for the benefit of pharmaceutical practitioners, potential practitioners, managers and regulators. Users will find a resources that addresses an unmet need on how pharmaceutical industry professionals can extract value from data that is routinely collected on products and processes, especially as these techniques become more widely used, and ultimately, expected by regulators. - Targets pharmaceutical industry practitioners and regulatory staff by addressing industry specific challenges - Includes case studies from different pharmaceutical companies and across product lifecycle of to introduce readers to the breadth of applications - Contains information on the current regulatory framework which will shape how multivariate analysis (MVA) is used in years to come




Reinforcement Learning


Book Description

Reinforcement learning encompasses both a science of adaptive behavior of rational beings in uncertain environments and a computational methodology for finding optimal behaviors for challenging problems in control, optimization and adaptive behavior of intelligent agents. As a field, reinforcement learning has progressed tremendously in the past decade. The main goal of this book is to present an up-to-date series of survey articles on the main contemporary sub-fields of reinforcement learning. This includes surveys on partially observable environments, hierarchical task decompositions, relational knowledge representation and predictive state representations. Furthermore, topics such as transfer, evolutionary methods and continuous spaces in reinforcement learning are surveyed. In addition, several chapters review reinforcement learning methods in robotics, in games, and in computational neuroscience. In total seventeen different subfields are presented by mostly young experts in those areas, and together they truly represent a state-of-the-art of current reinforcement learning research. Marco Wiering works at the artificial intelligence department of the University of Groningen in the Netherlands. He has published extensively on various reinforcement learning topics. Martijn van Otterlo works in the cognitive artificial intelligence group at the Radboud University Nijmegen in The Netherlands. He has mainly focused on expressive knowledge representation in reinforcement learning settings.




Statistical Models and Control Charts for High-Quality Processes


Book Description

Control charts are widely used in industry to monitor processes that are far from Zero-Defect (ZD), and their use in a near Zero-Defect manufacturing environment poses many problems. This book presents techniques of using control charts for high-quality processes, and some recent findings and applications of statistical control chart techniques for ZD processes are presented. A powerful technique based on counting of the cumulative conforming (CCC) items between two nonconforming ones is discussed in detail. Extensions of the CCC chart are described, as well as applications of cumulative sum and exponentially weighted moving average techniques to CCC-related data, multivariate methods, economic design of control chart procedures, and modeling and analysis of trended but regularly adjusted processes. Many examples, charts, and procedures, are presented throughout the book, and references are provided for those interested in exploring the details. A number of questions and issues are posed for further investigations. Researchers and students may find many ideas in this book useful in their academic work, as a foundation is laid for the exploration of many further theoretical and practical issues.