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.

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.

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

Design and manufacturing is the essential element in any product development lifecycle. Industry vendors and users have been seeking a common language to be used for the entire product development lifecycle that can describe design, manufacturing and other data pertaining to the product. Many solutions were proposed, the most successful being the Stadndard for Exchange of Product model (STEP). STEP provides a mechanism that is capable of describing product data, independent from any particular system. The nature of this description makes it suitable not only for neutral file exchange, but also as a basis for implementing, sharing and archiving product databases. ISO 10303-AP203 is the first and perhaps the most successful AP developed to exchange design data between different CAD systems. Going from geometric data (as in AP203) to features (as in AP224) represents an important step towards having the right type of data in a STEP-based CAD/CAM system. Of particular significance is the publication of STEP-NC, as an extension of STEP to NC, utilising feature-based concepts for CNC machining purposes. The aim of this book is to provide a snapshot of the recent research outcomes and implementation cases in the field of design and manufacturing where STEP is used as the primary data representation protocol. The 20 chapters are contributed by authors from most of the top research teams in the world. These research teams are based in national research institutes, industries as well as universities.

This guide aims to strip away the mystery surrounding statistical process control and to present its concepts and principles in as simple and straightforward a manner as possible. It is directed primarily at American business managers.

This book introduces the latest research on advanced control charts and new machine learning approaches to detect abnormalities in the smart manufacturing process. By approaching anomaly detection using both statistics and machine learning, the book promotes interdisciplinary cooperation between the research communities, to jointly develop new anomaly detection approaches that are more suitable for the 4.0 Industrial Revolution. The book provides ready-to-use algorithms and parameter sheets, enabling readers to design advanced control charts and machine learning-based approaches for anomaly detection in manufacturing. Case studies are introduced in each chapter to help practitioners easily apply these tools to real-world manufacturing processes. The book is of interest to researchers, industrial experts, and postgraduate students in the fields of industrial engineering, automation, statistical learning, and manufacturing industries.

The book is a collection of papers presented at the 5th International Workshop on Intelligent Statistical Quality Control in Würzburg, Germany. Contributions deal with methodology and successful industrial applications. They can be grouped in four catagories: Sampling Inspection, Statistical Process Control, Data Analysis and Process Capability Studies and Experimental Design.

This work presents significant advances and new methods both in statistical process control and experimental design. It addresses the management of process monitoring and experimental design, discusses the relationship between control charting and hypothesis testing, provides a new index for process capability studies, offers practical guidelines for the design of experiments, and more.

Looks at quality management in a new way; Offers a very different mathematical tool set than traditionally employed for quality control problems; Yao is a leading researcher in the area of stochastic modeling and the author of a previous Springer book

The work contains the results of the Sixth International Conference on Advanced Manufacturing Systems and Technology – AMST’02, which was held in Udine in June 2002. It presents up-to-date information on the latest developments – research results and experience – in the field of machining of conventional and advanced materials, machine tools and flexible manufacturing systems, forming, nonconventional processes, robotics, measurement and control, quality, design and ecodesign, rapid prototyping, rapid tooling and manufacturing, materials and mechanics.