Statistical Methods for Industrial Process Control

Statistical Methods for Industrial Process Control PDF

Author: David .C. Drain

Publisher: CRC Press

Published: 1997-02-01

Total Pages: 476

ISBN-13: 9780412085116

DOWNLOAD EBOOK →

To practice engineering effectively, engineers must need to have a working knowledge of statistical concepts and methods. What they do not need is a background heavy on statistical theory and number crunching. Statistical Methods for Industrial Process Control provides the practical statistics foundation engineers can immediately apply to the work they do every day, regardless of their industry or specialty. The author illustrates statistical concepts and methods with authentic semiconductor manufacturing process examples-integrated circuit fabrication is an exceedingly rich medium for communicating statistical concepts. However, once learned, these concepts and methods can easily be extended and applied to a variety of other industries. The text emphasizes the application of statistical tools, rather than statistical theory. Modern advances in statistical software have made tedious computations and formula memorization unnecessary. Therefore, the author demonstrates software use throughout the book and supplies MINITAB examples and SAS programs. Review problems at the end of each chapter challenge and deepen readers' understanding of the material. Statistical Methods for Industrial Process Control addresses topics that support the work engineers do, rather than educate them as statisticians, and these topics also reflect modern usage. It effectively introduces novice engineers to a fascinating industry and enables experienced engineers to build upon their existing knowledge and learn new skills.

Statistical Process Control in Automated Manufacturing

Statistical Process Control in Automated Manufacturing PDF

Author: Bert Keats

Publisher: CRC Press

Published: 2020-11-26

Total Pages: 317

ISBN-13: 1000147150

DOWNLOAD EBOOK →

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.

Multivariate Statistical Process Control with Industrial Applications

Multivariate Statistical Process Control with Industrial Applications PDF

Author: Robert L. Mason

Publisher: SIAM

Published: 2002-01-01

Total Pages: 271

ISBN-13: 0898714966

DOWNLOAD EBOOK →

Detailed coverage of the practical aspects of multivariate statistical process control (MVSPC) based on the application of Hotelling's T2 statistic. MVSPC is the application of multivariate statistical techniques to improve the quality and productivity of an industrial process. Provides valuable insight into the T2 statistic.

Introduction to Statistical Process Control

Introduction to Statistical Process Control PDF

Author: Peihua Qiu

Publisher: CRC Press

Published: 2013-10-14

Total Pages: 520

ISBN-13: 1482220415

DOWNLOAD EBOOK →

A major tool for quality control and management, statistical process control (SPC) monitors sequential processes, such as production lines and Internet traffic, to ensure that they work stably and satisfactorily. Along with covering traditional methods, Introduction to Statistical Process Control describes many recent SPC methods that improve upon

Multivariate Statistical Process Control

Multivariate Statistical Process Control PDF

Author: Zhiqiang Ge

Publisher: Springer Science & Business Media

Published: 2012-11-28

Total Pages: 204

ISBN-13: 1447145135

DOWNLOAD EBOOK →

Given their key position in the process control industry, process monitoring techniques have been extensively investigated by industrial practitioners and academic control researchers. Multivariate statistical process control (MSPC) is one of the most popular data-based methods for process monitoring and is widely used in various industrial areas. Effective routines for process monitoring can help operators run industrial processes efficiently at the same time as maintaining high product quality. Multivariate Statistical Process Control reviews the developments and improvements that have been made to MSPC over the last decade, and goes on to propose a series of new MSPC-based approaches for complex process monitoring. These new methods are demonstrated in several case studies from the chemical, biological, and semiconductor industrial areas. Control and process engineers, and academic researchers in the process monitoring, process control and fault detection and isolation (FDI) disciplines will be interested in this book. It can also be used to provide supplementary material and industrial insight for graduate and advanced undergraduate students, and graduate engineers. Advances in Industrial Control aims to report and encourage the transfer of technology in control engineering. The rapid development of control technology has an impact on all areas of the control discipline. The series offers an opportunity for researchers to present an extended exposition of new work in all aspects of industrial control.

Statistical Process Control in Industry

Statistical Process Control in Industry PDF

Author: R.J. Does

Publisher: Springer Science & Business

Published: 1999-01-31

Total Pages: 266

ISBN-13: 9780792355700

DOWNLOAD EBOOK →

During the past decade interest in quality management has greatly increased. One of the central elements of Total Quality Management is Statistical Process Control, more commonly known as SPC. This book describes the pitfalls and traps which businesses encounter when implementing and assuring SPC. Illustrations are given from practical experience in various companies. The following subjects are discussed: implementation of SPC, activity plan for achieving statistically controlled processes, statistical tools, and lastly, consolidation and improvement of the results. Also, an extensive checklist is provided with which a business can determine to what extent it has succeeded in the actual application of SPC. Audience: This volume is written for companies which are going to implement SPC, or which need a new impetus in order to get SPC properly off the ground. It will be of interest in particular to researchers whose work involves statistics and probability, production, operation and manufacturing management, industrial organisation and mathematical and quantitative methods. It will also appeal to specialists in engineering and management, for example in the electronic industry, discrete parts industry, process industry, automotive and aircraft industry and food industry.

Statistical Case Studies for Industrial Process Improvement

Statistical Case Studies for Industrial Process Improvement PDF

Author: Veronica Czitrom

Publisher: SIAM

Published: 1997-01-01

Total Pages: 541

ISBN-13: 9780898719765

DOWNLOAD EBOOK →

This book contains a broad selection of case studies written by professionals in the semiconductor industry that illustrate the use of statistical methods to improve manufacturing processes. These case studies offer engineers, scientists, technicians, and managers numerous examples of best-in-class practices by their peers. Because of the universal nature of statistical applications, the methods described here can be applied to a wide range of industries, including the chemical, biotechnology, automotive, steel, plastics, textile, and food industries. Many industries already benefit from the use of statistical methods, although the semiconductor industry is considered both a leader in and a model for the wide application and effective use of statistics.

Statistics for Process Control Engineers

Statistics for Process Control Engineers PDF

Author: Myke King

Publisher: John Wiley & Sons

Published: 2017-08-10

Total Pages: 917

ISBN-13: 1119383528

DOWNLOAD EBOOK →

The first statistics guide focussing on practical application to process control design and maintenance Statistics for Process Control Engineers is the only guide to statistics written by and for process control professionals. It takes a wholly practical approach to the subject. Statistics are applied throughout the life of a process control scheme – from assessing its economic benefit, designing inferential properties, identifying dynamic models, monitoring performance and diagnosing faults. This book addresses all of these areas and more. The book begins with an overview of various statistical applications in the field of process control, followed by discussions of data characteristics, probability functions, data presentation, sample size, significance testing and commonly used mathematical functions. It then shows how to select and fit a distribution to data, before moving on to the application of regression analysis and data reconciliation. The book is extensively illustrated throughout with line drawings, tables and equations, and features numerous worked examples. In addition, two appendices include the data used in the examples and an exhaustive catalogue of statistical distributions. The data and a simple-to-use software tool are available for download. The reader can thus reproduce all of the examples and then extend the same statistical techniques to real problems. Takes a back-to-basics approach with a focus on techniques that have immediate, practical, problem-solving applications for practicing engineers, as well as engineering students Shows how to avoid the many common errors made by the industry in applying statistics to process control Describes not only the well-known statistical distributions but also demonstrates the advantages of applying the large number that are less well-known Inspires engineers to identify new applications of statistical techniques to the design and support of control schemes Provides a deeper understanding of services and products which control engineers are often tasked with assessing This book is a valuable professional resource for engineers working in the global process industry and engineering companies, as well as students of engineering. It will be of great interest to those in the oil and gas, chemical, pulp and paper, water purification, pharmaceuticals and power generation industries, as well as for design engineers, instrument engineers and process technical support.