Statistical Methods for Industrial Process Control

Statistical Methods for Industrial Process Control
Author: David .C. Drain
Publisher: CRC Press
Total Pages: 476
Release: 1997-02-01
Genre: Mathematics
ISBN: 9780412085116

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.

Multivariate Statistical Process Control with Industrial Applications

Multivariate Statistical Process Control with Industrial Applications
Author: Robert L. Mason
Publisher: SIAM
Total Pages: 276
Release: 2002-01-01
Genre: Technology & Engineering
ISBN: 9780898718461

This applied, self-contained text provides 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. The authors, leading researchers in this area who have developed major software for this type of charting procedure, provide valuable insight into the T2 statistic. Intentionally including only a minimal amount of theory, they lead readers through the construction and monitoring phases of the T2 control statistic using numerous industrial examples taken primarily from the chemical and power industries. These examples are applied to the construction of historical data sets to serve as a point of reference for the control procedure and are also applied to the monitoring phase, where emphasis is placed on signal location and interpretation in terms of the process variables.

Introduction to Statistical Process Control

Introduction to Statistical Process Control
Author: Peihua Qiu
Publisher: CRC Press
Total Pages: 520
Release: 2013-10-14
Genre: Business & Economics
ISBN: 1482220415

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

Statistical Case Studies for Industrial Process Improvement

Statistical Case Studies for Industrial Process Improvement
Author: Veronica Czitrom
Publisher: SIAM
Total Pages: 541
Release: 1997-01-01
Genre: Technology & Engineering
ISBN: 9780898719765

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
Author: Myke King
Publisher: John Wiley & Sons
Total Pages: 917
Release: 2017-08-10
Genre: Technology & Engineering
ISBN: 1119383528

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.

Introduction to Statistical Process Control

Introduction to Statistical Process Control
Author: Muhammad Aslam
Publisher: John Wiley & Sons
Total Pages: 288
Release: 2020-08-25
Genre: Mathematics
ISBN: 1119528437

An Introduction to the Fundamentals and History of Control Charts, Applications, and Guidelines for Implementation Introduction to Statistical Process Control examines various types of control charts that are typically used by engineering students and practitioners. This book helps readers develop a better understanding of the history, implementation, and use-cases. Students are presented with varying control chart techniques, information, and roadmaps to ensure their control charts are operating efficiently and producing specification-confirming products. This is the essential text on the theories and applications behind statistical methods and control procedures. This eight-chapter reference breaks information down into digestible sections and covers topics including: ● An introduction to the basics as well as a background of control charts ● Widely used and newly researched attributes of control charts, including guidelines for implementation ● The process capability index for both normal and non-normal distribution via the sampling of multiple dependent states ● An overview of attribute control charts based on memory statistics ● The development of control charts using EQMA statistics For a solid understanding of control methodologies and the basics of quality assurance, Introduction to Statistical Process Control is a definitive reference designed to be read by practitioners and students alike. It is an essential textbook for those who want to explore quality control and systems design.

Statistical Process Control For Quality Improvement

Statistical Process Control For Quality Improvement
Author: James Evans
Publisher: Pearson Education
Total Pages: 231
Release: 1991-03-29
Genre: Technology & Engineering
ISBN: 0132442019

With today's growing emphasis on quality improvement, training individuals in fundamental quality control skills is a major challenge. Professionals in manufacturing industries need to bring processes into statistical control – and maintain them. This book is designed to help readers learn the statistical tools and concepts needed to develop and use quality control effectively.

Multivariate Statistical Process Control

Multivariate Statistical Process Control
Author: Zhiqiang Ge
Publisher: Springer Science & Business Media
Total Pages: 204
Release: 2012-11-28
Genre: Technology & Engineering
ISBN: 1447145135

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.