Quality Control with R

Quality Control with R
Author: Emilio L. Cano
Publisher: Springer
Total Pages: 373
Release: 2015-11-20
Genre: Business & Economics
ISBN: 3319240463

Presenting a practitioner's guide to capabilities and best practices of quality control systems using the R programming language, this volume emphasizes accessibility and ease-of-use through detailed explanations of R code as well as standard statistical methodologies. In the interest of reaching the widest possible audience of quality-control professionals and statisticians, examples throughout are structured to simplify complex equations and data structures, and to demonstrate their applications to quality control processes, such as ISO standards. The volume balances its treatment of key aspects of quality control, statistics, and programming in R, making the text accessible to beginners and expert quality control professionals alike. Several appendices serve as useful references for ISO standards and common tasks performed while applying quality control with R.

Statistical Quality Control

Statistical Quality Control
Author: Bhisham C. Gupta
Publisher: John Wiley & Sons
Total Pages: 400
Release: 2021-07-23
Genre: Technology & Engineering
ISBN: 1119671728

STATISTICAL QUALITY CONTROL Provides a basic understanding of statistical quality control (SQC) and demonstrates how to apply the techniques of SQC to improve the quality of products in various sectors This book introduces Statistical Quality Control and the elements of Six Sigma Methodology, illustrating the widespread applications that both have for a multitude of areas, including manufacturing, finance, transportation, and more. It places emphasis on both the theory and application of various SQC techniques and offers a large number of examples using data encountered in real life situations to support each theoretical concept. Statistical Quality Control: Using MINITAB, R, JMP and Python begins with a brief discussion of the different types of data encountered in various fields of statistical applications and introduces graphical and numerical tools needed to conduct preliminary analysis of the data. It then discusses the basic concept of statistical quality control (SQC) and Six Sigma Methodology and examines the different types of sampling methods encountered when sampling schemes are used to study certain populations. The book also covers Phase 1 Control Charts for variables and attributes; Phase II Control Charts to detect small shifts; the various types of Process Capability Indices (CPI); certain aspects of Measurement System Analysis (MSA); various aspects of PRE-control; and more. This helpful guide also Focuses on the learning and understanding of statistical quality control for second and third year undergraduates and practitioners in the field Discusses aspects of Six Sigma Methodology Teaches readers to use MINITAB, R, JMP and Python to create and analyze charts Requires no previous knowledge of statistical theory Is supplemented by an instructor-only book companion site featuring data sets and a solutions manual to all problems, as well as a student book companion site that includes data sets and a solutions manual to all odd-numbered problems Statistical Quality Control: Using MINITAB, R, JMP and Python is an excellent book for students studying engineering, statistics, management studies, and other related fields and who are interested in learning various techniques of statistical quality control. It also serves as a desk reference for practitioners who work to improve quality in various sectors, such as manufacturing, service, transportation, medical, oil, and financial institutions. It‘s also useful for those who use Six Sigma techniques to improve the quality of products in such areas.

Multivariate Statistical Quality Control Using R

Multivariate Statistical Quality Control Using R
Author: Edgar Santos-Fernández
Publisher: Springer Science & Business Media
Total Pages: 134
Release: 2012-09-22
Genre: Business & Economics
ISBN: 1461454522

​​​​​The intensive use of automatic data acquisition system and the use of cloud computing for process monitoring have led to an increased occurrence of industrial processes that utilize statistical process control and capability analysis. These analyses are performed almost exclusively with multivariate methodologies. The aim of this Brief is to present the most important MSQC techniques developed in R language. The book is divided into two parts. The first part contains the basic R elements, an introduction to statistical procedures, and the main aspects related to Statistical Quality Control (SQC). The second part covers the construction of multivariate control charts, the calculation of Multivariate Capability Indices.

Modern Statistical Quality Control and Improvement

Modern Statistical Quality Control and Improvement
Author: Nicholas R. Farnum
Publisher: Duxbury Resource Center
Total Pages: 522
Release: 1994
Genre: Business & Economics
ISBN:

Farnum's text takes a state-of-the-art approach to quality management. From the outset, it emphasizes the modern philosophy of continuous quality improvement and quality control. It is written for courses where both modern statistical methods for quality and their implementation into business are covered. In straightforward terms, the book explains the concepts and techniques that are essential to quality control, including cutting-edge topics.

Six Sigma with R

Six Sigma with R
Author: Emilio L. Cano
Publisher: Springer Science & Business Media
Total Pages: 296
Release: 2012-07-04
Genre: Mathematics
ISBN: 1461436524

Six Sigma has arisen in the last two decades as a breakthrough Quality Management Methodology. With Six Sigma, we are solving problems and improving processes using as a basis one of the most powerful tools of human development: the scientific method. For the analysis of data, Six Sigma requires the use of statistical software, being R an Open Source option that fulfills this requirement. R is a software system that includes a programming language widely used in academic and research departments. Nowadays, it is becoming a real alternative within corporate environments. The aim of this book is to show how R can be used as the software tool in the development of Six Sigma projects. The book includes a gentle introduction to Six Sigma and a variety of examples showing how to use R within real situations. It has been conceived as a self contained piece. Therefore, it is addressed not only to Six Sigma practitioners, but also to professionals trying to initiate themselves in this management methodology. The book may be used as a text book as well.

Statistical Quality Control for the Food Industry

Statistical Quality Control for the Food Industry
Author: Merton R. Hubbard
Publisher: Springer Science & Business Media
Total Pages: 347
Release: 2012-12-06
Genre: Technology & Engineering
ISBN: 1461501490

Specifically targeted at the food industry, this state-of-the-art text/reference combines all the principal methods of statistical quality and process control into a single, up-to-date volume. In an easily understood and highly readable style, the author clearly explains underlying concepts and uses real world examples to illustrate statistical techniques. This Third Edition maintains the strengths of the first and second editions while adding new information on Total Quality Management, Computer Integrated Management, ISO 9001-2002, and The Malcolm Baldrige Quality Award. There are updates on FDA Regulations and Net Weight control limits, as well as additional HACCP applications. A new chapter has been added to explain concepts and implementation of the six-sigma quality control system.

Process Quality Control

Process Quality Control
Author: Ellis Raymond Ott
Publisher: McGraw-Hill Companies
Total Pages: 504
Release: 1990
Genre: Computers
ISBN:

Introduction to Statistical Quality Control

Introduction to Statistical Quality Control
Author: Douglas C. Montgomery
Publisher: John Wiley & Sons
Total Pages: 772
Release:
Genre: Process control
ISBN: 1119657075

"This book is about the use of modern statistical methods for quality control and improvement. It provides comprehensive coverage of the subject from basic principles to state-of-the-art concepts. and applications. The objective is to give the reader a sound understanding of the principles and the basis for applying them in a variety of situations. Although statistical techniques are emphasized. throughout, the book has a strong engineering and management orientation. Extensive knowledge. of statistics is not a prerequisite for using this book. Readers whose background includes a basic course in statistical methods will find much of the material in this book easily accessible"--