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Author: Hans-Joachim Lenz
Publisher: Springer Science & Business Media
ISBN: 3642575900
Category : Business & Economics
Languages : en
Pages : 379
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Book Description
In the 1920's, Walter Shewhart visualized that the marriage of statistical methods and manufacturing processes would produce reliable and consistent quality products. Shewhart (1931) conceived the idea of statistical process control (SPC) and developed the well-known and appropriately named Shewhart control chart. However, from the 1930s to the 1990s, literature on SPC schemes have been "captured" by the Shewhart paradigm of normality, independence and homogeneous variance. When in fact, the problems facing today's industries are more inconsistent than those faced by Shewhart in the 1930s. As a result of the advances in machine and sensor technology, process data can often be collected on-line. In this situation, the process observations that result from data collection activities will frequently not be serially independent, but autocorrelated. Autocorrelation has a significant impact on a control chart: the process may not exhibit a state of statistical control when in fact, it is in control. As the prevalence of this type of data is expected to increase in industry (Hahn 1989), so does the need to control and monitor it. Equivalently, literature has reflected this trend, and research in the area of SPC with autocorrelated data continues so that effective methods of handling correlated data are available. This type of data regularly occurs in the chemical and process industries, and is pervasive in computer-integrated manufacturing environments, clinical laboratory settings and in the majority of SPC applications across various manufacturing and service industries (Alwan 1991).
Author: Hans-Joachim Lenz
Publisher: Springer Science & Business Media
ISBN: 3642575900
Category : Business & Economics
Languages : en
Pages : 379
Get Book Here
Book Description
In the 1920's, Walter Shewhart visualized that the marriage of statistical methods and manufacturing processes would produce reliable and consistent quality products. Shewhart (1931) conceived the idea of statistical process control (SPC) and developed the well-known and appropriately named Shewhart control chart. However, from the 1930s to the 1990s, literature on SPC schemes have been "captured" by the Shewhart paradigm of normality, independence and homogeneous variance. When in fact, the problems facing today's industries are more inconsistent than those faced by Shewhart in the 1930s. As a result of the advances in machine and sensor technology, process data can often be collected on-line. In this situation, the process observations that result from data collection activities will frequently not be serially independent, but autocorrelated. Autocorrelation has a significant impact on a control chart: the process may not exhibit a state of statistical control when in fact, it is in control. As the prevalence of this type of data is expected to increase in industry (Hahn 1989), so does the need to control and monitor it. Equivalently, literature has reflected this trend, and research in the area of SPC with autocorrelated data continues so that effective methods of handling correlated data are available. This type of data regularly occurs in the chemical and process industries, and is pervasive in computer-integrated manufacturing environments, clinical laboratory settings and in the majority of SPC applications across various manufacturing and service industries (Alwan 1991).
Author: Hans-Joachim Lenz
Publisher: Springer Science & Business Media
ISBN: 3790816876
Category : Mathematics
Languages : en
Pages : 359
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Book Description
In Canada, acceptance sampling has been used in legal metrology applications for nearly four decades. One of its principal uses has been in the quality control of utility meters that measure electricity or natural gas supplied to consumers. By law, such meters must be inspected for conformance to specification requirements prior to use and be periodically inspected while huse. With few exceptions, due to the numerous utility companies in the country and their varied practices, the meters exist in the form of isolated lots for inspection purposes. The proportion of nonconforming meters in a lot has traditionally defined lot quality for utility meter sampling inspection purposes. Another principal application of acceptance sampling has been in the quality control of the net contents of packaged products sold in the marketplace. Such products include those sold on the basis of such measures as weight, volume, length, and area. In this particular application, products are also usually inspected on an isolated-lot basis for regulatory purposes. However, lot quality is usually measured on the basis of two criteria for such products: the proportion of nonc- forming packages in the lot and the lot mean quantity. This section reviews Canadian quality control practices in these two areas of application, highlighting some of the deficiencies and issues. Three-class s- pling plans are proposed as a possible solution to some of these deficiencies and issues.
Author: Hans-Joachim Lenz
Publisher: Springer Science & Business Media
ISBN: 379082674X
Category : Business & Economics
Languages : en
Pages : 363
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Book Description
This volume treats the four main categories of Statistical Quality Control: General SQC Methodology, On-line Control including Sampling Inspection and Statistical Process Control, Off-line Control with Data Analysis and Experimental Design, and, fields related to Reliability. Experts with international reputation present their newest contributions.
Author: Sven Knoth
Publisher: Springer
ISBN: 3319123556
Category : Computers
Languages : en
Pages : 398
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Book Description
The main focus of this edited volume is on three major areas of statistical quality control: statistical process control (SPC), acceptance sampling and design of experiments. The majority of the papers deal with statistical process control, while acceptance sampling and design of experiments are also treated to a lesser extent. The book is organized into four thematic parts, with Part I addressing statistical process control. Part II is devoted to acceptance sampling. Part III covers the design of experiments, while Part IV discusses related fields. The twenty-three papers in this volume stem from The 11th International Workshop on Intelligent Statistical Quality Control, which was held in Sydney, Australia from August 20 to August 23, 2013. The event was hosted by Professor Ross Sparks, CSIRO Mathematics, Informatics and Statistics, North Ryde, Australia and was jointly organized by Professors S. Knoth, W. Schmid and Ross Sparks. The papers presented here were carefully selected and reviewed by the scientific program committee, before being revised and adapted for this volume.
Author: Sven Knoth
Publisher: Springer Nature
ISBN: 3030678563
Category : Mathematics
Languages : en
Pages : 410
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Book Description
This contributed book focuses on major aspects of statistical quality control, shares insights into important new developments in the field, and adapts established statistical quality control methods for use in e.g. big data, network analysis and medical applications. The content is divided into two parts, the first of which mainly addresses statistical process control, also known as statistical process monitoring. In turn, the second part explores selected topics in statistical quality control, including measurement uncertainty analysis and data quality. The peer-reviewed contributions gathered here were originally presented at the 13th International Workshop on Intelligent Statistical Quality Control, ISQC 2019, held in Hong Kong on August 12-14, 2019. Taken together, they bridge the gap between theory and practice, making the book of interest to both practitioners and researchers in the field of statistical quality control.
Author: Hans-Joachim Lenz
Publisher: Springer Science & Business Media
ISBN: 3790823805
Category : Mathematics
Languages : en
Pages : 367
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Book Description
The twenty-three papers in this volume are carefully selected, reviewed and revised for this volume, and are divided into two parts: Part 1: "On-line Control" with subchapters 1.1 "Control Charts" and 1.2 "Surveillance Sampling and Sampling Plans" and Part 2:"Off-line Control".
Author: Hans-Joachim Lenz
Publisher: Springer Science & Business Media
ISBN: 3642592392
Category : Business & Economics
Languages : en
Pages : 301
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Book Description
Like the preceding volumes, and met with a lively response, the present volume is collecting contributions stressed on methodology or successful industrial applications. The papers are classified under four main headings: sampling inspection, process quality control, data analysis and process capability studies and finally experimental design.
Author: Sven Knoth
Publisher: Springer Nature
ISBN: 3031691113
Category :
Languages : en
Pages : 503
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Book Description
Author: Muhammad Aslam
Publisher: John Wiley & Sons
ISBN: 1119528453
Category : Mathematics
Languages : en
Pages : 288
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Book Description
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.
Author: P. Ciarlini
Publisher: World Scientific
ISBN: 9812566740
Category : Computers
Languages : en
Pages : 386
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Book Description
This volume collects the refereed contributions based on the presentations made at the Seventh Workshop on Advanced Mathematical and Computational Tools in Metrology, a forum for metrologists, mathematicians and software engineers that will encourage a more effective synthesis of skills, capabilities and resources. The volume contains articles by world renowned metrologists and mathematicians involved in measurement science and, together with the six previous volumes in this series, constitutes an authoritative source of the mathematical, statistical and software tools necessary in modern metrology. Contents: Modeling Measurement Processes in Complex Systems with Partial Differential Equations: From Heat Conduction to the Heart (M Baer et al.); Mereotipological Approach for Measurement Software (E Benoit & R Dapoigny); Data Evaluation of Key Comparisons Involving Several Artefacts (M G Cox et al.); Box-Cox Transformations Versus Robust Control Charts in Statistical Process Control (M I Gomes & F O Figueiredo); Decision Making Using Sensor's Data Fusion and Kohonen Self Organizing Maps (P S Girao et al.); Generic System Design for Measurement Databases Applied to Calibrations in Vacuum Metrology, Bio-Signals and a Template System (H Gro et al.); Repeated Measurements: Evaluation of Their Uncertainty from the Viewpoints of Classical and Bayesian Statistics (I Lira & W Woger); Detection of Outliers in Interlaboratory Testing and Some Thoughts About Multivariate Precision (C Perruchet); On Appropriate Methods for the Validation of Metrological Software (D Richter et al.); Data Analysis-A Dialogue (D S Sivia); Validation of a Virtual Sensor for Monitoring Ambient Parameters (P Ciarlini et al.); Evaluation of Standard Uncertainties in Nested Structures (E Filipe); Linking GUM and ISO 5725 (A B Forbes); Monte Carlo Study on Logical and Statistical Correlation (B Siebert et al.); Some Problems Concerning the Estimate of the Uncertainty of the Degree of Equivalence in MRA Key Comparisons (F Pavese); Preparing for a European Research Area Network in Metrology: Where are We Now? (M Kuhne et al.); and other papers. Readership: Researchers, graduate students, academics and professionals in metrology.
