Statistical Quality Control

A Loss Minimization Approach

Author: Dan Trietsch

Publisher: World Scientific

ISBN: 9789810230319

Category: Technology & Engineering

Page: 385

View: 4605

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While many books on quality espouse the Taguchi loss function, they do not examine its impact on statistical quality control (SQC). But using the Taguchi loss function sheds new light on questions relating to SQC and calls for some changes. This book covers SQC in a way that conforms with the need to minimize loss. Subjects often not covered elsewhere include: (i) measurements, (ii) determining how many points to sample to obtain reliable control charts (for which purpose a new graphic tool, diffidence charts, is introduced), (iii) the connection between process capability and tolerances, (iv) how to adapt Deming's kp rule to quadratic loss, (v) how to adjust without tampering. We also discuss the efficiency of various statistics and how control chart constants are derived.
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Statistical Quality Control for the Food Industry

Author: Merton R. Hubbard

Publisher: Taylor & Francis US

ISBN: 9780306477287

Category: Mathematics

Page: 343

View: 4756

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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. Anyone involved in the production foods will find this book a valuable guide for assuring the safety and uniformity of food production through application of the latest techniques in process quality control. Specifically, this text can be used effectively by those skilled in the field for reference; by entry level technicians as a training aid; and by upper management to enhance their understanding of this highly specialized field. It can also be studied by operating and service departments to assist them in "total quality control" efforts.
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Frontiers in Statistical Quality Control 6

Author: Hans-Joachim Lenz,Peter-Theodor Wilrich

Publisher: Springer Science & Business Media

ISBN: 9783790813746

Category: Business & Economics

Page: 375

View: 3234

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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).
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Statistical quality control for manufacturing managers

Author: William Samuel Messina

Publisher: Wiley-Interscience

ISBN: N.A

Category: Technology & Engineering

Page: 331

View: 3067

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Provides the methods and tools for the manufacturing manager to improve quality, increase productivity, and enhance the competitive position of the manufacturing line. Proposes potentially controversial methods of performance appraisals, operation certification, line qualification, vendor certification, and just-in-time manufacturing. The organization of this book takes the reader logically from the basics of statistics through the fundamentals of statistical quality control, to the manufacturing applications and accompanying manufacturing strategies of statistical quality control (SQC). This book is the first written specifically for manufacturing management. Examples throughout the book demonstrate how the manufacturing manager can successfully implement SQC in the manufacturing process. Real-life manufacturing situations described illustrate situations managers are likely to find in their own line.
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Statistical Quality Control

Author: M. Jeya Chandra

Publisher: CRC Press

ISBN: 9781420038675

Category: Business & Economics

Page: 296

View: 7406

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It has recently become apparent that "quality" is quickly becoming the single most important factor for success and growth in business. Companies achieving higher quality in their products through effective quality improvement programs enjoy a significant competitive advantage. It is, therefore, essential for engineers responsible for design, development, and manufacture of products to understand the concepts and techniques of quality control. Statistical Quality Control imparts that understanding. Covering the basic steps in quality assurance and control methodologies, this unique text not only sequences, but also integrates the various techniques presented. The chapters, which include Optimum Process Means and Process Setting, are arranged in logical order. This advanced treatment makes Statistical Quality Control an ideal graduate text as well as a reference for practitioners working in design and quality control.
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Statistical Process Control For Quality Improvement

A Training Guide To Learning SPC

Author: James Evans

Publisher: Pearson Education

ISBN: 0132442019

Category: Technology & Engineering

Page: 210

View: 549

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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.
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Statistical quality control with microcomputer applications

Author: Larry E. Shirland

Publisher: John Wiley & Sons Inc

ISBN: N.A

Category: Business & Economics

Page: 395

View: 6218

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Concentrates on the technical and managerial aspects of quality, especially statistical process control (SPC). Divided into two parts, it begins with basic statistical principles and the design and use of control charts. Section Two deals with planning and applying acceptance sampling designs. Includes a significant amount of diverse data sets generated to enable students to analyze potential scenarios.
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Statistical Quality Control

A Modern Introduction

Author: Douglas C. Montgomery

Publisher: John Wiley & Sons

ISBN: 9781118322574

Category: Process control

Page: 752

View: 2237

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This Edition continues to explore the modern practice of statistical quality control, providing comprehensive coverage of the subject from basic principles to state-of-the-art concepts and applications. The objective is to give the reader a thorough grounding in the principles of statistical quality control and a basis for applying those principles in a wide variety of both product and nonproduct situations. Divided into four parts, it contains numerous changes, including a more detailed discussion of the basic SPC problem-solving tools and two new case studies, expanded treatment on variable control charts with new examples, a chapter devoted entirely to cumulative-sum control charts and exponentially-weighted, moving-average control charts, and a new section on process improvement with designed experiments.
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