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Statistical Quality Control: Strategies and Tools for Continual Improvement | 
 enlarge | Authors: Johannes Ledolter, Claude W. Burrill
Publisher: Wiley
Category: Book
Buy New: $35.00
New (17) Used (15) from $35.00
Rating:  2 reviews
Sales Rank: 1024231
Format: Student Edition
Media: Paperback
Edition: 99
Pages: 544
Number Of Items: 1
Shipping Weight (lbs): 2.1
Dimensions (in): 9.4 x 7.7 x 1
ISBN: 0471183784
Dewey Decimal Number: 658.562
EAN: 9780471183785
Publication Date: August 4, 1998
Availability: Usually ships in 1-2 business days
Shipping: Expedited shipping available
Condition: Brand New
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Product Description
This text provides the reader with a general and widely-applicable problem solving strategy for use in quality improvement. It covers a variety of statistical and "non-statistical" problem-solving tools, and discusses techniques that are useful when problems are solved by groups or teams of people. It also shows how the success of problem solving is influenced by the style of management and the type of management-employee interaction.
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| Customer Reviews:
nice introduction to methods and strategies in quality control February 15, 2008
Michael R. Chernick (Holland PA)
22 out of 22 found this review helpful
This texts assumes little mathematics and no statistical training. It is intended to teach engineering students and managers the basic tools and strategies for successful quality control and management. The authors are statisticians, so the importance of probability and statistics is emphasized and taught from first principles. Yet the first five Chapters (Section 1 of the book), does not deal with statistics at all! The authors describe quality problems and strategies for solving problems. This involves sketching the importance of data and data analysis and mentioning the various statistical tools in the context of the roles they play. Chapter 2 deals with ways of detecting quality porblems and includes flowcharting processes, the use of scorecards and Pareto diagrams. Chapter 3 deals with problem solving techniques and cause-and-effect diagrams. Chapter 4 deals with group problem solving including quality circles and the delphi technique for reaching a consensus. Section 1 concludes with the use of a rewards system to facilitate employee involvement in quality improvement.
In Section 2 basic statistical concepts are introduced as they are needed. Chapter 6 deals with ways to measure productivity and collect data. Chapter 7 covers graphical displays, descriptive statistics and probability distributions and concludes with an enumeration of Ishikawa's seven basic tools. Formal probability is introduced in Chapter 8, survey sampling in Chapter 9, statistical inference under simple random sampling in Chapter 10, acceptance sampling in Chapter 11, statistical process control in Chapter 12, process capability indices in Chapter 13 (a good introductory treatment). Section 2 is Chapters 6-11 covering the tools for data analysis. Chapters 12 and 13 are separated as Section 3 covering process stabilization and predictability. Several real projects are described at the end of Section 3. Section 4 is on design of experiments covering Chapters 14 -16. Chapters 14 and 15 deal with classical statistical designs while Chapter 16 deals with Taguchi designs that are useful for determining robust conditions and process improvement. Many useful applications are given to illustrate the techniques. Other useful statistical methods in quality control are relegated to Chapter 17. This includes regression analysis, response surface methods and model selection procedures.
This is an excellent text for a first course.
interesting introduction to quality tools and strategies December 13, 2000
Michael R. Chernick (Malvern, PA)
14 out of 14 found this review helpful
This texts assumes little mathematics and no statistical training. It is intended to teach engineering students and managers the basic tools and strategies for successful quality control and management. The authors are statisticians, so the importance of probability and statistics is emphasized and taught from first principles. Yet the first five Chapters (Section 1 of the book), does not deal with statistics at all! The authors describe quality problems and strategies for solving problems. This involves sketching the importance of data and data analysis and mentioning the various statistical tools in the context of the roles they play. Chapter 2 deals with ways of detecting quality porblems and includes flowcharting processes, the use of scorecards and Pareto diagrams. Chapter 3 deals with problem solving techniques and cause-and-effect diagrams. Chapter 4 deals with group problem solving including quality circles and the delphi technique for reaching a consensus. Section 1 concludes with the use of a rewards system to facilitate employee involvement in quality improvement.In Section 2 basic statistical concepts are introduced as they are needed. Chapter 6 deals with ways to measure productivity and collect data. Chapter 7 covers graphical displays, descriptive statistics and probability distributions and concludes with an enumeration of Ishikawa's seven basic tools. Formal probability is introduced in Chapter 8, survey sampling in Chapter 9, statistical inference under simple random sampling in Chapter 10, acceptance sampling in Chapter 11, statistical process control in Chapter 12, process capability indices in Chapter 13 (a good introductory treatment). Section 2 is Chapters 6-11 covering the tools for data analysis. Chapters 12 and 13 are separated as Section 3 covering process stabilization and predictability. Several real projects are described at the end of Section 3. Section 4 is on design of experiments covering Chapters 14 -16. Chapters 14 and 15 deal with classical statistical designs while Chapter 16 deals with Taguchi designs that are useful for determining robust conditions and process improvement. Many useful applications are given to illustrate the techniques. Other useful statistical methods in quality control are relegated to Chapter 17. This includes regression analysis, response surface methods and model selection procedures. This is an excellent text for a first course....
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