Introduction to Statistical Quality Control

ISBN-10: 1118146816
ISBN-13: 9781118146811
Edition: 7th 2013
List price: $215.95 Buy it from $133.65
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Book details

List price: $215.95
Edition: 7th
Copyright year: 2013
Publisher: John Wiley & Sons, Incorporated
Publication date: 6/19/2012
Binding: Hardcover
Pages: 768
Size: 8.50" wide x 10.50" long x 1.25" tall
Weight: 3.190
Language: English

Introduction
Quality Improvement in the Modern Business Environment
Chapter Overview and Learning Objectives
The Meaning of Quality and Quality Improvement
Dimensions of Quality
Quality Engineering Terminology
A Brief History of Quality Control and Improvement
Statistical Methods for Quality Control and Improvement
Management Aspects of Quality Improvement
Quality Philosophy and Management Strategies
The Link Between Quality and Productivity
Supply Chain Quality Management
Quality Costs
Legal Aspects of Quality
Implementing Quality Improvement
The Dmaic Process
Chapter Overview and Learning Objectives
Overview of DMAIC
The Define Step
The Measure Step
The Analyze Step
The Improve Step
The Control Step
Examples of DMAIC
Litigation Documents
Improving On-Time Delivery
Improving Service Quality in a Bank
Statistical Methods Useful in Quality Control and Improvement
Modeling Process Quality
Chapter Overview and Learning Objectives
Describing Variation
The Stem-and-Leaf Plot
The Histogram
Numerical Summary of Data
The Box Plot
Probability Distributions
Important Discrete Distributions
The Hypergeometric Distribution
The Binomial Distribution
The Poisson Distribution
The Negative Binomial and Geometric Distributions
Important Continuous Distributions
The Normal Distribution
The Lognormal Distribution
The Exponential Distribution
The Gamma Distribution
The Weibull Distribution
Probability Plots
Normal Probability Plots
Other Probability Plots
Some Useful Approximations
The Binomial Approximation to the Hypergeometric
The Poisson Approximation to the Binomial
The Normal Approximation to the Binomial
Comments on Approximations
Inferences About Process Quality
Chapter Overview and Learning Objectives
Statistics and Sampling Distributions
Sampling from a Normal Distribution
Sampling from a Bernoulli Distribution
Sampling from a Poisson Distribution
Point Estimation of Process Parameters
Statistical Inference for a Single Sample
Inference on the Mean of a Population, Variance Known
The Use of P-Values for Hypothesis Testing
Inference on the Mean of a Normal Distribution, Variance Unknown
Inference on the Variance of a Normal Distribution
Inference on a Population Proportion
The Probability of Type II Error and Sample Size Decisions
Statistical Inference for Two Samples
Inference for a Difference in Means, Variances Known
Inference for a Difference in Means of Two Normal Distributions, Variances Unknown
Inference on the Variances of Two Normal Distributions
Inference on Two Population Proportions
What If There Are More Than Two Populations? The Analysis of Variance
An Example
The Analysis of Variance
Checking Assumptions: Residual Analysis
Linear Regression Models
Estimation of the Parameters in Linear Regression Models
Hypothesis Testing in Multiple Regression
Confidance Intervals in Multiple Regression
Prediction of New Observations
Regression Model Diagnostics
Basic Methods of Statistical Process Control and Capability Analysis
Methods and Philosophy of Statistical Process Control
Chapter Overview and Learning Objectives
Introduction
Chance and Assignable Causes of Quality Variation
Statistical Basis of the Control Chart
Basic Principles
Choice of Control Limits
Sample Size and Sampling Frequency
Rational Subgroups
Analysis of Patterns on Control Charts
Discussion of Sensitizing Rules for Control Charts
Phase I and Phase II of Control Chart Application
The Rest of the Magnificent Seven
Implementing SPC in a Quality Improvement Program
An Application of SPC
Applications of Statistical Process Control and Quality Improvement Tools in Transactional and Service Businesses
Control Charts for Variables
Chapter Overview and Learning Objectives
Introduction
Control Charts for �x and R
Statistical Basis of the Charts
Development and Use of �x and R Charts
Charts Based on Standard Values
Interpretation of �x and R Charts
The Effect of Nonnormality on �x and R Charts
The Operating-Characteristic Function
The Average Run Length for the �x Chart

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