Title	Frontiers in Statistical Quality Control [electronic resource] / edited by Hans-Joachim Lenz, Peter-Theodor Wilrich
Imprint	Heidelberg : Physica-Verlag HD : Imprint: Physica, 1997
Connect to	http://dx.doi.org/10.1007/978-3-642-59239-3
Descript	X, 297 p. online resource

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

1: Sampling Inspection -- An Adaptive Sampling System with a Fuzzy Controller -- Determination of Sample Sizes for Double Sampling Attribute Plans -- Unbiased Estimation of Generalized Moments of Process Curves -- On the Non-Robustness of Maximum-Likelihood Sampling Plans by Variables -- Normal Approximations to the Distribution Function of the Symmetric Beta Distribution -- 2: Process Quality Control -- A Mathematical Framework for Statistical Process Control -- A Review of Statistical and Fuzzy Quality Control Charts Based on Categorical Data -- Efficient Estimation of Control Chart Parameters -- Control Charts for Dependent and Multivariate Measurements -- On EWMA Charts for Time Series -- Statistical Process Control for Autocorrelated Processes: A Case-Study -- Quality Control of a Continuously Monitored Production Process -- Group Sequential Design with Delayed Observations for Selecting One of Two Processes in a Production System -- Design of the ($$ \overline x $$, s) Control Chart Based on Kullback-Leibler Information -- 3: Data Analysis And Process Capability Studies -- Measurement Error Effects on the Performance of Process Capability Indices -- A New Approach for Describing and Controlling Process Capability -- On the Use of Field Failure Data for Repairable Systems to Identify Sources of Variation -- 4: Experimental Design -- Control Chart Method for Analyzing Staggered Nested Data -- Prediction Properties of the Process Variance Using the Combined Array -- Joint Analysis of Mean and Variance Function Based on Second Order Polynomials -- Dependability Improvement Through Unreplicated Experimental Designs

1. Production management
2. Operations research
3. Decision making
4. Statistics
5. Economic theory
6. Econometrics
7. Economics
8. Econometrics
9. Operations Management
10. Operation Research/Decision Theory
11. Statistics for Business/Economics/Mathematical Finance/Insurance
12. Economic Theory/Quantitative Economics/Mathematical Methods