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Statistical quality control : a modern introduction

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TLDR
Part I: Introduction Chapter 1: Quality Improvement in the Modern Business Environment Chapter 2: The DMAIC Process Chapter 3: Statistical Methods Useful in Quality Control and Improvement Chapter 4: Inferences about Process Quality
Abstract
Part I: Introduction Chapter 1: Quality Improvement in the Modern Business Environment Chapter 2: The DMAIC Process Part II: Statistical Methods Useful in Quality Control and Improvement Chapter 3: Modeling Process Quality Chapter 4: Inferences about Process Quality Part III: Basic Methods of Statistical Process Control and Capability Analysis Chapter 5: Methods and Philosophy of Statistical Process Control Chapter 6: Control Charts for Variables Chapter 7: Control Charts for Attributes Chapter 8: Process and Measurement System Capability Analysis Part IV: Other Statistical Process-Monitoring and Control Techniques Chapter 9: Cumulative Sum and Exponentially Weighted Moving Average Control Charts Chapter 10: Other Univariate Statistical Process Monitoring and Control Techniques Chapter 11: Multivariate Process Monitoring and Control Chapter 12: Engineering Process Control and SPC Part V: Process Design and Improvement with Designed Experiments Chapter 13: Factorial and Fractional Experiments for Process Design and Improvements Chapter 14: Process Optimization and Designed Experiments Part VI: Acceptance Sampling Chapter 15: Lot-by-Lot Acceptance Sampling for Attributes Chapter 16: Other Acceptance Sampling Techniques Appendix

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Monitoring of high-yield and periodical processes in health care.

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Safety Inventory under a Periodic Review System

TL;DR: In this article, the authors derived and verified a formula for calculating safety inventory that satisfies a desired cycle service level in a periodic review system, where stochastic variables, including customer demand and supplier's lead time, are assumed to be normally distributed.
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Control Charts Usage for Monitoring Performance in Surgery: A Systematic Review

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Proceedings ArticleDOI

An alternative method to achieve metrological confirmation in measurement process

TL;DR: In this paper, an alternative method to the traditional metrological requirements about the relationship between tolerance and measurement uncertainty, to develop such confirmation processes is presented. But it is based on a given inspection task of the measurement process into the manufacturing system, and it is defined as the Index of Contamination of the Capability, ICC.

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TL;DR: In this article, the authors used the Generalized Variance (GV) control chart and the Hotelling T2 control chart to determine the variables (elements) that affected the out-of-control observation.
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