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Statistical quality control : a modern introduction
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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 QualityAbstract:
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 Appendixread more
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Bringing Data to Life with Post-Hoc CUSUM Charts
TL;DR: The authors believe that this case study would be of value to classes in applied statistics at intermediate level in courses including an element on applications to process improvement.
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Assessment of damage localization based on spatial filters using numerical crack propagation models
TL;DR: In this article, a crack propagation model is used to detect cracks in concrete structures. But the model is based on a simply supported beam modeled with 2D plane stress elements, and the results of the model are used as the input to the previously designed damage localization system to assess its performances.
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Method for improving the measurement system selection depending on part and process precisions
TL;DR: In this article, a method for selecting the appropriate measurement system that at best fits to the precisions of part and process simultaneously is proposed, where the authors conduct a hypothesis test using the number of observations n, the probabilities of type I and type II errors, the required value of the capability index (Cp,Required) and the tolerance (Tol) of the evaluated specification to establish the corresponding critical values of the NDC∗ and the precision to tolerance ratio (PTR∗).
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Uncertainty quantification of dynamic responses in the frequency domain in the context of virtual testing
Maik Brehm,Arnaud Deraemaeker +1 more
TL;DR: A novel approach is proposed that overcomes the limitation of both aforementioned methods, by providing a fast analytical probabilistic framework for uncertainty quantification to determine accurately the statistics of short time dynamic responses.