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Introduction to Engineering Statistics and Six Sigma: Statistical Quality Control and Design of Experiments and Systems
9 references·2 citing·33 second hop
Introduction to Engineering Statistics and Six Sigma: Statistical Quality Control and Design of Experiments and Systems (2009)Introduction to Engineering Statistics an…Statistical Quality Control (2001)Statistical Quality ControlExperiments: Planning, Analysis, and Parameter Design Optimization (2001)Experiments: Planning, Analys…The Six Sigma Way: How GE, Motorola, and Other Top Companies are Honing Their Performance (2000)The Six Sigma Way: How GE, Mo…Six Sigma: The Breakthrough Management Strategy Revolutionizing the World's Top Corporations (2000)Six Sigma: The Breakthrough M…Implementing Six Sigma: Smarter Solutions Using Statistical Methods (2000)Implementing Six Sigma: Smart…Design and Analysis of Experiments (2000)Design and Analysis of Experi…Model-Oriented Design of Experiments (1997)Model-Oriented Design of Expe…Empirical Model-Building and Response Surfaces. (1988)Empirical Model-Building and …Response Surface Methodology (1973)Response Surface MethodologyProcess Capability and Six Sigma Methodology Including Fuzzy and Lean Approaches (2010)Process Capability and Six Si…The application of the Multiple-Domain Matrix: Considering multiple domains and dependency types in complex product design (2008)The application of the Multip…Product development performance: strategy, organization, and management in the world auto industry (1991)Mass customization: The new frontier in business competition (1999)Design Rules (2000)Case Study–Based Testing of Design Interface Management System (2012)Integrating virtual and physical testing to accelerate the engineering product development process (2014)Together They are Strong: The Quest for Service Modularization Parameters (2014)Chapter 17 Contingent Valuation (2005)Design of experiments with multiple independent variables: A resource management perspective on complete and reduced factorial designs. (2009)Implementation and evaluation of nonparametric regression procedures for sensitivity analysis of computationally demanding models (2009)People Capability Maturity Model (P-CMM) Version 2.0 (2001)Application of six sigma methodology to reduce defects of a grinding process (2011)Coerced Practice Implementation in Cases of Low Cultural Fit: Cultural Change and Practice Adaptation During the Implementation of Six Sigma at 3M (2013)Implementing the Lean Sigma framework in an Indian SME: a case study (2006)Total Survey Error: Design, Implementation, and Evaluation (2010)An analysis of the Six Sigma DMAIC method from the perspective of problem solving (2012)Experimental Design: Review and Comment (1984)Optimization via simulation: A review (1994)Multiple predictor smoothing methods for sensitivity analysis: Description of techniques (2007)A Methodology for Trading-Off Performance and Robustness Under Uncertainty (2005)Performance Moment Integration (PMI) Method for Quality Assessment in Reliability-Based Robust Design Optimization (2005)Integration of Possibility-Based Optimization and Robust Design for Epistemic Uncertainty (2006)Optimal experimental design and some related control problems (2007)Design of computer experiments: space filling and beyond (2011)A Review of Modern Computational Algorithms for Bayesian Optimal Design (2015)Latin hypercube sampling and the propagation of uncertainty in analyses of complex systems (2003)Three-level meta-analysis of dependent effect sizes (2012)A Review on Global Sensitivity Analysis Methods (2015)Design and Analysis of Experiments (2001)State-of-the-Art Review: A User’s Guide to the Brave New World of Designing Simulation Experiments (2005)Design and Analysis of Experiments (2006)Key ingredients for the effective implementation of Six Sigma program (2002)Six Sigma: a goal‐theoretic perspective (2002)Six Sigma: Definition and underlying theory⋆ (2007)
this work references cited by second hop

References

  • 2000Design and Analysis of Experiments2,656 cited
  • 1988Empirical Model-Building and Response Surfaces.1,894 cited
  • 2000The Six Sigma Way: How GE, Motorola, and Other Top Companies are Honing Their Performance994 cited
  • 2000Implementing Six Sigma: Smarter Solutions Using Statistical Methods772 cited
  • 2001Experiments: Planning, Analysis, and Parameter Design Optimization536 cited
  • 1973Response Surface Methodology466 cited
  • 1997Model-Oriented Design of Experiments409 cited
  • 2000Six Sigma: The Breakthrough Management Strategy Revolutionizing the World's Top Corporations172 cited
  • 2001Statistical Quality Control106 cited

Cited by

  • 2008The application of the Multiple-Domain Matrix: Considering multiple domains and dependency types in complex product design31 cited
  • 2010Process Capability and Six Sigma Methodology Including Fuzzy and Lean Approaches25 cited

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