Lean Six Sigma and statistical tools for engineers and engineering managers /

This book is intended to be a textbook for advanced undergraduate students, graduate students in engineering, and mid-career engineering professionals. It can also be a reference book, or be used to prepare for the Six Sigma Green Belt and Black Belt certifications by organizations such as American...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autores principales: Zhan, Wei (Autor), Ding, Xuru (Autor)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: New York [New York] (222 East 46th Street, New York, NY 10017) : Momentum Press, 2016.
Edición:First edition.
Colección:Engineering management collection.
Temas:
Six sigma (Quality control standard)
Lean manufacturing.
Production management > Quality control.
Six Sigma.
Production allégée.
Production > Gestion > Qualité > Contrôle.
BUSINESS & ECONOMICS > Industrial Management.
BUSINESS & ECONOMICS > Management.
BUSINESS & ECONOMICS > Management Science.
BUSINESS & ECONOMICS > Organizational Behavior.
Lean
Six Sigma
Design for Six Sigma
statistics
probability
DMAIC
engineering
management
optimization
process improvement
quality control
design of experiment
response surface method
Monte Carlo analysis
hypothesis test
robust design
computer-aided design
data analysis
Acceso en línea:Texto completo
Tabla de Contenidos:
  • 1. Introduction
  • 1.1 History of Lean Six Sigma
  • 1.2 Optimal quality cost
  • 1.3 Benefits of Lean Six Sigma.
  • 2. Probability and statistics
  • 2.1 Why is statistics relevant to engineers?
  • 2.2 Probability, sampling, and random variables
  • 2.3 Set theory
  • 2.4 Calculus of probabilities
  • 2.5 System probability as a function of subsystem probabilities
  • 2.6 Law of total probability and Bayes' theorem
  • 2.7 Probability distributions and cumulative distribution functions
  • 2.8 Expected value and variance
  • 2.9 Probability distributions
  • 2.10 The central limit theorem
  • 2.11 Statistical data analysis
  • 2.12 Graphical methods.
  • 3. DMAIC: the process of Lean Six Sigma
  • 3.1 Introduction
  • 3.2 Six Sigma as a statistical measure
  • 3.3 The DMAIC process.
  • 4. Lean Six Sigma tools
  • 4.1 SWOT, affinity diagram, SIPOC, VOC, CTQ
  • 4.2 Cp, Cpk, GR & R, Pareto diagram, prioritization matrix, normality check, Monte Carlo analysis
  • 4.3 Confidence intervals, hypothesis testing, cause-and-effect analysis, FMEA, DOE, VSM
  • 4.4 RSM, regression
  • 4.5 Statistical process control.
  • 5. Excel, MATLAB, Minitab, and other simulation tools
  • 5.1 Excel
  • 5.2 MATLAB
  • 5.3 Minitab
  • 5.4 R and other software tools.
  • 6. Lean Six Sigma projects: strategic planning and project execution
  • 6.1 Strategic planning and deployment
  • 6.2 Project selection
  • 6.3 Lean Six Sigma team
  • 6.4 Project scope and project management
  • 6.5 Milestones, deliverables, and project summary.
  • 7. Design for Six Sigma
  • 7.1 Overview: quality at low costs
  • 7.2 Process of DFSS
  • 7.3 Implementing DFSS
  • 7.4 Conclusions.
  • 8. Case studies
  • 8.1 Lean Six Sigma project, pulse width modulation control for motor speed
  • 8.2 DFSS project, vehicle-occupant safety robust design for frontal impact
  • 8.3 DFSS project, reliability improvement of car window regulator operation.

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