Lean Six Sigma and statistical tools for engineers and engineering managers

✍ Scribed by Ding, Xuru.; Zhan, Wei

• Publisher: Momentum Press
• Year: 2016
• Tongue: English
• Leaves: 273
• Series: Engineering management collection
• Edition: First edition
• Category: Library

✦ Synopsis

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 Society for Quality. The book focuses on the introduction of the basic concepts, processes, and tools used in Lean Six Sigma. A unique feature of this book is the detailed discussion on Design for Six Sigma aided by computer modeling and simulation. The authors present several sample projects in which Lean Six Sigma and Design for Six Sigma were used to solve engineering problems or improve processes based on their own research and development experiences in engineering design and analysis. Read more...

Abstract: 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 Society for Quality. The book focuses on the introduction of the basic concepts, processes, and tools used in Lean Six Sigma. A unique feature of this book is the detailed discussion on Design for Six Sigma aided by computer modeling and simulation. The authors present several sample projects in which Lean Six Sigma and Design for Six Sigma were used to solve engineering problems or improve processes based on their own research and development experiences in engineering design and analysis

✦ Table of Contents

Content: 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 --

✦ Subjects

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