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Statistical and Managerial Techniques for Six Sigma Methodology: Theory and Application Book

Statistical and Managerial Techniques for Six Sigma Methodology: Theory and Application
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Statistical and Managerial Techniques for Six Sigma Methodology: Theory and Application, Statistical and Managerial Techniques for Six Sigma Methodology examines the methodology through illustrating the most widespread tool and techniques involved in Six Sigma application. Both managerial and statistical aspects of Six Sigma will be an, Statistical and Managerial Techniques for Six Sigma Methodology: Theory and Application
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  • Statistical and Managerial Techniques for Six Sigma Methodology: Theory and Application
  • Written by author Stefano Barone
  • Published by Wiley, John & Sons, Incorporated, 4/10/2012
  • Statistical and Managerial Techniques for Six Sigma Methodology examines the methodology through illustrating the most widespread tool and techniques involved in Six Sigma application. Both managerial and statistical aspects of Six Sigma will be an
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1 Six Sigma Methodology

1.1 Management by Process

1.1.1 The Concept of ‛Process’

1.1.2 Managing by Process

1.1.3 The Process Performance Triangle

1.1.4 Customer Satisfaction

1.1.5 The Success of Enterprise

1.1.6 Innovation and Six  Sigma

1.2 Meanings and Origins of Six  Sigma

1.2.1 Variation in Products and Processes

1.2.2 Meaning of ‘Six  Sigma’

1.2.3 Six  Sigma Process

1.2.4 Origins of Six  Sigma

1.2.5 Six  Sigma: Some Definitions

13 Six  Sigma Projects

1.3.1 Why Implement Six  Sigma Projects?

1.3.2 Six  Sigma Paths

1.4 The DMARIC Path

1.4.1 Human Resources and Training

References

2 Basic Managerial Techniques

2.1 For Brainstorming

2.1.1 Cause–Effect Diagram

2.1.2 Affinity Diagram (KJ Analysis)

2.2 To Manage the Project

2.2.1 Work Breakdown Structure

2.2.2 Gantt Chart

2.3 To Describe and Understand the Processes

2.3.1 The SIPOC Scheme

2.3.2 The Flow Chart

2.3.3 The ServQual Model

2.4 To Direct the Improvement

2.4.1 The Kano Model

References

3 Basic Statistical Techniques

3.1 To Explore Data

3.1.1 Fundamental Concepts and Phases of the Exploratory Data Analysis

3.1.2 Empirical Frequency Distribution of a Numerical Variable

3.1.3 Analysis by Stratification

3.1.4 Other Graphical Representations

3.2 To Define and Calculate the Uncertainty

3.2.1 Definitions of Probability

3.2.2 Events and Probabilities in the Venn Diagram

3.2.3 Probability Calculation Rules

3.2.4 Dispositions, Permutations and Combinations

3.3 To Model the Random Variability

3.3.1 Definition of Random Variable

3.3.2 Probability Distribution Function

3.3.3 Probability Mass Function for Discrete Random Variables

3.3.4 Probability Density Function for Continuous Variables

3.3.5 Mean and Variance of a Random Variable

3.3.6 Principal Models of Random Variables

3.4 To Draw Conclusions from Observed Data

3.4.1 The Inferential Process

3.4.2 Sampling and Samples

3.4.3 Adopting a Probability Distribution Model by Graphical Analysis of the Sample (Probability Plot)

3.4.4 Point Estimation of the Parameters of a Gaussian Population

3.4.5 Interval Estimation

3.4.6 Hypothesis Testing

References

4 Advanced Managerial Techniques

4.1 To Describe Processes

4.1.1 IDEF 0

4.2 To Manage a Project

4.2.1 Project Evaluation and Review Technique

4.2.2 Critical Path Method

4.3 To Analyse Faults

4.3.1 Failure Mode and Effect Analysis

4.3.2 Fault Tree Analysis

4.4 To Make Decisions

4.4.1 Analytic Hierarchy Process

4.4.2 Response Latency Model

4.4.3 Quality Function Deployment

References

5          Advanced Statistical Techniques to Study the Relationships between Variables

5.1 To Study the Relationships between Variables

5.1.1Linear Regression Analysis

5.1.2Logistic Regression Models

5.1.3Introduction to Multivariate Statistics

5.2 To Monitor and Keep Processes under Control

5.2.1Process Capability

5.2.2Online Process Control and Main Control Charts

5.2.3Offline Process Control

5.3 To Improve Products, Services and Production Processes

5.3.1Robustness Thinking

5.3.2Variation Mode and Effect Analysis

5.3.3Systemic Robust Design

5.3.4Design of Experiments

5.3.5Four Case Studies of Robustness Thinking

5.4 To Assess the Measurement System

5.4.1Some Definitions about Measurement Systems

5.4.2Measurement System Analysis

5.4.3Lack of Stability and Drift of Measurement System

5.4.4Preparation of a Gauge R&R Study

5.4.5Gauge R&R Illustrative Example

References

6          Six  Sigma Methodology in Action. Selected Black Belt Projects in Swedish Organisations

6.1 Resource Planning Improvement at SAAB Microwave Systems

6.1.1 Presentation of SAAB Microwave Systems

6.1.2 Project Background

6.1.3 Define Phase

6.1.4 Measure Phase

6.1.5 Analyse Phase

6.1.6 Improve Phase (Ideas and Intentions)

6.1.7 Control Phase (Ideas and Intentions)

6.2 Improving Capacity Planning of Available Beds: a Case Study for the Medical Wards at Sahlgrenska and Östra Hospitals

6.2.1 Presentation of Sahlgrenska and Östra Hospitals

6.2.2 Project Background

6.2.3 Define Phase

6.2.4 Measure Phase

6.2.5 Analyse Phase

6.2.6 Improve Phase (Ideas and Intentions)

6.2.7 Control Phase (Ideas and Intentions)

6.3 Controlling Variation in Play in Mast Production Process at ATLET

6.3.1 Presentation of ATLET AB

6.3.2 Project Background

6.3.3 Define Phase

6.3.4 Measure Phase

6.3.5 Analyse Phase

6.3.6 Improve Phase (Ideas and Intentions)

6.3.7 Control Phase (Ideas and Intentions)

6.4 Optimising the Recognition and Treatment of Unexpectedly Worsening In-Patients at Kärnsjiukhuset, Skaraborg Hospital

6.4.1 Presentation of Skaraborg Hospital

6.4.2 Project Background

6.4.3 Define Phase

6.4.4 Measure Phase

6.4.5 Analyse Phase (Ideas and Intentions)

6.4.6 Improve Phase (Ideas and Intentions)

6.4.7 Control Phase (Ideas and Intentions)

6.5 Optimal Scheduling for Higher Efficiency and Minimal Losses in Warehouse at Structo Hydraulics AB

6.5.1 Presentation of Structo Hydraulics AB

6.5.2 Project Background

6.5.3 Define Phase

6.5.4 Measure Phase

6.5.5 Analyse Phase

6.5.6 Improve Phase (Planning)

6.5.7 Control Phase (Planning)

6.6 Reducing Welding Defect Rate for a Critical Component of an Aircraft Engine

6.6.1 Presentation of Volvo Aero Corporation

6.6.2 Project Background

6.6.3 Define Phase

6.6.4 Measure Phase

6.6.5 Analyse Phase

6.6.6 Improve Phase (Ideas and Intentions)

6.6.7 Control Phase (Ideas and Intentions)

6.7 Attacking a Problem of Low Capability in Final Machining for an Aircraft Engine Component at VAC Volvo Aero Corporation

6.7.1 Presentation of Volvo Aero Corporation

6.7.2 Project Background

6.7.3 Define Phase

6.7.4 Measure Phase

6.7.5 Analyse Phase

6.7.6 Improve Phase (Ideas and Intentions)

Index


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Statistical and Managerial Techniques for Six Sigma Methodology: Theory and Application, <i>Statistical and Managerial Techniques for Six Sigma Methodology</i> examines the methodology through illustrating the most widespread tool and techniques involved in Six Sigma application. Both managerial and statistical aspects of Six Sigma will be an, Statistical and Managerial Techniques for Six Sigma Methodology: Theory and Application

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Statistical and Managerial Techniques for Six Sigma Methodology: Theory and Application, <i>Statistical and Managerial Techniques for Six Sigma Methodology</i> examines the methodology through illustrating the most widespread tool and techniques involved in Six Sigma application. Both managerial and statistical aspects of Six Sigma will be an, Statistical and Managerial Techniques for Six Sigma Methodology: Theory and Application

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Statistical and Managerial Techniques for Six Sigma Methodology: Theory and Application, <i>Statistical and Managerial Techniques for Six Sigma Methodology</i> examines the methodology through illustrating the most widespread tool and techniques involved in Six Sigma application. Both managerial and statistical aspects of Six Sigma will be an, Statistical and Managerial Techniques for Six Sigma Methodology: Theory and Application

Statistical and Managerial Techniques for Six Sigma Methodology: Theory and Application

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