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In 377 pages, this book
Shows the execution of Minitab functions in a detailed Lean Six Sigma Define-Measure-Analyze-Improve-Control (DMAIC) roadmap to enhance the Y response for process improvement projects
Shows use of a free software app for response-metric tracking that provides insight not possible with traditional metric reporting techniques
Utilizes over 50 datasets to illustrate Y-response tracking from a process-output perspective and Y=f(X) analyses
Discusses over 200 figures that illustrate software inputs and outputs
Provides a clickable Lean Six Sigma Define-Measure-Analyze-Improve-Control (DMAIC) process-improvement roadmap that integrates the application of Lean and Six Sigma tools so that the right tool is used at the right time when undertaking process improvement efforts
Shows a methodology for Lean Six Sigma improvement project selection so that the organization's big-picture benefits from the project's completion
Provides a method to statistically show and quantify at the 30,000-foot-level the benefits of process improvement efforts
Offers a business process improvement system that goes beyond traditional Lean Six Sigma and the Balanced Scorecard
Explains a method for executing and enhancing digital transformation efforts in an organization
This book provides direction on how organizations can resolve issues that commonly occur with
Traditional control charts and process capability reporting techniques
AQL testing and reporting
Lean Six Sigma deployments
This book provides direction on how organizations can benefit from the wise application of:
Statistical and non-statistical techniques
Design of Experiments (DOE) in both manufacturing and transactional processes
This book provides a comprehensive 9-step system that CEOs, presidents, general managers, executives, managers, leaders, practitioners, and others can use to resolve elephant-in-the-room management issues such as
Business goals not being met
Scorecards leading to harmful, if not destructive, behaviors
Persistent day-to-day firefighting problems
Business strategies that are very generic and difficult to translate into organizational work environments
Lean events and other improvement projects can consume many resources but often do not offer a quantifiable benefit to the business as a whole
Lean Six Sigma process improvement deployments that have improvement projects, which are either not completed in a timely fashion or which make substantial financial claims that are questionable
This book describes the application and how to use of the following tools in Minitab as part of a Lean Six Sigma Define-Measure-Analyze-Improve-Control (DMAIC) roadmap
Time-series plot
Histogram
Dot plot
Descriptive statistics
Pareto chart
Probability plot
X-bar and R control chart
P-chart
Process capability indices
30,000-foot-level reports
Cause-and-effect diagram
Visualization of data
Multi-vari chart
Hypothesis testing
Inferences: continuous data
Inferrences: attribute data
Comparing two samples
Demonstration of process metric output response improvement
Variance components
Correlation
Simple regression
Residuals
Single factor ANOVA
ANOM
Two factor ANOVA
Multiple regression
Binary Logistic regression
General Linear Model (GLM)
Design of Experiments (DOE)
Response surface methodology (RSM)
Control phase - maintain the gain
Offers a methodology to implement Deming's management philosophy, ISO 9000, Baldrige award criteria & Shingo Prize criteria
Shows the execution of Minitab functions in a detailed Lean Six Sigma Define-Measure-Analyze-Improve-Control (DMAIC) roadmap to enhance the Y response for process improvement projects
Shows use of a free software app for response-metric tracking that provides insight not possible with traditional metric reporting techniques
Utilizes over 50 datasets to illustrate Y-response tracking from a process-output perspective and Y=f(X) analyses
Discusses over 200 figures that illustrate software inputs and outputs
Provides a clickable Lean Six Sigma Define-Measure-Analyze-Improve-Control (DMAIC) process-improvement roadmap that integrates the application of Lean and Six Sigma tools so that the right tool is used at the right time when undertaking process improvement efforts
Shows a methodology for Lean Six Sigma improvement project selection so that the organization's big-picture benefits from the project's completion
Provides a method to statistically show and quantify at the 30,000-foot-level the benefits of process improvement efforts
Offers a business process improvement system that goes beyond traditional Lean Six Sigma and the Balanced Scorecard
Explains a method for executing and enhancing digital transformation efforts in an organization
This book provides direction on how organizations can resolve issues that commonly occur with
Traditional control charts and process capability reporting techniques
AQL testing and reporting
Lean Six Sigma deployments
This book provides direction on how organizations can benefit from the wise application of:
Statistical and non-statistical techniques
Design of Experiments (DOE) in both manufacturing and transactional processes
This book provides a comprehensive 9-step system that CEOs, presidents, general managers, executives, managers, leaders, practitioners, and others can use to resolve elephant-in-the-room management issues such as
Business goals not being met
Scorecards leading to harmful, if not destructive, behaviors
Persistent day-to-day firefighting problems
Business strategies that are very generic and difficult to translate into organizational work environments
Lean events and other improvement projects can consume many resources but often do not offer a quantifiable benefit to the business as a whole
Lean Six Sigma process improvement deployments that have improvement projects, which are either not completed in a timely fashion or which make substantial financial claims that are questionable
This book describes the application and how to use of the following tools in Minitab as part of a Lean Six Sigma Define-Measure-Analyze-Improve-Control (DMAIC) roadmap
Time-series plot
Histogram
Dot plot
Descriptive statistics
Pareto chart
Probability plot
X-bar and R control chart
P-chart
Process capability indices
30,000-foot-level reports
Cause-and-effect diagram
Visualization of data
Multi-vari chart
Hypothesis testing
Inferences: continuous data
Inferrences: attribute data
Comparing two samples
Demonstration of process metric output response improvement
Variance components
Correlation
Simple regression
Residuals
Single factor ANOVA
ANOM
Two factor ANOVA
Multiple regression
Binary Logistic regression
General Linear Model (GLM)
Design of Experiments (DOE)
Response surface methodology (RSM)
Control phase - maintain the gain
Offers a methodology to implement Deming's management philosophy, ISO 9000, Baldrige award criteria & Shingo Prize criteria
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