Six Sigma Green Belt: Improve and Control

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Design of Experiments and Validation of Solutions in Six Sigma
Credit NASBA: 1.5

Statistical Process Control and Control Plans in Six Sigma
Credit NASBA: 2

Using Basic Control Charts in Six Sigma
Credit NASBA: 3

Structura cursului

Design of Experiments and Validation of Solutions in Six Sigma

  • match the key elements of the DOE methodology with examples

 

  • match each type of DOE with an example

 

  • distinguish between full and fractional factorial DOEs based on the number of runs, factors, and levels for each

 

  • sequence examples of the steps in the DOE process

 

  • identify examples of interactions and main effects in DOE

 

  • match tools that are used to identify improvement solutions with descriptions

 

  • identify how to evaluate and select solutions using a solution selection matrix

 

  • recognize when to use various tools for testing and validating improvement solutions

 

 

 

Statistical Process Control and Control Plans in Six Sigma

  • identify the key objectives of statistical process control

 

  • identify the benefits of statistical control

 

  • recognize examples demonstrating the different strategies for rational subgrouping

 

  • match the key elements with descriptions of their roles in control charts

 

  • determine the types of control charts suitable to use for given types of data

 

  • identify control chart patterns that indicate a process is out of control

 

  • match each control plan type with a description of the type of information it provides

 

  • sequence the steps in each phase of the construction of a control plan

 

  • match the key sections of a control plan with the information they contain

 

 

 

Using Basic Control Charts in Six Sigma

  • recognize which variable or attribute control chart to use in a specific situation

 

  • identify the major activities that are performed at each step in the standard control charting process

 

  • identify the four commonly applied tests that determine evidence of special cause variation

 

  • determine any special cause variation in data by creating and interpreting an Xbar and R chart

 

  • recognize which formulas to use to help determine special cause variation in an Xbar and s control chart

 

  • determine any special cause variation in data by creating and interpreting an ImR chart

 

  • calculate the center line, UCL, and LCL for a p control chart to determine if special cause variation exists

 

  • calculate the center line, UCL, and LCL for an np control chart to determine if special cause variation exists

 

  • calculate the center line, UCL, and LCL for a u control chart to determine if special cause variation exists

 

  • calculate the center line, UCL, and LCL for a c control chart to determine if special cause variation exists

 

 

 

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