QC101

List the 8 dimensions of quality

Discuss the importance and contributions of the quality Gurus Phil Crosby, Edward Deming, Joseph Juran, Karoru Ishikawa

Discuss the practical implications of Nelson's Funnel Experiment

Define QMS

Describe the tenets of ISO 9001 and ISO 14002

Explain the fundamental principles and procedure for Six Sigma

Define PSDA

List the four activities of the plan phase

Define CAR and its purpose

Describe how to select members of a quality improvement team and their roles and responsibilities.

Define and develop a SMART goal

Explain the purpose of a check sheet

Develop and use a Pareto chart to select a problem to be solved.

Design a process flow chart with the proper symbols

Design a value stream map including the use of C/T, C/O, and Takt time

Determine the takt time for a process

Describe what happens in the Do, Study, Act phase of the PDSA cycle.

Develop a cause and effect chart to address a problem.

Describe the process of brainstorming

Describe the purpose of a scatter plot diagram, histogram, and run charts in the PDSA cycle.

Demonstrate the use a force field analysis to address a change.

Create a scatter plot diagram and a basic histogram using Excel.

Define variable data and give an example of the two kinds of variable data.

Define and give examples of discrete data.

Define and describe the difference between precision and accuracy.

Round a number using the odd-up even down method

Perform a mathematical calculation and determine the answer with the proper number of significant figures.

Learn how to produce same Pareto chart in Minitab

Learn how to use Mini-tab to produce and analyze Histograms

Sort data into a stacked column using Mini-tab

Format histograms with labels and gridlines

Create a dot plot to organize and find the frequency of the data.

Determine the average of ungrouped data using the average formula

Explain how mean, median, and mode may be used to describe the distribution of data.

Explain why and how the standard deviation and range may be used to describe the distribution of data. What are the terms in the formula for Standard Deviation.

Use Mini-tab to calculate the skewness value for a given set of data. Explain how this numerical value relates to skewness and what would be seen on a graph of the data. Use Mini-tab to calculate the kurtosis of a value for a given set of data. Explain how this numerical relates to kurtosis and what would be seen on a graph of the data. Explain how to calculate the coefficient of variation and explain how this value is useful to comparing sets of data with similar standard deviations.

Illustrate how a normal distribution may be represented. Describe what a normalized curve does. Determine the Z value and the probability using a normal curve.

Find the probability of parts being in or out of specification using the standard normal curve. Use a histogram to determine if data follows a normal distribution. Given a scatter diagram, determine the degrees and type of correlation.

Produce a probability plot for a given set of data and determine if the distribution is normal. List the types of common causes variation that is to be expected for piece part production. For each example of common cause variation, given an example.

Define and explain the difference between assignable and common cause (chance cause) variation

List some benefits of using a control chart. Explain how a normal distribution curve relates to the control chart. Calculate the UCL and LCL using Excel or Table of constant formulas

Explain what is meant by the LCL and UCL Explain any correlation of LCL and UCL to customer specifications. Explain where the center line for a control charts comes from.

Create an X-bar Chart and R Chart using Mini-tab Explain why the R-chart or s-chart is evaluated prior to evaluating the X-bar chart. Create an X-bar, S chart. When is the s- chart preferred over the R-chart? When should LCL and UCL limits be re-evaluated?

Explain how a control chart can be thought of or illustrated as tiny distribution curves. Explain the difference between a type I and type II error. Recognize and identify the trends that occur that can indicate a process is out of control.

Explain difference that may occur when using individual measurements and subgroup measurements in finding averages. Find the estimated population mean. Determine the process capability and process capability index for a set of data and customer specifications.

Explain why a good process capability (Cp) may not be a good indication that you are meeting specifications. Explain the difference between tolerance and process capability.

Explain why an iMR chart may be used instead of a X--bar, R chart. Show how to calculate the moving average or moving range for a set of data. Explain why a control chart for trends might be appropriate.

Create and explain the primary purpose for using a EWMA chart. Explain the differences between continuous and batch processing. Explain the difference between in batch variation and batch to batch variation.

Explain and demonstrate how to create, use, and analysis a multi-vari chart. Create and use a specification control chart. Create and use a deviation control chart.

Create and use a Z control chart (with MW). Demonstrate the method of pre-control for a start-up or short run process. Differentiate between continuous and attribute data.

Explain the difference and give examples of defectives versus defects Determine the central line and UCL, LCL for np and P charts. Produce an attribute chart on Excel and Mini-tab

Determine the central line and UCL and LCL for C and U charts. Explain the difference between a C and U chart. Plot a C and U chart. Create a variable U and P chart