iSixSigma-Editorial

Control Chart Wizard – c-Chart: Control charts dealing with the number of defects or nonconformities are called c charts (for count). There is a difference between a defect and defective, as there is between a nonconformity and nonconforming unit. The c-chart control chart is used with discrete/attribute defect data when c-Bar is greater than 5.

Control Chart Wizard – Discrete Defect Data: How large is your discrete/attribute defect data sample size?

Control Chart Wizard – Discrete Data: What type of discrete/attribute data do you have?

Steps in Constructing an X-Bar and s Control Chart: This document contains the step-by-step instructions to construct an X-Bar and s control chart. First the s chart is constructed. If the s chart validates that the process variation is in statistical control, the XBAR chart is constructed.

Control Chart Wizard – Average And Standard Deviation: This document contains the step-by-step instructions to construct an Average And Standard Deviation control chart.

Steps In Constructing An Exponentially Weighted Moving Average (EWMA) Chart: This document contains the step-by-step instructions to construct an Exponentially Weighted Moving Average (EWMA) control chart.

Steps In Constructing An Individuals And Moving Range Control Chart: This document contains the step-by-step instructions to construct an Individuals And Moving Range control chart.

Steps in Constructing an X-Bar and R Control Chart: This document contains the step-by-step instructions to construct an X-bar and R control chart. First the R chart is constructed. If the R chart validates that the process variation is in statistical control, the XBAR chart is constructed.

Steps in Constructing a Median And Range Control Chart: This document contains the step-by-step instructions to construct a Median And Range control chart. The primary reason for using medians is that it is easier to do on the shop floor because no arithmetic must be done. The person doing the charting can simply order the data and pick the center element.

Control Chart Wizard – Median And Range: If the sample size is relatively small (e.g., less than 10-15) and the median is known, we can display how well a process is centered using the median or middle value. In contrast to the X-Bar and R control chart, this chart is useful when you would like to see less influence by data outliers. This can be an advantage or a disadvantage depending on your objective. The range of a sample is simply the difference between the largest and smallest observation. The Median and R control chart is used with continuous/variable data when subgroup or sample size is between 2 and 15.

Average And Range – X-Bar and R: If the sample size is relatively small (e.g., less than 10-15), we can use the range instead of the standard deviation of a sample to construct control charts on X-Bar (arithmetic mean) and the range, R. The range of a sample is simply the difference between the largest and smallest observation. The X-bar and R control chart is used with continuous/variable data when subgroup or sample size is between 2 and 15.

Continuous/Variable Control Chart Table Of Constants

Wizard Home > Continuous/Variable Data Sample Size Selector Control Chart Suggestion Individuals And Moving Range – X and Rm Control Chart Description Control charts for individual measurements (e.g., the sample size = 1) use the moving range of two successive observations to measure the process variability. The combination of the X Chart for Individuals and […]

Wizard Home > Control Chart Wizard Home Question How large is your continuous/variable data sample size? Choices Please select your sample size from the choices below: Sample Size Of One Sample Size Is Small (Usually Less Than 10-15) Sample Size Is Small (Usually Less Than 10-15), Median Value Known Sample Size Is Large (Usually Greater […]

This Control Chart Wizard will guide you through the process of determining your data type, help you determine the correct control chart, and provide the proper formulas for creating a control chart for your process.

When you know your process yield (percentage of a process that is free of defects), you can use this yield to sigma conversion table to easily determine your process sigma level, as well as your process defects per million opportunities.