Statistical Process Control

Process Capability consists of comparing the Voice of the Customer to the Voice of the Process. SPC Control Charts provide a quantitative measure of the Voice of the Process. This lesson explains the principle of process capability and the role of SPC in achieving and maintaining it.

Process Capability is often correlated with process Sigma. The calculation of process capability is quite different depending upon whether the data is variable or attribute data. This lesson will present the technique and practice using the variable data process capability ratios.

Six Sigma projects strive to achieve a process capability that represents Six Sigma quality. The calculation of process capability is quite different depending upon whether the data is variable or attribute. This lesson will present the technique used for determining process capability with attribute data.

This lesson explains how a control chart works. The various elements of a control chart are described and the correlation between the data shown on Control Charts and process stability is discussed.

In this lesson the strategy for how to use Control Charts is discussed. In addition to monitoring the process, the charts can be used to set performance baselines, validate the impact of improvement, and identify sources of variation.

This lesson explains the principles behind how control limits are calculated. The lesson also discusses when to establish limits and how to use those limits to detect special cause variation. Finally, the lesson will show how to set the threshold criteria for use with control limits in Minitab.

This lesson introduces the eight step approach to be used with establishing control charts for a process. In addition, it provides a decision tree for selecting which control chart to use based upon the nature of the data being monitored.

Some of the most important decisions with respect to control charting are the decisions about subgroups and samples. These decisions will dictate the type of control chart that should be used. They also will determine the number of data points in a subgroup. The decisions should be made based upon the characteristics of the process that is being control charted.

This class reviews the appropriate and inappropriate response to be taken based upon the data found on a control chart. It reviews what steps to follow when there is special cause variation and what steps to follow with common cause variation.

This lesson discusses the principles of using control charts with variable data and provides ground rules for data sampling. The differences between the variable data SPC control charts are explained.

The Individual and Moving Range chart is the simplest of the variable data control chart. This lesson explains how the data is recorded and interpreted on the chart. The lesson describes how to create this control chart in both Microsoft Excel and using Minitab. The lesson will include practice creating the chart.

The X-bar and Range chart is the most commonly used variable data control chart. When discussing SPC, this is always the example. This lesson explains how the data is recorded and interpreted on the chart. The lesson describes how to create this control chart in both Microsoft Excel and using Minitab. The lesson will include practice creating the chart.

This lesson discusses the unique considerations associated with monitoring attribute data with control charts. It compares and contrasts the various attribute data control charts and provides some ground rules for subgroups selection.

The C chart (plots Counts) is the simplest of the attribute data control charts. This lesson explains how the data is recorded and interpreted on the chart. The lesson describes how to create this control chart in both Microsoft Excel and using Minitab. The lesson will include practice creating the chart.

The U chart relies on counting both defects and units and is appropriate if the process has erratic flow. This lesson explains how the data is recorded and interpreted on the chart. The lesson describes how to create this control chart in both Microsoft Excel and using Minitab. The lesson will include practice creating the chart.

The NP Chart tracks defective units rather than actual defects. It provides a more macro perspective for the organization. This lesson explains how the data is recorded and interpreted on the chart. The lesson describes how to create this control chart in both Microsoft Excel and using Minitab. The lesson will include practice creating the chart.

The P chart is closely related to the NP Chart. It also tracks units but tracks the percentage of defective units. This lesson explains how the data is recorded and interpreted on the chart. The lesson describes how to create this control chart in both Microsoft Excel and using Minitab. The lesson will include practice creating the chart.

This lesson introduces the concept of weighting the data being tracked in a control chart based upon other recent data values. The advantages and disadvantages of this approach are discussed as the weighting principles are introduced.

The Cumulative Sum (CUSUM) Chart is more sensitive to subtle shifts in the process than the traditional variable data charts. The look of this control chart is unique among the commonly used control charts. This lesson explains how the data is calculated and interpreted on the chart. The lesson describes how to create this control chart in both Microsoft Excel and using Minitab. The lesson will include practice creating the chart.

The Exponentially Weighted Moving Average Chart uses both the current data point and recent data points. It is also very sensitive to small shifts in the data. This lesson explains how the data is recorded and interpreted on the chart. The lesson describes how to create this control chart in both Microsoft Excel and using Minitab. The lesson will include practice creating the chart.