Step 1

Add and configure an SPC Document.

The SPC document is the container for all of the products that are to be grouped together. The products' variables, attributes and defects are stored here in a directory structure similar to Windows Explorer.

The properties that you specify for your document will impact all of its included products. For example, the designated ODBC data source will store data calculated from the SPC Data Collector for all the products included in the document.

Step 2

Add and configure products.

The product is the main container for the type of data that you will choose to collect and analyze. Initially you will provide a name, description and resource ID for your product.

Step 3

Add and configure variable quality characteristics.

Specify the variables you want to measure for each product. For each variable, indicate the following information:

Description (for example, Widget_Length)

Collection characteristics

Limits

Alarms

Calculation Type

For each variable that you add, a histogram is automatically generated by SPC. In addition, you can select between the following chart types:

XBar-R chart set to view the range between the highest and lowest point in a sample.
This range is relatively efficient for small subgroup sample sizes (especially below 9). Although it provides you with a spread, it does not give you a clear indication of where the points fall relative to your control limits.

XBar-S chart sets to review the average of the standard deviations.
This is a more efficient indicator of process variability, especially with larger sample sizes. However, it is less sensitive in detecting special causes of variation that result in only a single value in a subgroup to be unusual.

From "Statistical Process Control," Chrysler Corporation, Ford Motor Company and General Motors Corporation, 1995.

Step 4

Add and configure attribute quality characteristics.

Specify the attributes you want to measure for each product. For each attribute, indicate the following information:

Description (for example Color_Light)

Collection characteristics

Limits

Alarms

Calculation Type

In addition, you can select from among the following chart types:

p chart set measures the proportion of nonconforming (discrepant or defective) items in a group of units being inspected. Proportion is defined as the ratio of the number of nonconforming items in a population to the total number of units in that population. Sample sizes need not be equal.

nP chart set measures the number of nonconforming units in an inspection lot. It is identical to p chart, except that the actual number of nonconforming units, rather than their proportion of the sample are plotted. The inspection sample sizes must be equal in this case.

c chart measures the number of nonconforming units (discrepancies or defects) in an inspection lot. The c chart requires a constant sample size.

u chart measures the number of nonconforming items per inspection unit subgroups, which can have varying sample sizes. It is similar to c chart, except that the number of nonconforming units is expressed on a per unit basis.

Step 5

Add and configure defect categories.

Specify the defects that are to be tracked for each product. For each defect, indicate the following information:

Defect Description

Scope (for example, if you want to use the same data source for multiple defects)

Collection characteristics

Measurement—SPC generates Pareto charts by default

Upgrade CimView screens.

Configure SPC data.