PeopleSoft Quality 9.1 PeopleBook

Using PeopleSoft Quality Graphics

This chapter provides an overview of different types of quality graphics and discusses how to:

View Quality graphics.
Define data extractions and load datasets.

Viewing PeopleSoft Quality Graphics

This section discusses how to:

View control charts.
View histograms.
View Pareto charts.
View bar graphs.

Pages Used to View PeopleSoft Quality Graphics

Page Name	Definition Name	Navigation	Usage
Compare Dataset Statistics	QS_ANLZ_STSSUM_SPG	Select the View Chart button on the Data Entry From Access List - Review page: Results tab or on the Data Entry By Control Plan - Review page: Results tab. Select the Control Chart in the Display Graph field on the Review Ctrl Plan Performance - Stream Review inquiry page.	View a control chart associated with the selected subgroups.
Histogram	QS_HISTOGRAM_RVW	Select Histogram in the Display Graph field on the Review Ctrl Plan Performance - Stream Review inquiry page.	View a histogram associated with the selected subgroups.
Pareto Chart	QS_PARETO_RVW	Select Pareto of Alarms, Pareto of Comments, Pareto of Corrective Actions, Pareto of Defects, or Pareto of Probable Causes in the Display Graph field on the Review Ctrl Plan Performance - Stream Review inquiry page.	View a Pareto chart of type comments, corrective actions, defects, or probable causes associated with the selected subgroups.
Bar Graph	QS_BARGRAPH_RVW	Click the Graph Results button on the Compare Data Statistics page.	View a bar graph associated with the selected subgroup.

Viewing Control Charts

Access the Control Chart page (Select the Control Chart in the Display Graph field on the Review Ctrl Plan Performance - Stream Review inquiry page).

In the upper portion of the page, the control chart associated with the subgroups that you selected appears.

The control chart is rendered as two line graphs for plotting means and variance information. Each point on the control chart represents an individual subgroup.

To the left of each graph, the system displays the values and the appropriate labels for upper control limit (UCL), mean (CL), and lower control limit (LCL).

Note. Control limit labels are not set to scale; however, the control limit boundaries are overlaid to scale on each chart.

In the upper portion of the page, the system displays the control limit status, subgroup size, and unit of measure.

Point Display	Select the number of points to display for the control charts. Values are: 05, 10, 15, 20, and 25.
	Click this button to view the next group of control chart points.
	Click this button to view the previous group of control chart points.
Label By	Select how to label the control charts. Values are: Day:Hour: Displays the day and hour under each individual subgroup point on the control chart. Hour:Minute: Displays the hour and minute under each individual subgroup point on the control chart. Month-Day: Displays the month and day under each individual subgroup point on the control chart. Subgroup ID: Displays the subgroup sequence ID under each individual subgroup point on the control chart. Year-Month-Day: Displays the year, month, and day under each individual subgroup point on the control chart.
Alarm Count	The alarm count represents the number of subgroups within the current chart that have an out-of-control condition. Next to this field, a bar graph represents the type of alarm that occurred for each subgroup. A red bar extending upward represents a specification violation, and a yellow bar extending upward represents a means (upper) control chart violation. A blue bar extending downward represents a variance (lower) control chart violation. Additionally, the actual control test description appears when you hover over a subgroup point, enabling you to easily view the specific alarms corresponding to the bar graphs.

Subgroup Details

View details of the subgroup results and test violations for each subgroup.

See Also

Using Control Charts

Defining Control Plans

Reviewing Current Session Results

Reviewing Process Streams

Viewing Histograms

Access the Histogram page (Select Histogram in the Display Graph field on the Review Ctrl Plan Performance - Stream Review inquiry page).

In the upper portion of the page, the histogram associated with the subgroups that you selected appears. A histogram is used to display distribution analysis.

Cell Details

Cell Interval	Displays the high and low boundaries that this cell represents. This field is derived by dividing the distribution range by the number of cells desired for display. The left brace ({) character indicates in which cell the mean, lower specification limit, and upper specification values are contained.
Cell Midpoint	Displays the midpoint of the cell interval.
Cell Tally	Displays the total number of individual values in a cell.
% of Total (percent of total)	Displays the percent of individual values in a cell.

Statistics

Summary statistics are calculated based upon active values for this subset.

See Also

Using Histograms

Reviewing Process Streams

Viewing Pareto Charts

Access the Pareto Chart page (Select Pareto of Alarms,Pareto of Comments,Pareto of Corrective Actions, Pareto of Defects, or Pareto of Probable Causes in the Display Graph field on the Review Ctrl Plan Performance - Stream Review inquiry page).

In the upper portion of the page, a Pareto chart associated with the selected subgroups and attribute type appears. You can create a Pareto chart of alarms, comments, corrective actions, defects, or probable causes. With Pareto charts, you can display attribute counts in a ranked-order format.

Cell Details

Attribute Description	Displays the attribute description. For example, for defects, defect attribute descriptions appear, and for alarms, alarm attribute descriptions appear.
Cell Tally	Displays the attribute count.
% of Total (percentage of total)	Displays the percentage of the number for that particular attribute type for which the attribute accounts. For example, for a Pareto chart of defects, this field represents the percentage of the number of defects for which that attribute accounts.
Cumulative % (cumulative percent)	Displays the cumulative percent value. If you were to plot this line on the Pareto chart, it would represent the cumulative percent line, also known as the Lorenze curve.

Modify Graph

Graph Style

Select the style of graph to display. Options are:

Frequency: Displays the order of the attributes by frequency.
Cumulative Percent: Displays the order of attributes by cumulative percent. This option redraws the chart using the cumulative percent on the X axis.

Redraw

Click this button to redraw the Pareto chart with the selected options (cells containing text, cell display limit, and graph style).

The complete list of cell statistics always appears, regardless of the modification options that you select.

Reset

Click this button to restore the number of cells that appear in the Pareto chart to the number of cells that appeared when the graph was first displayed.

The number of cells that appear in the Pareto chart can change when you use the Cells Containing Text and Cell Display Limit fields. When you click the Reset button, the cells that appear in the Pareto chart are redrawn to there original appearance. Reset does not effect the graph style.

See Also

Using Pareto Charts

Reviewing Process Streams

Viewing Bar Graphs

Access the Bar Graph page (Click the Graph Results button on the Compare Data Statistics page).

In the upper portion of the page, a bar graph associated with the selected subgroups appears. With bar graphs, you can compare a selected statistic between multiple subsets.

Details

The details (bar item and value) for the bar graph appear.

Modify Graph

Redraw

Click this button to redraw the bar graph with the options (items containing text and bar display limit) that you selected.

The complete list of details always appears, regardless of the modification options that you select.

Reset

Click this button to restore the number of items that appear in the bar graph to the number of items that appeared when the graph was first displayed.

The number of items in the bar graph can change when you use the Items Containing Text and Bar Display Limit fields. When you click the Reset button, the items that appear in the bar graph are redrawn to their original appearance.

See Also

Using Bar Graphs

Reviewing Process Streams

Defining Data Extractions and Loading Datasets

To define data extractions, use the Define Extraction Criteria component (QS_QSX_DEF). This section provides an overview of datasets and data extractions and discusses how to:

Define extract settings.
Define extract criteria.
Perform data extractions.

Understanding Datasets and Data Extractions

Using the Quality application client, you can generate graphics and perform exploratory analysis of quality data while offline. The data managed by the PeopleSoft application client is called a dataset and contains the related measurement, traceability, attribute, and configuration information required for performing quality analysis. This information is formatted specifically for use by the Quality application client and resides outside the quality database.

Datasets are created as a result of defining and executing data extractions. The information taken from the Quality database fills a dataset based on selection and filtering criteria that you provide. Datasets are composed of spreadsheet-like elements, such as rows, columns, subsets (pages), and cell values. Datasets contain these options for column and row types:

Common columns (traceability).

Common columns apply to all subsets in the dataset and usually represent traceability information, such as lot numbers and date stamps. Common columns help minimize redundant information when creating a standalone dataset.
Data columns (reading, defects, violations).

Data columns are specific to an individual subset. Data columns typically include measurement values, subgroup counts, and attribute information, such as defects, causes, and actions.

Note. Datasets created from the database, such as performing data extractions, use data columns exclusively.
Subset.

Subset columns are logical groupings of data, typically based on a process stream or characteristic. A subset encompasses the columns in the dataset much like a page does in a typical spreadsheet program. Subsets are configured similarly to measurement plan characteristics; you can assign a data type and control parameters to a subset. This enables the subset to be graphed and analyzed easily.

Note. Datasets created from the database populate the subset control configuration parameters with the current settings for the characteristic or stream. A dataset can contain up to 100 subsets. The tabs on the Quality application client spreadsheet represent subset names.
Standard cell.

Standard cells contain a single value.
Tall cell.

Tall cells contain multiple values. Attributes data, such as test violations, causes, and actions, can occur in multiples for a given cell, and thus may be displayed as multiple rows within the cell. Click the F2 button twice to enter multiple lines into a tall cell.

Datasets appear as a spreadsheet in the Quality application client. You create datasets using one of these methods:

Define and run a data extraction.
Access the Quality application client and create a dataset from scratch.

Extractions are reusable queries that retrieve data from the Quality database and can be shared by multiple users. The extraction functions (define and execute) are separated to facilitate access by users with different job functions, such as managers and analysts.

Use the Data Extraction PeopleCode process to select a set of inspection data from the PeopleSoft database and analyze it using the Quality application client tools. You define the data to extract and download it to the Quality application client for exploratory and ad-hoc analysis. Use the Quality application client to manipulate, add, change, or delete data to perform what-if analyses of processes and view graphics of the data.

Prerequisites

Before defining a dataset for use by the Quality application client, you must:

Determine the processes to extract.
Decide how to organize the dataset.
Identify the categories of data to extract from the database.
Determine the amount of data to include in the extraction.

You must also use the using the File Locations page to enter the location to store the datasets.

See Defining Additional Common Information.

Common Elements Used in This Section

Extraction Name	Enter an extraction name. An extraction identifies data you select from the Quality database used to create a dataset. Extraction names must conform to Microsoft Windows NT file naming conventions, so avoid using special characters, such as dashes, periods, and apostrophes in names.
Description	Enter the description for the subset. The name must be unique within the dataset.
Graph Preference ID	Select the default graph preference to associate with an extraction.

Pages Used to Define Data Extractions and Load Datasets

Page Name	Definition Name	Navigation	Usage
Define Extraction Criteria - General	QS_QSX_DEF	Quality, Prepare Analysis, Define Extraction Criteria, General	Define general settings for the extraction.
Define Extraction Criteria - Selection Criteria	QS_QSX_FLDS	Quality, Prepare Analysis, Define Extraction Criteria, Selection Criteria	Define how to filter data for the extraction and select data-entry sessions.
Perform Data Extraction	QS_QSX_INQ	Quality, Analyze Quality Results, Perform Data Extraction	Execute the Data Extraction PeopleCode process.

Defining Extract Settings

Access the General page (Quality, Prepare Analysis, Define Extraction Criteria, General).

Subset By	Select how the system subsets data for the extraction. Options are: All (Single Subset): All data is displayed as one subset. Characteristic: The data is divided into subsets according to individual characteristics. Stream: The data is divided into subsets according to process stream.
Display Options	Select if the system should include one or all other categories of information to display, in addition to session data information.
Select Sessions By	Select how sessions are selected by timeframe. Options are: All Subgroups: Extract all the subgroups for each process. Daily Window: Extract the sessions entered in the last n days based on the current date and time. Enter the number of days to subtract from the current date in the Number of Days field. Specific Date Range: Extract the sessions entered between a certain date range. Enter the date from and from time, and enter the date to and to time. Subgroup Window: Extract the most current n subgroups entered. You'll enter the number of subgroups in the Number of Subgroups field.
Lock Selections	Select this check box to protect the integrity of the expressions and the amount of data to be included in the extraction. If selections aren't locked here, you can modify them during execution.

Defining Extract Criteria

Access the Define Extract Criteria - Selection page (Quality, Prepare Analysis, Define Extraction Criteria, Selection Criteria).

Specify the sessions from which you want to select data. You can limit the extraction to sessions entered for specific values of hierarchy data and trace data from the business unit and quality function, or you can limit data to sessions entered within a certain time period.

Hierarchy Field Selections and Trace Field Selections

The fields vary depending on the quality function. Use these fields to further limit the sessions that are retrieved. Set all operators to ALL if you do not want to qualify based on hierarchy or trace field values. Qualifier values for both fields include:

<>: Greater than or less than the value entered.

=: Equal to the value entered.

ALL: All entries are returned, and there is no qualification on the field.

BETWEEN: Select the field between the values you enter.

LIKE: Select the field where it is like or similar to the value. Use the % character to denote wildcard positions.

Performing Data Extractions

Access the Perform Data Extraction page (Quality, Analyze Quality Results, Perform Data Extraction).

The page displays the extraction criteria defined using the Define Extract Criteria component.

Session History	If you haven't locked the qualifier selections that specify the streams and data content to extract from the database, you can change the values associated with the statements and the history. The new settings are in effect for this run only and aren't saved.
Search	Click this button to run the Data Extraction PeopleCode process. When the process is complete, the system creates a dataset based on the extraction contents. Using the browser, you can display the dataset online if the Quality application client is installed on a local machine, or you can download the file to a local machine.
Dataset Location	Displays the location of where the dataset is created upon completion of the extraction process. Note. The Data Extraction process creates one file, in the location you specified on the File Locations page. The name of the file is the extraction name with this extension: cld.
View Dataset	Click this button to view the dataset using the browser. You can either download the dataset file to a local machine or open the dataset remotely using the Quality application client. In either case, it is assumed that you have installed the application client software on the computer that you are using.