Dimensional Planning and Validation Admin Guide
Dimensional Planning and Validation Admin Guide
Dimensional Planning and Validation Admin Guide
Teamcenter 12.0
Dimensional
Planning and
Validation
Administration
PLM00151 • 12.0
Contents
Glossary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . B-1
Provides the foundation of DPV, which is the collection and storage of quality data and the
interactive 3-D reporting and analysis of that data.
• Site
Provides DPV Core capabilities, plus provides Web-based reporting and monitoring of quality
data.
• Enterprise
Provides DPV Site capabilities, plus provides summarized historical reports, and enables the
entire enterprise to identify, analyze, and share quality data through a Web-based collaboration
environment.
DPV components
• Validating data.
DPV components
The Dimensional Planning and Validation (DPV) solution consists of the following key components:
Core
The foundation of DPV provides the collection and storage of quality data and the interactive 3-D
reporting and analysis of that data. It includes the following components:
o Physical inspection devices at the shop floor capture and store real-time quality data.
Typically, these inspection devices include laser gap analysis, coordinate measuring
machines (CMM), optical and digital measurement devices, hand-held devices, and any
number of physical inspection systems.
o DPV Extraction, Translation, and Loading (DPV ETL) provides real-time data loading, storing,
and monitoring of the quality data obtained from the inspection devices. An administrator
uses DPV Enterprise Configuration Explorer to configure the tasks that DPV ETL performs.
o Teamcenter provides the database definition and management of the quality data captured,
including DPV Measurements that lets you view measurement events.
o Visualization Illustration lets you create templates for graphical reports of quality data and its
analysis.
Site
The Site configuration provides the added dimensions of the Web-based reporting and monitoring of
quality data and includes the following components.
• Web-based reporting
o DPV Viewer provides access to reports.
o Microsoft SQL Server Reporting Services (SSRS) manages the publication of data and
reports.
o Siemens PLM Software Visualization Automation Server updates the DPV Reporting &
Analysis charts in the graphical reports using the latest measurement data and publishing
them to the DPV Web site.
o DPV Quality Data Monitor provides real-time viewing and loading of quality data.
Enterprise
The Enterprise configuration provides the added dimensions of summarized historical reports and
the ability of the entire enterprise to identify, analyze, and share quality data through a Web-based
collaboration environment:
• DPV Microsoft SQL Analysis Server (DPV-SSAS) provides historical reporting.
• Teamcenter community collaboration provides the viewing of reports and collaboration across
your enterprise.
Flow of data
The flow of quality data through Dimensional Planning and Validation (DPV) is shown.
• The inspection devices (such as, vision systems, coordinate measurement machines (CMM), and
handheld devices) on the shop floor collect quality data referred to as measurement data. The
data can be in ASCII or Document Markup Language (DML). They send the data to the DPV
Extraction, Translation, and Loading (DPV ETL).
• DPV ETL translates the data into a standard data loading format and stores the data in its
database for analysis and backup. It then sends the collected data to the Teamcenter database
for storage. An administrator uses the DPV Enterprise Configuration Explorer to configure the
tasks performed and the DPV Web-based monitoring tools to monitor the tasks.
• Teamcenter makes the measurement available to other DPV components for analysis and
reporting.
o DPV Reporting & Analysis to query for the data in Teamcenter and visualize and analyze
the data to help identify and resolve issues. DPV Reporting & Analysis provides you with a
wide range of reports and features to analyze the data, including charts, advanced filtering
of data, and mathematical data transformations. In addition, you can export the data for
analysis in Variation Analysis.
o Visualization Illustration to create templates of graphical reports and administer the creation
and publication of reports using Microsoft SSRS. In an Enterprise environment, historical
summary reports are also managed in the DPV-SSAS cube.
o The Visualization Automation Server updates the DPV Reporting & Analysis charts in
templates using the latest measurement data and publishes them to the Web.
• A bill of process that defines the engineering data. A bill of process is a hierarchical structure
that represents the measurement or inspection process within a given plant. The structure
defines the locations where the measurement routines are executed throughout the plant. The
MEPrPlantProcess process is its root.
A measurement routine defines the actual elements that are measured. These elements are grouped
together as a single operation (the routine) within the process.
The top level of the bill of resource is a plant of the type of MEPrPlant. You can then have
stations below it of the type MEPrStation. Inspection devices are modeled using items of the type
InspectionDevice.
When defining engineering data, you create a process structure (bill of process) using Manufacturing
Process Planner. The bill of process contains the measurement routines and products. The
measurement routines are operations within the plant. Each routine has a set of features to be
measured and associated data, such as nominal coordinates, vectors, and tolerances.
The following example shows a bill of process with a measurement routine, Meas Rout 100, which
has the products P1 and P2 assigned to it.
Before you can begin, you must have defined the product and plant process.
Note
This help does not cover creating a product. You should follow the instructions in the
Manufacturing Process Planner to create them.
The MEPrPlantProcess in the bill of process must have the same name as the MEPrPlant in the bill
of resource. The inspection device must have a parent item (MEWorkareas). The following shows
two related bill of resource and bill of process.
Note
Users use the plant information you define here to query for the appropriate measurement
data in Teamcenter lifecycle visualization.
After creating the plant process, attach forms to specify its location, shift start times, and how
frequently you are notified of errors.
Note
For detailed instructions on creating a process structure and form, see the Manufacturing
Process Planner.
• Forms, such as those specifying parsing script parameters and the location of the remote
transfer agents.
Measurement routine
The following elements are attached to a measurement routine to define it:
• Forms, such as those defining the error notification.
• Feature data.
• Inspection devices.
• Create a collaboration context object to store the inspection objects and then use it to load all
objects into Manufacturing Process Planner at the same time.
• Create templates from which users can quickly create new routines and inspection devices.
Templates are generic placeholders. Users create the actual occurrences of these objects from
the templates.
2. Create subfolders within the new folder for storing objects. For example, create BOR, BOP,
Devices, and Context.
3. Click Save.
You receive a message that the collaboration context object has been saved to your Newstuff
folder in My Teamcenter.
4. Click OK.
The collaboration context object appears in your Newstuff folder in My Teamcenter.
5. Copy the collaboration context object to the Context subfolder you created in your project folder.
Note
To send the collaboration context object to Manufacturing Process Planner, right-click it
and choose Send to→Manufacturing Process Planner.
Creating templates
About templates
Administrators create templates from which users can quickly create new routines and inspection
devices. Templates are generic placeholders. Users create the actual occurrences of these objects
from the templates.
Tip
To check the templates, associate them with a routine and send the device or routine to
DPV ETL.
Templates are helpful for users creating multiple routines. You do not need to create them, however,
if you are only creating a single routine. You can simple follow the instructions to create an inspection
device or measurement routine and not create a template from it.
• Creating the forms that define the inspection device, such as specifying parsing script parameters
and the location of the remote transfer agents.
2. From the list, select Dimensional Planning And Validation Inspection Device.
3. Click Next.
7. Click Finish.
Note
Click the plus sign (+) next to the inspection device to view the revision.
2. Create the following forms selecting Apply between each creation so you can continue making
them:
• Dimensional Planning And Validation Device Location
3. Click OK.
4. Check out and edit each form to enter any default information in the fields to assist the user in
defining an inspection device. Click a form name listed in step 2 to learn about its fields.
• Create the forms that define the measurement routine, such as specify error notification.
Note
You can also choose File→New→Operation.
2. In the New Operation dialog box, from the Operation Type list, select one of the following:
Note
There can be other user-defined types of Manufacturing Engineering Inspection for
other types of inspection devices.
3. Click Next.
1. In Manufacturing Process Planner, right-click the measurement routine template and choose
Open with→Attachments as shown.
2. In the Attachments view, select the measurement routine (the top line).
Note
You must select the root process (top line) in the data pane to create a form.
3. Create the following forms, as necessary, selecting Apply between each creation so you can
continue making them:
• Dimensional Planning And Validation Error Notification
4. Click OK.
5. Check out and edit each form to enter any default information in the fields to assist the user in
defining a measurement routine. Click a form name listed in step 3 to learn about its fields.
Type the region number and any customer-defined values or select from a list of values.
Tip
Type North America or South America, and so on.
Create a form
2. In the New Form dialog box, click the form type you want to attach.
4. Select the Open on Create check box to edit the form options.
5. Click OK.
The Attachments view allows you to see the forms attached to an item revision, view and edit the
forms, add new forms, and remove forms from an item revision.
This view is available from nearly every Teamcenter rich client application, including My Teamcenter,
Manufacturing Process Planner, and Part Planner.
1. In a rich client application, such as Manufacturing Process Planner, right-click the revision of the
item, for example a routine, and choose Open with→Attachments as shown.
2. (Optional) Drag the Attachments view to the left to display it in the entire width of the Teamcenter
interface.
5. Edit the form and when you are finished, click Save and Check-In.
You can open all your forms in separate Viewers to compare them or to work with them at the same
time.
1. View your forms in the Attachments view.
2. In the Attachments view, right-click a form, and choose Open with→Viewer, as shown.
3. Freeze the Viewer so it only shows the content for this form even if you select another by clicking
the Disable response to selections tool.
4. Continue creating Viewers for each form and freezing the content.
The result is a collection of Viewer tabs in the right pane, similar to shown.
5. Click between Viewers to edit each form or drag the Viewers so they are stacked horizontally and
you can view all the forms at once, as shown.
The following tables list all the forms used to define components. Use them to make sure that you
have created or edited all the necessary forms.
Forms for bill of process
Is attached to
The form
Plant Routine
The default form of the object
Is attached to
The form
Plant Routine
Dimensional Planning
And Validation Trigger
Configuration
Is attached to
The form
Inspection device (copy in context)
Dimensional Planning And Validation Device
Location
Dimensional Planning And Validation
Measurement Device Definition
Dimensional Planning And Validation
Measurement Context
Dimensional Planning And Validation
Measurement Parse Parameter
• Defining scripts.
For an introduction to defining a bill of resource, see the Dimensional Planning and Validation tutorial.
2. Choose MEPrPlant.
3. Click Next.
Note
• To facilitate measurement data loading, the plant name specified in the bill of
resource must match the plant name in the measurement files.
• The plant name cannot exceed 30 characters or the Application Interface (AI)
objects exported for that plant will not be downloaded to DPV ETL.
6. Click Finish.
The Plant tab appears, as shown.
7. Select the top level in the structure (MEPrPlant) and repeat the workarea creation process to
create the line (MEPrLine) and the station (MEPrStation).
8. (Optional) In My Teamcenter, verify that the bill of resource has been created, and copy and paste
the bill of resource from the Newstuff folder into a designated project folder.
Note
Copy and paste the plant level item into the project folder; the structure beneath it
comes along.
Note
• When you create the inspection device from a template, Teamcenter creates all the
necessary forms you need to define the device. You will edit the forms.
• If you do not have a template, create the inspection device as instructed in Create
inspection device and do not call it a template. Then, create all the necessary forms
listed in Create forms associated with the inspection device.
2. Click the Choose Template tab, type the name of the template in the Template ID box, and
select Use Template. Alternatively, you can search or browse for the template you require.
Tip
• Click Add to Favorites to save the template to a favorites palette so it can be
quickly accessed and used.
c. In the Find Template by Name dialog box, type the search criteria including
wildcards, such as *template*.
d. Click Find.
The templates that match the criteria appear in the dialog box.
3. Click the Configuration tab and choose the cloning rule Cloning. If required, you can also
change the revision rule on this tab.
4. Change the name of the device (for example, Perceptron, PCDMIS, or Zeiss).
Note
All other values (ID, revision, type, description) are automatically set for you.
5. Click OK.
A new tab appears listing the inspection device.
b. Select the bill of resource tab and select the location for the inspection device.
c. Choose Edit→Paste.
8. In the Attachments view, view the forms created for the inspection device, similar to the figure
shown.
9. Check out and edit the forms following the instructions in Specifying the transfer of information.
Duplicate data
Duplicate data occurs when there are communication failures and the inspection devices do not
know that the data was already collected. Duplicated data will have the same routine ID and job
serial number. DPV ETL marks the data as being a duplicate and then adds the latest data as the
final data. The data appears in the log file as:
•
Measurement Event Type = D
Example
For example, vision stations can lose the connection to the machine that provides them with
their job serial numbers so they process the data as the same number again and again.
A remote transfer agent runs on each inspection device computer. A plant can have multiple
inspection device computers. Each inspection device computer can collect data for one or more
inspection devices.
For information on installing the remote transfer agents, see Installing the Dimensional Planning and
Validation solution in the DPV help collection.
• Set the transfer of information
Define where the remote transfer agent and the directory where the data files are located.
1. In the Attachments view, select the inspection device.
Note
You must select the inspection device in the Attachments view to create a form.
2. Check out and edit the form of the type Dimensional Planning And Validation Device Location.
4. Click Check-In.
Note
The end-of-routine flag cannot be set to a character that is present in the routine name.
Note
You must select the inspection device in the Attachments view to create a form.
2. Check out and edit the form of the type Dimensional Planning And Validation Measurement
Device Definition.
Example
If the data file name is UBVIS_380ES_193176.cdi and the end-of-routine flag is
“_”, the routine name is computed from the data file as UBVIS (that is, until the first
occurrence of “_”). Specify this same name in the shopfloor_name box in the
Dimensional Planning And Validation Routine Information form.
4. Click Check-In.
Parsing scripts translate data from many types of inspection devices. The data can be in either ASCII
or Document Markup Language (DML) format. All code that is common to the scripts is stored in
common scripts that are called from the parsing scripts. DPV provides standard scripts.
You can create custom device-specific scripts (for example, to accommodate local configuration
differences, such as language). These device-specific scripts should allow for the processing of input
data files from multiple routines. You can also use script parameters to define custom information.
Defining parsing scripts involves:
All code that is common to all parsing scripts is stored in a common script, which is much like
a sub-routine. Any change to the common code propagates to all scripts that call the common
code script. You can manage a common script in Teamcenter and export it to multiple DPV ETL
installations.
The common code script is a Visual Basic class and contains methods or actions that can be
performed that apply to all the plants in your DPV installation. The standard scripts use the methods
for basic functions, such as extracting the script parameters, writing the error log file, and so on.
Using the Script Debug Utility provided, you can customize these methods, as well as add your own,
such as defining a method for trace code mapping and adding specific common code. You can also
modify the corresponding parsing scripts to call this common code. You can then pass parameters
to the customized script and extend the common script to create individual error log files for each
failed measurement data file. You debug the common script using the Script Debug Utility workspace,
without needing to access DPV. Customizing the common script requires Visual Basic .NET and
Visual Studio (IDE) knowledge.
In the DPV ETL configuration, the common script is stored in the CommonScript folder under
the xmlcfg folder.
Note
• During the DPV ETL installation process, the default common script is automatically
copied to the Commonscript folder only if it does not exist. If the common script
already exists, it is not overwritten.
• You can view information about the common script being used by a DPV ETL
installation (item ID, revision, and date/time of the common device script) through the
DPV ETL Error Viewer.
For more information, see Viewing DPV ETL Status in the DPV help collection.
The following routines, which are used in the standard parsing scripts, can be customized in the
common script. You can also add your own routines.
You can add error messages to a common code parsing script by adding new entries to the
htErrorLog hash table in the common script using the initErrorLogger() method. You can then raise
the errors using pre-defined error codes (in the hashtable) or have the system construct the error
messages based on arguments that are passed in.
The following steps describe how to add and test new error messages through the common script.
1. Add new error messages to the following method in the common script:
This method initializes the error logger and adds the error codes with corresponding error
messages to the error log hashtable htErrorLog. The following are two examples of how to
add new error messages to this method. Example 1 is a simple error message of string type,
while Example 2 uses place holders for variables. The variables receive values from the device
parsing script.
Example 1
Example 2
2. Call this code from the correct place in the device parsing script. The message is then written to
the error text file through the logError method of the common script. Modify the device parsing
script as follows to log the new error:
Because the error messages are about not finding the routine name, log them through the
getRoutineName() method.
3. After modifying both the common script and the device parsing script, export them to DPV
Extraction, Translation, and Loading (ETL). Check for successful compilation of the scripts.
4. After successful compilation, process a measurement data file and check whether or not the new
error message is logged to the error text file.
In this example, Args () is a parameter array, and is a way to pass multiple (variable) numbers of
parameters to the same function. This method reads all the parameters passed and creates an error
message string by formatting them.
Example
Add the error message to the hashtable:
htErrorLog.Add(123456, “Attribute {0] is invalid for Feature {1}”)
Then, in the logError () function, format the string with the arguments passed in:
strErrorMessage = String.Format(strErrorMessage, strAttrName, strFtrName)
End Sub
swLogWriter = File.AppendText(strFilePath)
For i = 0 To alstErrorList.Count - 1
swLogWriter.WriteLine(alstErrorList(i))
Next i
swLogWriter.Close()
End Sub
Note
For more information about:
• The Dimensional Planning And Validation Shift Time form, see Define the shift
times.
• The location of the attributes rules XML file, see Specify the location of the attribute
rules XML file.
The following describes the error messages that appear in the Issues list in the DPV ETL Dashboard
when you view issues with a measurement data file.
For more information, see Monitoring measurement data in the DPV help collection.
Note
Learn more aboutparsing scripts.
This method reads the values of script parameters, such as ROUTINENAMEKEY, EVENTYPEKEY,
ITEMTYPEKEY, PROJECTNAMEKEY, and so on.
To add a new script parameter, for example NEWSCRIPTPARAM, add the following code to this
method to read the value:
Note
You also must declare the new variable strNewScriptParameter at the start of the class:
Note
All the parsing scripts must be modified to use the common script object for methods
that are implemented in the common script. An object of CommonScript type is already
created in the default parsing scripts, through which the new methods can be called.
To set the default values of script parameters for all parsing scripts using the common script, use
the following method:
The script first sets the default value throughout the function. If any value is present for a script
parameter, then that value overwrites the value set in this function.
For example, if you want to specify a default value for the NEWSCRIPTPARAM that was shown
extracted in the Example of extracting a new script parameter, add the following line of code:
strNewScriptParameter = “DefaultStringValue”
Example of extracting parameter-based routine names from the measurement data file
To extract the routine name from the data file based on script parameters, implement the logic to use
the script parameter in the parsing script. Script parameters defined in the device configuration XML
are passed to the getRoutineName() method so you can extract the routine name from a desired
location within the measurement data file. The common code parsing script only provides an interface
method that passes the script parameters to the compiled script object. Because this parameter is
required for extraction of the routine name, it should be specified on the device.
The following is an example of how to read the routine name based on the script parameter and not
the default location from a CDI measurement data file. By default, in a CDI measurement data file,
the routine name is read from the SpecDocName field as shown.
You may also want to read it from another field, for example, RoutineName.
1. Modify the following to add logic to the CDI device parsing script to read the routine name based
on the script parameter and not the default location:
2. After modifying the device parsing script, export it to DPV Extraction, Translation, and Loading
(ETL). Check for successful compilation.
3. After successful compilation, process a measurement data file and check whether or not the
routine name is read using the RoutineNameKey script parameter.
Note
See your DPV support personnel for information about the debug workspace.
Use the Script Debug Utility to debug a parsing script, including debugging the use of any common
code scripts.
Tip
To debug the common code script, paste the common code into the CommonScript.vb
file as shown in the figure.
If the common parsing script compilation fails when DPV ETL starts, the DPV Parser is not started.
The following error message is logged in the DPVParser log file:
[ERROR] Compilation errors in the Common Script. Exiting the DPVParser application...
If the common script is updated and fails to compile, when DPV ETL is running, DPV ETL reverts to
the earlier working script. The following message is logged in the DPVParser log file:
[ERROR]: Compilation errors in the updated Common Script. Reverting to the earlier script...
You can export a common parsing script to multiple DPV ETL installations. When you send the
common script to DPV ETL, DPV ETL finishes processing any previously started parsing scripts and
uses the new common script for any new parsing tasks. You do not need to restart DPV ETL.
Note
The common parsing script does not need to be under a station since it is common to all
stations. You can store it in the Newstuff folder or any folder.
b. Choose File→Item.
d. Click Next.
g. Click Finish.
000243/A:1-CommonScriptDevice
View
000243/A
CommonScript
b. In the New Process dialog box, from the Process Template list, select Export Common
Device to AI.
The file names automatically fill in.
c. Verify that the targets specified in the New Process dialog box are correct.
d. Click OK.
An application Interface (AI) object is created. The AI object contains a .plmxml file with the
information you exported.
Managing AI objects created during export
While defining the quality inspection process, you can define script parameters that can be passed to
the parsing scripts to modify how they handle data. By defining parameters in scripts, you can use
the same parsing script for different inspection devices. This is particularly helpful when you have
localization issues, such as how the date is displayed or the language used. Instead of creating two
scripts, you can create one script using parameters. In addition, you can pass parameters from a
device to a parsing script that uses the common script.
You specify the parameters using the Dimensional Planning And Validation Measurement Parse
Parameter form that you can attach to the inspection device (bill of process) and/or the routine (bill
of resource), as shown in the figure.
When parameters are passed from the Dimensional Planning And Validation Measurement
Parse Parameter form, they overwrite the default parameters set in the parsing script. The order
of precedence for setting script parameters is:
1. Form attached to routine
Default script parameters that the common parsing script reads are available for any parsing scripts
to use.
• If the inspection device type is not contained within the measurement data file, then the default
is Inspection Device. You can overwrite this by defining the following parameter value in
the parsing parameter form (Dimensional Planning And Validation Measurement Parse
Parameter) attached to the inspection device:
Adding this parameter results in the device_type being set to Vision, as shown in DPV
Measurements.
• Using parameters, you can use a single script to parse different comma-separated value (CSV)
files with different languages. If time and data is in column 1 in one language, such as English,
and in column 2 in another language, such as Spanish, then set parameters for each of these
conditions.
• Use parameters in a single script to change the label for time from English to Spanish.
The parsing script for this measurement data would have the following defined within it for the
column headers:
1 Date and time Indicates the column header for the data and time. Note
that multiple methods for defining the date and time are
supported, based on the structure of the data.
2 Serial number Indicates the column header for the serial number.
3 Non-feature data (multiple) Indicates the column header for non-feature data (for
example, Date, Collector ID, and so on).
4 Trace codes Indicates the column header for trace codes. Trace codes
are information added to a measurement data file to
define specific conditions that apply to a particular serial
number (for example, product variants, such as having a
sunroof or no sunroof).
You could replace this script with a generic script that defines the column headers using parameter
forms attached to the inspection device. There would be five forms.
• Two forms for non-features because the param_value length is restricted to 64 characters, which
does not allow all the non-feature values to be defined in one field.
The values for the first form for non-features are:
The following table lists the script parameters that the common parsing script reads, by default, and
available for the device parsing scripts to use. The table lists all parsing scripts. You can modify any
existing script to use the default script parameters.
When parameters are passed to the parsing script, they overwrite the default parameters set in
the parsing script.
Note
If
NONFEATURES
exceeds 64
characters,
split the line
into two
lines using
NONFEATURES1.
For
example, the
following line
contains 69
characters:
"GAUGE
ID,JSN,MO,DAY,YR,
HR,MIN,SEC,MODEL,
C_RS,SHIFT,DATA
TYPE,FIXTURE"
Therefore,
split the line
as follows:
NONFEATURES
"GAUGE
ID,JSN,MO,DAY,
YR,HR,MIN,SEC,
MODEL,C_RS,SHIFT,
DATA
TYPE"
NONFEATURES1
"FIXTURE"
Split the line
after the last
full token
before the
comma.
1. In Manufacturing Process Planner, in the Attachments view, select the inspection device.
Note
• You must select the inspection device in the Attachments view to create a form.
• The script parameter form for the routine name must be added to the inspection
device and not the routine in Teamcenter.
2. Create a form of the type Dimensional Planning And Validation Measurement Parse
Parameter.
Example
Use this when a feature has
one name when it is in the
raw measurement data file and
another name when it is in
Teamcenter.
Example
When you are renaming a feature,
this specifies the original name of
the feature.
Example
When you are renaming a feature,
this specifies the original value of
the feature.
1. In Manufacturing Process Planner, select the inspection device, and choose File→New→Dataset.
2. Choose Text.
3. Click OK.
4. Verify that the parsing script appears as an attachment on the inspection device.
5. In the Import box, click ... and navigate to the inspection device parsing script.
6. Click OK.
• PCDMIS_2.txt
• PCDMIS_3.txt
• PCDMIS_3.1.txt
• PCDMIS_3.1.txt
• PCDMIS_3.2.txt
Zeiss/UMESS • UMESS_1.txt
• UMESS_2.txt
Zeiss SMC/UMESS UMESS_3.txt
Zeiss SMC/UMESS Format 2 5. UMESS_4.txt
Wentzel/Metrosoft • Metrosoft_1.txt
• Metrosoft_2.txt
Zeiss/Metroligic/DMIS DMIS.txt
LKDMIS LKDMIS.txt
Perceptron IPNET PERCEPT_1.txt
Perceptron P1000 Perceptron_CDI.txt
Perceptron Spec/Reject SPEC_REJECT.txt
• Tolerance specification
• Feature specification
Note
If this file downloads as a zip file, change its extension to docx.
• Line
• Plane
• Circle
• Cylinder
• Sphere
• Cone
• Open slot
• Closed slot
• Point Curve
• Torus
Features of the type ellipse, pattern, and constant Xsect are not supported.
Note
The Engineering XML file generated from the XML Generation Utility contains feature
types that are not present in the Teamcenter feature list of values (LOVs). Therefore,
when you import the Engineering XML, these features are ignored and are not imported in
the Excel Engineering workbook.
To have the feature types included in the workbook, add them to the Teamcenter features
LOV using Business Modeler IDE, before importing the engineering XML into Teamcenter
(using Tools→Import Feature Data).
Information about the measurement data is read from the header data by default. The information
includes routine name, build label, and data and time. The following shows the information expected
in the header for routine:
If this data is to be read from the qis_def section of a DML file and not the header, as shown for the
routine name, add script parameters to the parsing scripts to extract the data from the qis_def section:
Note
The param value can change depending on the type attribute of the qis_def node:
<qis_def label="DCX_19" type="Routine" value="DMLRoutine" />
2. In the same way, add script parameter forms for the following to be read from the qis_def section
of the DML file, as shown in the figure:
Trace Codes: The value can be a comma-separated list of all trace codes to be read
Param_name = TraceCodeKeys
Param_values = Category,Serial Number
<qis_def label="DCX_20" type="Category" value="PS" />
<qis_def label="DCX_21" type="Serial Number" value="050110" />
• DateKey
• TimeKey
• EvenTypeKey
• ItemTypeKey
• FacilityNameKey
• ProjectNameKey
• PhaseNameKey
• SiteLocationKey
• DeviceTypeKey
If they are not in the qis_def section, add the corresponding forms (Dimensional Planning And
Validation Routine Information for Item_name and Dimensional Planning And Validation
Measurement Context for Phase_name) to the routine. These values are required for the file to
pass validation.
For more information on creating a routine and the forms needed, see Create a measurement routine
from a template and Create forms associated with the measurement routine.
to the attribute LOV using Business Modeler IDE. See Adding feature data and Defining custom
feature attributes.
Example
If a feature contains two custom attributes, DMIN and DMAX, that are not defined in the
Teamcenter list of values (LOV), they are not imported to the Engg Excel worksheet.
Therefore, after importing the engineering XML, manually add DMIN and DMAX to the
Excel worksheet (both the FeatureInfo and ENGG tabs) and fill in the corresponding
columns (under the feature) before exporting the routine to workflow.
2. Add the attribute values to the corresponding columns under the feature:
2. 2. Add the attribute values to the corresponding columns under the feature:
For an introduction to defining engineering data, see the Dimensional Planning and Validation tutorial.
Note
You can also choose File→New→Process.
b. In the New Process dialog box, from the Process Type list, select MEPrPlantProcess.
c. Click Next.
Note
The plant name cannot exceed 30 characters or the Application Interface (AI)
objects exported for that plant will not be downloaded to DPV ETL.
f. Click Finish.
A new tab appears for the process.
g. (Optional) Select the process you just created, and create another process that defines an
assembly line using the steps outlined in step 2. Use a Process Type of MEPrLineProcess.
h. (Optional) Select the assembly line you just created, and create another process that defines
a zone using the steps outlined in step 2. Use a Process Type of MEPrZoneProcess.
Tip
To view its contents, you may have to expand the process (click the +).
i. (Optional) Select the zone you just created, and create another process that defines a station
using the steps outlined in step 2. Use a Process Type of MEPrStatnProcess.
Note
You must select the root process (MEPrPlantProcess) in the data pane to create a
form.
6. Click OK.
Alternative abbreviations
In addition to the standard Windows time zones listed in the Date and Time Properties dialog box,
the time_zone box accepts the following common abbreviations.
Abbreviation Meaning
MIT Midway Island Time
HST Hawaii Standard Time
AST Alaska Standard Time
PST Pacific Standard Time
MST Mountain Standard Time
MST7 Arizona
CST Central Standard Time
EST5 Indiana (East)
EST Eastern Standard Time
GMT Greenwich Mean Time
WET Western European Time
CET Central European Time
EET Eastern European Time
IST India Standard Time
CHST Chinese Standard Time
JST Japan Standard Time
KST Korean Standard Time
Use the Dimensional Planning And Validation Shift Time form to specify shift times for a plant.
There should only be one form per plant.
Note
Only production days need to be defined. Any day with no shift defined is assumed to
not be a production day.
1. In Manufacturing Process Planner, click the tab associated with the plant process.
Note
You must select the plant process in the Attachments view to create a form.
4. Create a form of the type Dimensional Planning And Validation Shift Time.
5. Type the start times for the shifts in the boxes, for each day of the week. It is in 24-hour format:
hh:mm.
Example
If the start time is 8:00 a.m., type 08:00.
Tip
• You can specify a shift that continues until the next day. For example, the following
specifies a late Monday shift that runs until 5:59 the next day:
Monday 3
Start: 22:00 End: 5:59
• You can include hours from a previous day in a shift. For example, the following
specifies that the Tuesday shift starts at 10:00 on Monday, because –2 hours are
subtracted from the start of Tuesday.
Tuesday 3
Start: –2:00 End: 5:59
6. Click OK.
Note
Error notification can also be defined for a particular measurement routine. If you define it
for a routine, it overrides the value defined for the plant.
1. In Manufacturing Process Planner, click the tab associated with the plant process.
Note
You must select the plant process in the Attachments view to create a form.
4. Create a form of the type Dimensional Planning And Validation Error Notification.
5. From the notification_type list, select when you want to be notified of errors.
Example
If the first three data files have errors, and the fourth and fifth do not, while the sixth
does, then you receive the following messages, depending on how you set the option:
• Set it to All, receive messages for first, second, third, and sixth files.
• Set it to First, receive messages for the first and sixth files.
6. Click OK.
If the measurement data is stored in a remote measurement database, add a reference to the new
plant process structure in that measurement database. After adding the reference, Teamcenter stores
all data that is processed for that plant in the measurement database. In addition, if a link to a
remote measurement database is not available, you can create a link to it if both the Teamcenter and
measurement databases are Oracle databases.
Note
• This step does not need to be performed if the measurement data resides within the
Teamcenter database instance.
• The group to which you belong must be part of the DPV Admin group for you to have
permission to add the plant to a measurement database.
• You must know which database link is associated with which measurement database.
For information about creating links to measurement databases, see Creating links in
Teamcenter to the measurement databases in the Installing the Dimensional Planning
and Validation solution guide in the DPV help collection.
1. In Manufacturing Process Planner, right-click the top of the plant process structure (the
MEPrPlantProcess item) and choose Send Plant ID.
The Send Plant ID dialog box appears.
Note
For information about creating links,
see Creating links in Teamcenter to
the measurement databases in the
Installing the Dimensional Planning
and Validation solution guide in the
DPV help collection.
3. Click OK.
Either of the following messages appear:
4. Click OK.
After creating the process structure, define the measurement routine as an operation within the
plant. The type of operation you create depends on the type of inspection device. After defining
the routine, add feature data.
Note
• Measurement routines cannot be shared between plants. They belong to only one
plant.
• When data for a routine is not collected in a single file, you can merge the files into one
event stored in the Teamcenter measurement database. You specify the merging when
you define the feature data, using the option loading split ID. See Defining split events.
• Define triggers
Note
• When you create the measurement routine from a template, Teamcenter creates all
the necessary forms you need to define the routine. You will edit the forms.
• If you do not have a template, create the measurement routine as instructed in Create
a measurement routine and do not call it a template. Then, create all the necessary
forms listed in Create forms associated with the measurement routine.
1. In Manufacturing Process Planner, select the tab associated with the process structure.
2. Select the plant or a location in the plant (assembly, zone, or station) for which you want to
define a measurement routine.
4. Click the Choose Template tab, type the name of the template in the Template ID box, and
select Use Template. Alternatively, you can search or browse for the template you require.
Tip
• Click Add to Favorites to save the template to a favorites palette so it can be
quickly accessed and used.
c. In the Find Template by Name dialog box, type the search criteria including
wildcards, such as *template*.
d. Click Find.
The templates that match the criteria appear in the dialog box.
5. Click the Configuration tab and choose the cloning rule Mapping_Consumes. If required, you
can also change the revision rule on this tab.
Note
All other values (ID, revision, type, description) are automatically set for you.
7. Click OK.
8. In the Attachments view, view the forms created for the measurement routine.
9. Check out and edit the forms following the instructions in:
• Define error notification during data loading
Note
Error notification is always defined for the plant. If you define it for a routine, it overrides
the value you defined for the plant.
1. In Manufacturing Process Planner, click the tab associated with the process structure.
Note
You must select the routine in the Attachments view to create a form.
4. Check out and edit the form of the type Dimensional Planning And Validation Error
Notification.
Example
If the first three data files have errors, and the fourth and fifth do not, but the sixth does,
then you receive the following message, depending on how you set the option:
• Set to All, receive messages for first, second, third, and sixth files.
• Set it to First, receive messages for the first and sixth files.
6. Click Check-In.
1. In Manufacturing Process Planner, click the tab associated with the process structure.
Note
You must select the routine in the Attachments view to create a form.
4. Check out and edit the form of the type Dimensional Planning And Validation Export To
Regions.
6. Click Check-In.
You can also define split events, define custom feature attributes and generate feature data from
measurement data.
Feature validation
When you edit a DPV Excel Engineering workbook through Teamcenter, it is associated with a
rule set that validates the feature data you enter. The rule set is a collection of macros stored in a
Microsoft Excel binary workbook (.xlsb). Siemens PLM Software provides a default rule set. We
also recommend that you create your own custom rule set to validate the feature data against your
company’s standards. In particular, use it to define the specification set worksheets names.
You associate a DPV Engineering Excel workbook with a custom rule set when you import it. You can
also change the association using the Apply Rule Set command. The workbook is always associated
with the default rule set that Siemens PLM Software provides.
When you edit the workbook, you can activate and run validations using both the default and the
selected custom rule set. You can run static validations of the entire workbook or runtime validation of
the current cell. The rule sets create discrepancy worksheets in which to display any validation errors,
for example, you entered a name that contains characters that are not allowed. They highlight cells
with errors in red and cells with warnings in yellow. When you correct the errors, the corresponding
entries are deleted from the discrepancy worksheets.
In addition to rule set validation, the Teamcenter server validates the feature data when you import
and save the Excel Engineering workbook. If the server validation fails, the routine data cannot be
sent to client applications, such as DPV ETL, DPV Reporting & Analysis, and DPV-SSAS.
Note
Any warnings in the DPV Excel Engineering worksheet (highlighted in yellow) pass the
Teamcenter server validation.
In addition, the master form of the routine revision with which the DPV Excel Engineering dataset is
associated is updated with information about the validation.
Note the following:
• If the server validation fails, the routine data cannot be sent to client applications, such as DPV
ETL, DPV Reporting & Analysis, and DPV-SSAS.
• The date and time validations of routine revisions created before 9.0 are blank. Therefore, they
are sent to client applications even if they have errors. To change this, associate the routine
revisions created before 9.0 with a rule set using the Apply Rule Set command. Then, open or
save the dataset. The server validation automatically runs and the master form of the routine
revision is updated.
Feature name
• The feature name is unique.
• The feature name is an alphanumeric string. All characters are allowed except:
,<>\/“‘&`@#(){}[]|: ;*^%
Feature ID
• Feature IDs are automatically generated, and the Feature ID column is read only (cannot be
edited).
Numeric fields
• The following fields must be in numeric or empty elements (required fields cannot be blank).
o In the Feature Info worksheet: x, y, z, i, j, k, i2, j2, k2, Significance, and Nominal.
■ i, j, k, i2, j2, k2 - No warning is issued when any of these fields are blank.
■ Otherwise, if any one or two of the fields are blank, there is a warning.
o String-based numbers (for example, 1.000) used in releases before the DPV 9.0 release are
supported but are converted to a number when data is sent to client applications, such as
DPV Reporting & Analysis, DPV ETL, and DPV-SSAS.
Errors
o There are feature labels in the specification or feature mapping worksheets that are not in the
Feature Info worksheet. In the feature mapping worksheets, only features of the dataset’s
routine revision are verified.
o There are attribute codes in the specification worksheets that are not in the Feature Info
worksheet.
Warnings
o There are feature labels in the Feature Info worksheet that are not in one or more of the
specification set code worksheets.
o There are attribute codes in the Feature Info worksheet that are not in one or more of the
specification set code sheets.
Required fields
• Error messages appear if any of the following are not entered or are incorrect.
o All header information in the Feature Info, specification set code, and feature mapping
worksheets.
■ Feature ID
■ Feature label
■ Feature label
Note
A specification set code name can be up to 26 characters. It cannot contain the
following characters:
,<>\/“‘&`@#(){}[]|: ;*^%
o Comment columns
You can add columns to the feature information sheet after the last feature attribute columns.
These are treated as comments. No system action is taken on these comment columns (for
example, they are not visible in any application except Excel).
If you attempt to add a comment column before the last feature attribute column, it is flagged
as an error.
o Comment worksheets
You add additional worksheets to the DPV Excel Engineering workbook for storing comments.
• Deleting columns
Users cannot remove required columns.
o Feature ID
o Feature Label
o Feature Type
o Feature Description
o Active Status
o Need
o Loading Split Id
o x, y, z, i, j, k, i2, j2, k2
■ Measurement
■ Need
■ Nominal
Required columns for a specification worksheet
o Feature Label
■ TAR
■ USL
Required columns for a feature mapping worksheet
As you edit a DPV Excel Engineering workbook with rules validation activated, any errors are
displayed in the cells.
Any problems with the feature data are highlighted in the cells of the workbook. Errors are highlighted
in red and warnings in yellow. In addition, comments may appear next to the cell explaining the error.
Note
Any warnings in the workbook pass the Teamcenter server validation.
In addition to displaying errors in cells, the validation rule sets create discrepancy worksheets
to display validation errors:
• The default rule set that Siemens PLM Software provides creates a worksheet called
Discrepancy to display any default validation errors, such as you entered a name that contains
characters that are not allowed.
• A custom rule set creates a worksheet (usually named User Discrepancy) to display custom
validation errors, such as you entered a name that is inconsistent with your company’s standards.
Clicking a cell in a discrepancy worksheet places the cursor in the cell with the error so you can correct
it. When you correct the error, its corresponding entry is deleted from the discrepancy worksheet.
1. Depending on your version of Microsoft Office, access the Excel Options dialog box.
Example
In Excel 2003, click the Microsoft Office button ( ) and click Excel Options.
2. On the left, click Customize Ribbon and make sure Add-Ins is in your list of displayed tabs. If it
is not, add it and click OK.
3. On the left, click Trust Center and then click Trust Center Settings.
6. Under Developer Macro Settings, select Trust access to the VBA project object model.
After opening a DPV Engineering Excel workbook for feature definition, you must run static validations
of the entire workbook.
After running static validations, you can toggle on and off runtime validation, which validates the
current cell you are editing. Turning off runtime validation speeds up the entry of multiple cells
because you do not have to wait for validation after each entry. Note that if you turn on runtime
validation, you can still quickly copy and paste cells across worksheets because runtime validation
only validates the current cell and not the entire workbook. You must first run static validations to
turn on runtime validation.
The options for running static and runtime validations are available from the Add-Ins menu, which is
automatically displayed when you open a DPV Engineering Excel workbook.
If there are XLSB files associated with the DPV Engineering Excel worksheet, the Static
Validations button is enabled.
After the first run, the Static Validations and Runtime On/Off buttons in the Discrepancy
worksheet are disabled.
Navigating to another worksheets enables the buttons, as shown when you navigate from the
Discrepancy worksheet to the Feature Info worksheet.
4. (Optional) Navigate to another worksheet and toggle Runtime On/Off as you edit the workbook.
Note
The date and time are the local date and time of the Teamcenter server.
Note
The date and time validations of routine revisions created before 9.0 are blank.
When you import feature data, it is associated with the default DPV validation rule set and you
are prompted to associate the dataset with a custom DPV validation rule set. You can change the
custom rule set with which it is associated at any time. You apply the custom rule set to the routine
revision with which the workbook is associated.
Note
You can only apply a custom rule set to a routine revision to which you have write
permission. You often do not have permission to a routine revision that has been released.
If the routine revision is released, revise it before using the Apply Rule Set command.
1. In Manufacturing Process Planner, right-click the routine revision with which you want to associate
the custom DPV validation rule set, and choose Apply Rule Set.
The Apply Rule Set dialog box appears, listing all the custom rule sets available.
2. Select the custom rule set to use for validation of the feature data, and click OK.
Learn more about DPV rule set validation.
It is recommended that you create a custom DPV validation rule set. In particular, create a custom
rule set to specify the specification set code worksheet names. Then, when a user adds a worksheet
and its name is in the list of specification set code worksheets, the sheet is treated as a specification
set code worksheet. Otherwise, it is treated as a comment sheet unless it is a Feature Info or
feature mapping sheet.
Note
A specification set code name can be up to 26 characters. It cannot contain the following
characters:
,<>\/“‘&`@#(){}[]|: ;*^%
1. Use the standard Teamcenter functionality (Access Manager and Organization) to set the users
who can create custom DPV validation rule sets.
2. Set the Teamcenter DatsetTypesPref preference to include the Dimensional Planning And
Validation Rule Set Dataset value. DatsetTypesPref sets the dataset types that are listed when
users choose the System→New→Dataset command.
3. Create a Microsoft Excel binary workbook (.xlsb) containing the validation macros.
4. In Teamcenter, create an item revision of the type Dimensional Planning And Validation
Rule Set.
Learn about types of rule sets.
5. Create a dataset of the type Dimensional Planning And Validation Rule Set Dataset containing
the Microsoft Excel binary workbook (.xlsb) associated with the Dimensional Planning And
Validation Rule Set item revision.
6. Release the Dimensional Planning And Validation Rule Set item revision. Once the
Dimensional Planning And Validation Rule Set item revision is released, it can be associated
with a measurement routine or operation.
When you release the custom rule set, it is listed under Specifications. Use the copy action
Copy as Object.
To differentiate between the default DPV validation rule set that Siemens PLM Software provides and
those that you create, they are each defined as different item types in Teamcenter:
• Default rule set
The rule set that Siemens PLM Software provides is of the type Dimensional Planning And
Validation Rule Siemens. Only one instance of this item type is allowed in a Teamcenter
database. This item instance is created by default when creating or upgrading the Teamcenter
database to version 9.0 or later. Therefore, no user can create or delete the instance of this item
type. The rules in the default rule set are password-protected so they cannot be modified.
The Excel Engineering workbook sample contains worksheets for defining the features and tolerances
and displaying errors and comments:
• FeatureInfo
Worksheet where you enter all the feature-level information and nominal data of the feature
attributes. Each row represents a different feature. Each feature can have many feature attributes.
• Discrepancy worksheets
The default rule set creates a worksheet called Discrepancy to display any validation errors,
such as if you entered a name that contains characters that are not allowed. A custom rule
set also creates a tab (usually named User Discrepancy) to display custom validation errors,
such as if you entered a name that is inconsistent with your company’s standards. When you
correct errors in the feature data, the corresponding entries are deleted from the Discrepancy
and User Discrepancy worksheets.
Working with validation errors
• Comment worksheets
You can add comment worksheets or comment columns to the DPV Excel Engineering workbook
to assist you in understanding the entered data. Comment columns must be added after all
other required columns.
Tip
Use Excel functionality, such as sorting and filtering, to help you enter and manage the data.
Note
Names of features must be unique within the routine.
Tip
• Use Excel functionality, such as sorting and filtering, to help you enter and manage
the data. In addition, to keep the headers visible when scrolling in the worksheet,
freeze the pane.
• Hide rows and columns in the workbook as you need to assist in entering data. All
validation rules still work regardless of whether or not the rows and columns are visible.
Note
Use the dpvExcel.xlsx sample file located in the dpv_install.zip to get started.
Note
For the Dimensional Planning and Validation rule set validation to be triggered, you
must work with the DPV Excel Engineering workbook inside of Teamcenter.
2.
3. In the FeatureInfo worksheet, fill in the following information to define features and feature
attributes.
Feature-level information
A Feature ID Leave blank. DPV validation
automatically creates it.
Note
Used internally by
DPV.
Note
• Enter only
alphanumeric
characters. Do
not use special
characters.
• The feature
name is used
for reporting.
• Hole
• Pin
• Slot
• Tab
Note
The alternate
feature label
is used in the
Analysis window
in DPV Reporting
& Analysis and in
DPV ETL if a feature
cannot be identified
by the feature label.
Note
There is no limit
to the number of
files to be merged.
Assign each split
a different name.
For example,
Left, Right, Top,
Bottom, Middle,
and so on.
Note
• X, Y, and Z are
the anchor point
coordinates
used in
interactive
reporting.
• Nominals
cannot be the
same as the
specification
limits USL,
LSL, and
Target. Add
specifications.
• All child
elements
of feature
nominals are
required. If
there are no
i2, j2, and k2
values, enter
the feature
nominals
with empty
elements.
Attribute-level information
For each attribute, enter its name under the Attributen header.
R (for attribute 1) Significance Enter the significance of the
feature attribute:
• 0 – Insignificant
• 1 – Significant
Note
If this value is blank,
data is not loaded
through the extract,
translate, and load
(ETL) process.
Note
Typically, 0 for
deviations.
5. Choose File→Save.
A message appears asking you if you want to save the workbook as a macro-free workbook.
6. Click Yes.
Note
• There can be only one derived feature attribute per derived feature.
• Derived features are not supported when importing feature data through an .xml file.
You can only define the derived feature while editing in Excel.
2. To add a derived feature, enter the derived feature name and set its type to Derived in the
Feature Type column (column C). This derived feature would not have any normal attributes. It
has only derived attributes, as shown in the example:
3. To add a derived attribute, add four columns as if creating a new attribute (a set of four columns:
Significance, Measurement Approach, Need, and Nominal.)
Note
The columns must be in the order specified.
4. Add a fifth column after Nominal called Expression, as shown in the example.
Note
This column would be under the same heading (attribute code merged cell) as the
other four columns.
6. Type the expression using the feature label and attribute codes, enclosing the attributes in square
brackets [], as shown in the example.
Example
For example, [ftr_1.attr_1]*[ftr_1.attr_2]
Note
• Separate the feature label and attribute code using a dot.
Note
Adding specification set codes to derived attributes is the same as setting
them for a normal attribute. Make sure that the Derived:<att_code>
is placed in the header and define the specifications in the appropriate
sheet.
Midpoint expression
REF_POINT([FEATURE_NAME],X=x.xx,Y=x.xx,Z=x.xx, I=x.xx,J=x.xx,K=x.xx)
Required
Either [FEATURE_NAME] or X=x.xx,Y=x.xx,Z=x.xx
X=x.xx,Y=x.xx,Z=x.xx takes precedence over the feature name.
Optional
Either [FEATURE_NAME] or X=x.xx,Y=x.xx,Z=x.xx
I=x.xx,J=x.xx,K=x.xx
For a reference point, either the feature name or the X, Y, and Z components must be specified.
• If X, Y, and Z are specified, they define the reference location; otherwise, a feature name must be
specified.
• If both a feature name and X, Y, and Z are specified, X, Y, and Z take precedence and define the
feature location. If either X, Y, or Z are not specified and feature label is specified, the feature
label takes precedence.
Add specification types and limits to feature attributes. Specification types and limits set the
deviations that are allowed from the nominal values. You set the specifications within the context
of a particular routine. DPV provides the default specifications in the ENGG and DML worksheets
in the dpvExcel.xlsx sample workbook. You can add additional worksheets containing other sets
of specifications. The name of the sheet is the same as the specification set. You can alsospecify
one-sided tolerances so DPV Reporting & Analysis ignores one side when performing Statistical
Process Control (SPC) calculations.
You set user-defined specification codes to define the specification types. DPV Reporting & Analysis
and historical reporting (DPV-SSAS) use the codes to determine which specification limits to use
when performing SPC calculations. You can change between specification sets in DPV Reporting &
Analysis by setting the properties of a result set.
If you do not define the specifications, summary calculations on the measurement data on which
the specifications are based are not performed.
Define specifications in a DPV Excel Engineering workbook
• Create a DPV Excel Engineering workbook using the dpvExcel.xlsx sample file, create a
dataset, and upload it to Teamcenter.
Note
• For the DPV rules validation to be triggered, you must work with the workbook
though Teamcenter.
• If you have already created feature and attributes in the DPV Excel Engineering
workbook and DPV rule set validation is configured, the worksheet is already
populated with the feature and its attributes. All you will need to do is to add the
tolerance information.
3. Create or rename a worksheet to define one or more of the following specification limit values.
Name the worksheet the name of the type of specification being defined.
Note
• If you enter a name for the specification worksheet that is not defined in the custom
validation rule, the sheet is created as a comment sheet.
Create a custom DPV validation rule set.
• Target, LSL, and USL are mandatory fields. LSL and USL can be zero but they
cannot be null.
Note
• If you have already created
feature and attributes in the
workbook and DPV rule set
validation is activated, the
worksheet is already populated
with the feature name.
Note
If you have already created feature
and attributes in the workbook and
DPV rule set validation is activated,
the worksheet is already populated
with the attributes.
Note
• For build-to-normal scenarios,
the target value is equal to the
nominal.
4. (Optional) Add worksheets containing the feature attributes whose control limits you want to
freeze, as shown in the table. You must name the worksheets exactly as shown.
The following is an example of a workbook with the worksheets and a limit set for the CN26
feature attribute .
5. Choose File→Save.
A message appears asking you if you want to save the workbook as a macro-free workbook.
6. Click Yes.
If your result set has one-sided tolerances, you can specify that either the upper (USL) or lower (LSL)
specification limits be ignored by entering -1E+08 in the appropriate field in the DPV Excel Engineering
worksheet. When you enter -1E+08 as a specification limit, DPV Reporting & Analysis ignores that
side of the tolerance when calculating its three outputs: Cpk, Ppk, and the estimated percent out of
spec. For example, this would be helpful if you wanted to ignore processes in which lower and upper
specifications are unacceptable or are not applicable, such as the one-sided diameter of a hole.
The following shows an example of setting USL to -1E+08 for the CN0026 feature and the results
that appear in the DPV Reporting & Analysis Analysis window.
To better support situations in which your process is tightly controlled and you do not want calculated
control limits to appear in in DPV Reporting & Analysis, you can freeze specification limits for
individual feature attributes. This option ensures that the DPV Reporting & Analysis uses only those
frozen limits and does not recalculate limits for every new query or data source update.
In the DPV Excel Engineering workbook, add the following workbook worksheets to contain the
control limits for specific feature attributes.
The frozen worksheet labels appear as specification limit types in the Spec Limit list in the Analysis
window:
The following is an example of a workbook with the worksheets and a limit set for a feature attribute of
CN26.
Tip
You can also define custom feature attributes.
Note
This sample .xml file contains three features. The first two features already exist in
Teamcenter (they have a non-blank IDs) and are being modified, while the third feature is
being added (its ID is blank). The second feature defines attributes for Z_DEV, X_ACT,
and Y_DEV.
Tip
Before starting you may want to define custom feature attributes.
1. Create an .xml file in an XML or text editor. Enter the following, which acts as a container for the
feature data and is common for any .xml file.
<?xml version=”1.0” encoding=UTF-8”?>
<engineering_data version=”1.0”>
</engineering_data>
<engineering_data version=”1.0”>
<!—-Add routine element here-–>
</engineering_data>
A routine is identified by its item ID (id), name (name), and revision (version). For a detailed
explanation, see the table of XML elements.
Note
The routine element helps you manage the .xml file. It tells you which routine the
feature data belongs to. It does not perform any real function.
Example
<routine id="000036" name="Routineg1_1" version="A">
</routine>
<engineering_data version=”1.0”>
<routine id="000036" name="Routineg1_1" version="A">
<!—-Add feature data here-–>
</routine>
</engineering_data>
Feature data consists of feature elements—one element for every feature to be added to the
routine. Each feature has properties (name, alternate name, type, status, need, description,
and loading split ID) that are attributes of the feature element. For a detailed explanation, see
the table of XML elements.
Example
<feature name="featg2" alternate_name="g2" type="Slot"
status="active" need="OPTIONAL"
description="Another feat"
loading_split_id="value">
<engineering_data version=”1.0”>
<routine id="000036" name="Routineg1_1" version="A">
<feature name="featg2" alternate_name="g2" type="Slot"
status="active" need="OPTIONAL"
description="Another feat"
loading_split_id="value">
<!—-Add feature content here-–>
</feature>
</routine>
</engineering_data>
Feature content consists of feature nominals and attributes, which have tolerances.
• Feature nominals
Feature nominals consist of X, Y, Z, I, J, K, I2, J2, and K2. For a detailed explanation, see
the table of XML elements.
Example
<feature_nominals>
<x>0</x>
<y>0</y>
<z>0</z>
<i>0</i>
<j>0</j>
<k>0</k>
<i2>0</i2>
<j2>0</j2>
<k2>0</k2>
</feature_nominals>
Note
All child elements of feature nominals are required. If there are no i2, j2 and k2
values, enter the feature nominals with empty elements as follows:
<feature_nominals>
<x>0</x>
<y>0</y>
<z>0</z>
<i>0</i>
<j>0</j>
<k>0</k>
<i2></i2>
<j2></j2>
<k2></k2>
</feature_nominals>
• Feature attributes
Each feature has a set of attributes. Each attribute is captured as an attribute element. The
attribute properties include type, significance, need, measurement approach, and nominal,
which appear as attributes of the element. For a detailed explanation, see the table of XML
elements.
Tip
You can define custom feature attributes.
Example
<attribute type="X_ACT" significance="value"
need="OPTIONAL" measurement_approach="value"
nominal="9.0">
</attribute>
• Tolerance
Each attribute has a set of specifications defined. Each specification is defined using a
tolerance element. For a detailed explanation, see the table of XML elements.
The tolerance element has spec_set_code as an attribute, indicating the name of the
specification set. The USL, LSL, and target are captured as child elements.
Example
<tolerance spec_set_code="ENGG">
<usl>1.2</usl>
<lsl>2.1</lsl>
<target>0</target>
</tolerance>
5. Repeat this process to add as many tolerances to the attribute, as many attributes to the feature,
and as many features to the routine as required.
Note
Although some of the values in the elements are optional (for example, i2, j2, k2), you
should keep the values in the .xml file. Leave them blank if you do not want to use them.
Note
• Enter only
alphanumeric
characters. Do
not use special
characters.
• The feature
name is used
for reporting.
Note
The alternate feature
label is used in the
Analysis window
in DPV Reporting
& Analysis and in
DPV ETL if a feature
cannot be identified
by the feature label.
• Hole
• Pin
• Slot
• Tab
Note
There is no limit to
the number of files to
be merged. Assign
each split a different
name. For example,
Left, Right, Top,
Bottom, Middle, and
so on.
• 1 – Significant
measurement_ Select how the coordinate
approach measuring machine (CMM)
probe measures a point for:
• Surface – Takes into
account the actual vector of
the measured geometry.
Note
Enter any string for
the specification.
Note that if you make
a typographical error,
it defines a new
specification code.
Note
There is only one dataset for a routine.
1. In the Manufacturing Process Planner, click the tab associated with the process structure.
2. Select the routine for which you want to create the dataset.
3. Choose File→New→Dataset.
4. From the Type list, select Dimensional Planning And Validation Excel.
6. Import a DPV Excel Engineering workbook containing feature data by doing the following:
c. Click OK.
Note
You must save the DPV Excel Engineering workbook as an .xslx file before you can
upload it.
1. In Manufacturing Process Planner, click the tab associated with the process structure.
3. In the Attachments view, right-click the existing data set associated with the routine, and choose
Named References.
5. Browse for the DPV Excel Engineering workbook and click Upload.
Note
Do not select the routine revision on the Attachments page.
Note
Click to browse for the file.
6. Click OK.
Tip
Use Excel functionality, such as sorting and filtering, to help you enter and manage the data.
In addition, set freeze pane to keep the headers visible when scrolling in the worksheet.
1. In Manufacturing Process Planner, click the tab associated with the process structure (bill of
process).
6. Choose File→Save.
A message appears asking you if you want to save the workbook as a macro-free workbook.
7. Click Yes.
• Parsing script
• Encoding
2. In the Select Measurement Data File box, enter the path to the data file from which the
Engineering Excel workbook will be created.
3. In the Select Parsing Script box, enter the path to the parsing script for the selected data file.
The parsing script is compiled internally and the data is parsed using the methods in this parsing
script.
4. (Optional) In the Select Common Script box, enter the path to the common code script for
the selected data file.
5. (Optional) In the Optional inputs section of the XML Generation Utility dialog box, enter the
following:
• Routine, Device, or Plant Configuration files
These are input script parameters for the parsing script.
These configurations files are extracted from Teamcenter and are in the folder on the ETL
server:
DPVRoutine/ DPVDevice folders in the %DPVETLENTAPP%/DPV folder.
• Encoding
This input is required only for data files of type PCDMIS 3.1. This file has special characters,
such as NOME DA PEÇA, SÉRIE, NÚMERO, and so on. To correctly read and parse this
file, encoding should be set to UTF7 either in the device configuration file or through this
input. If the encoding is not set, these special characters cannot be read and are interpreted
incorrectly.
• Feature
• Hole
• Pin
• Slot
• Tab
The following table explains the options you can set for need in the DPV feature data definition.
Often feature data for a routine is not collected in a single file but in several. You can merge the
files into one event that is stored in the Teamcenter measurement database. In the DPV Excel
Engineering workbook and the XML feature data, a loading split ID represents the events (loading
splits) that should be merged into one event as shown in the figure.
Data about the split event is not available in reports or DPV-SSAS until all the required split event
data is in the Teamcenter measurement database. You can, however, use DPV Reporting & Analysis
to query and view event data before it is all collected by setting the Event Type parameter to H
in the Query list.
Example
If the left side of a car is stored in one file and the right side in a separate file, enter the
following for Loading Split ID:
• LeftSide for all features that are part of the left side.
Because these are the only two groups of measurements to be merged, each feature
belongs to either LeftSide or RightSide (there should be no features without a loading
split ID).
When the extract, translate, and load (ETL) processing encounters a split event, it stores
the data for the side received first into the Teamcenter measurement database. When the
other side is measured, its data is merged into the data for the first side.
There is no limit to the number of files to be merged. Assign each split a different name. For example,
Left, Right, Top, Bottom, Middle, and so on.
Note
• There is no limit to the number of files to be merged. Assign each split a different
name. For example, Left, Right, Top, Bottom, Middle, and so on.
• The threshold set in the DPV Enterprise Configuration Explorer to define how extra
feature attributes are handled applies to split events. If a measurement data job
arrives with extra feature attributes, the number of feature attributes used to determine
the percentage of the threshold is based on the split in the DPV Engineering Excel
workbook. For example, if the job is a LH job, the number of feature attributes used to
determine the percentage calculation for the threshold is defined by the LH feature
attributes in the workbook.
Because it is a dataset, a datum transformation does not have its own revision control. A revision of
the cluster, however, results in the new revision having its own copy of the transformation definition.
This new copy can be modified independent of the definition on the previous cluster revision.
Example
Cluster 1/Revision A –> Transformation Definition 1
Transformation Definition 1 does not have any revision control with respect to Cluster
1/Revision A. If Cluster 1/Revision A is revised, Cluster 1/Revision B has a copy of
Transformation Definition 1. This can be modified without affecting the definition on the
earlier version of the transformation on the cluster’s revision A.
Cluster 1/Revision B –> Transformation Definition 1
This is a copy of Revision A’s definition. Modifications here do not affect the Cluster 1/
Revision A’s datum transformation definition.
</datumTransform>
</datumXForms>
Note
Although some of the values in the elements are optional, you should keep the values in
the .xml file. Leave them blank if you do not want to use them.
• NO
Note
Must be uppercase.
• Y
• Z
secondaryAxis Specify the secondary axis:
• X
• Y
• Z
tertiaryAxis Specify the tertiary axis:
• X
• Y
• Z
primaryFeatures Holder for the primary features
secondaryFeatures Holder for the secondary
features
tertiaryFeatures Holder for the tertiary features
Define triggers
Attach a trigger form to each routine that needs a graphical report created (called a triggered report)
whenever it is processed.
For more information, see Administering reports in the DPV help collection.
1. In Manufacturing Process Planner, click the tab associated with the process structure.
4. Check out and edit the form of the type Dimensional Planning And Validation Trigger
Configuration.
5. In trigger_reports enter the Boolean flag that specifies whether or not to trigger a report for this
routine when a measurement event is received.
6. Set the preference DPV_ccuaservice_url. The value is the URL at which the SSRS Custom
Cache Updating Application (CCUA) is hosted.
7. Click OK.
Teamcenter can store the mapping between features across measurement routines so you can
compare measurements from different inspection devices (referred to as device compare). The
mapping can then be retrieved when queried for in DPV Reporting & Analysis.
1. Review the Excel Engineering datasets belonging to the routines to determine the common
features to be mapped.
3. Add a new worksheet with the name FeatureMap and copy the Feature label column from the
FeatureInfo worksheet and paste it in the FeatureMap sheet.
Example
The following shows an example of adding the Feature Label column with three
features.
4. In the FeatureMap worksheet, enter the mapping for the different routines in the columns: one
column per routine with mapped features:
• Enter the routine ID and revision in the same row as the Feature Label heading.
• Enter the feature to which the initial feature is to be mapped in the same row as the initial
feature. Separate the routine ID and revision using a ~ character, as shown in the example.
Note
Only the feature names are used during the mapping. The attributes are not entered in
the mapping worksheet. It is assumed that all the attributes of the respective features
are mapped.
Example
In the following example of an Excel workbook with feature mapping defined, Column
A lists the features that belong to the routine associated with this Excel workbook
(ExampleRoutine). It has three features: ftr1, ftr2, and ftr3. The Columns B and C
list the IDs and revisions of the routines to which these features will be mapped.
In the example:
• ftr1 of ExampleRoutine is mapped to feature5 of the routine with the ID GMO003
and revision 1.
Note
To delete the feature mapping, delete the worksheet or the row of mapping.
2. (Optional) Add the new attribute to the DPV List of Values (LOV) through the Business Modeler
IDE (Integrated Development Environment), a tool for configuring and extending Teamcenter.
This is required only if you want the attribute code to be transformed to its abbreviation when a
user queries for it in DPV Reporting & Analysis.
3. (Optional) Define a rule to extract the feature attribute data from the measurement file.
If your custom attribute name is not explicitly specified in the raw data measurement file, you need
to create a rule in the attribute rules XML file to specify how to extract it. For example, if its name
is contained within the feature label, you need to define a rule that specifies how to extract it. You
can easily read and modify the attribute rules XML file using the Attribute Rules XML Editor.
4. (Optional) Place the updated attribute rules XML file on a server that can be accessed by various
DPV ETL servers in the deployment.
Note
The location of the attribute rules XML file was specified during the installation of DPV
ETL. You can change it using the DPV ETL Configuration Editor.
DPV Parser reads the raw measurement data file using the device-specific parsing script. This
data is then passed in a common XML format (DML) to DPV Validate for validation of data. The
correct data, including the new attribute, is inserted into the SQL database. From there, DPV
Reporting & Analysis and Teamcenter community collaboration access the data for viewing
and analysis.
See Flow of data from shop floor to DPV in the DPV online help.
Note
• You may need to modify the associated parsing script to correctly parse the new
attribute type.
• For filtering in the DPV-SQL Server Analysis Services (DPV-SSAS) and SQL
Server Reporting Services (SSRS), clusters must be created in DPV-SSAS and
SSRS.
As described in Adding features, add the new feature attribute to the definition of the routine in
Teamcenter. The process is the same as for adding a standard attribute code:
1. Open the Excel Engineering workbook associated with the routine, and add the custom feature
attribute definition to it as you would any standard attribute.
(Optional) Add the feature attributes to the list of values in Business Modeler IDE
If you want the attribute code to be transformed to its abbreviation in DPV Reporting & Analysis, add
the new feature attributes to the DPV list of values (LOV). If you do not require this transformation,
you do not need to add the attribute code to the LOV.
Example
To transform the attribute code X_DEV to its abbreviation X in DPV Reporting & Analysis,
create a value in the LOV made up of its code and abbreviation separated by a ~ character
(X_DEV~X).
When the data in the data file comes in as X_DEV, it is transformed to X when sent to DPV
Reporting & Analysis in a query.
Note
For more information about using the Business Modeler IDE, see the Configure your
business data model in BMIDE.
2. Choose File→New→Project.
3. In the New Project wizard, expand Business Modeler IDE and select New Business Modeler
IDE Template.
4. Click Next.
6. Click Next.
7. In the Prefix box, type a prefix to use for the project. This prefix is placed on every data model
item you create to identify it as belonging to this project.
8. Next to the Dependent templates directory box, click Browse and browse for the following
location containing the Dimensional Planning and Validation templates, where xxx is the version
of Teamcenter:
install_dir/Program Files/Siemens/Teamcenter/Tcxxx/bmide/templates
9. Click OK.
2. In the Extensions view, expand the project you just created until you see the LOV folders
displayed.
3. Double-click DPVFtrAttCode.
The LOV appears. All its values appear in the Details view.
5. In the Add LOV Value dialog box, in the Value box, type a value and its abbreviation separated
by a ~ character.
Example
To define New Width, with the value NWID and the abbreviation NW, enter NWID~NW.
6. Click Finish.
• Define a server connection profile, which specifies the Teamcenter servers to connect to:
a. Choose Window→Preferences.
c. Click Add.
The Teamcenter Repository Connection wizard runs.
3. Select the project in a view and on the main toolbar, click the Deploy Template button.
4. From the Server Connection Profiles box, choose the server to which to deploy the extensions
to.
5. Change any information and enter the password to access the server.
6. Click Finish.
The attribute rules XML file contains a list of rules that specify how to determine attribute codes if
they are not explicitly specified in the raw data measurement file. For example, if the measurement
file does not contain an entry for the feature attribute name (FeatureAttributeType) but instead
incorporates the name into its alternative feature label (AltFeatureLbl), you must create a rule that
specifies how to extract the name from the feature label.
Use the Attribute Rule XML Editor to define the rules for the attribute rules XML file. The default
attribute rules XML file is included with the Dimensional Planning and Validation installation.
Note
The sequence of the rules is important. They are in top to bottom priority, with the first rules
taking precedence. For example, if you have the following two rules in this order:
<Rule condition="Chars" Position="2" conditionKey="D" atribute_code="DIM" />
Then if a feature label contains a D in both its second and first positions, it will be
interpreted as having the attribute code DIM and not DOS. If you reversed the order, then
it would be interpreted as DOS.
2. Type the path and name of the attribute rules XML file, or click Browse to search for a file.
Tip
A scroll bar on the right lets you scroll through the file. The arrows on the right change
the sequence of the rules.
3. Set the values for the new rule using the Condition, Condition Key, and Attribute Code options.
4. Click Insert Above, Insert Below, or Insert Last to insert the rule into the attribute rules XML file.
Tip
To Do the following
Delete a rule Select the rule to be deleted and click
Delete Selected.
Change the sequence of rules Select the rule to be moved and click an
arrow on the right.
Modify existing rule Select the rule to be modified, change the
desired value, and click Modify Existing.
Note
You must restart DPV ETL because DPV Parser reads the XML in to memory only at
startup. Any changes made to the XML will be applied only after a restart.
The location of the attribute rules XML file was specified during the installation of DPV ETL. You can
change it using the DPV Enterprise Configuration Editor. DPV Parser accesses and reads the XML
from this path at startup. If the access to the XML fails, DPV Parser does not start and logs an error
message in its log file, located at DPVETLENTAPP\log\DPVParser.log, where DPVETLENTAPP
is the location of DPV ETL.
Tip
You can:
• Have a different set of rules for each server by placing a different attribute rules XML
file on each server where DPV ETL is deployed.
• Use the same set of rules across various DPV ETL servers by placing the attribute
rules XML file on a shared location accessible to all the servers. Have the system
administrator at the user site do this by creating mapped drives or network shared
paths to Windows or UNIX machines.
1. In the DPV Enterprise Configuration Explorer, in the tree structure on the left, under your server
branch, expand Dimensional Planning & Validation→Task Configuration.
3. In the Attribute Rules XML File Path box, type the path for the attribute rules XML.
Rule conditions
The rule conditions used in the attribute rules XML file are:
• EndsWith
Use the EndsWith condition to specify that if the ending (right-most portion) of the feature
name in the raw measurement data file matches the string specified in conditionKey, the
attribute_code specifies the attribute type for that feature label.
Example
<Rule condition="EndsWith" conditionKey="(F/A)" attribute_code="X_DEV" />
If the feature name ends in F/A, the feature attribute code is X_DEV.
• StartsWith
Use the StartsWith condition to specify that if the beginning (left-most portion) of the feature
name in the raw measurement data file matches the string specified in conditionKey, the
attribute_code specifies the attribute type for that feature label.
Example
<Rule condition="StartsWith" conditionKey="GAP " atribute_code="GAP" />
If the feature name starts with GAP , the feature attribute code is GAP.
• Contains
Use the Contains condition to specify that if the feature name in the raw measurement data file
matches the string specified in conditionKey, the attribute_code specifies the attribute type
for that feature label.
Example
<Rule condition="Contains" conditionKey="(I/O)" atribute_code="Y_DEV" />
If the feature name contains I/O, the feature attribute code is Y_DEV.
• Chars
Use the Chars condition to specify that if the feature name in the raw measurement data file
contains the characters specified in conditionKey in the positions specified in Position, the
attribute_code specifies the attribute type for that feature label.
Note
<Rule condition="Chars" Position="3-5" conditionKey="XXG" atribute_code="S2S"
/>
If the third through fifth characters in the feature name are XXG, then the feature attribute code
is s2s.
The contents of the attribute rules XML file must conform to the following. If they do not, when you
save the file, a warning message appears listing the errors and yellow highlighting appears on the
invalid rules in the Attribute Rule XML Editor. You cannot save the file until the errors are corrected.
During processing, DPV Parser writes an error message to its log file, located at
DPVETLENTAPP\log\DPVParser.log, where DPVETLENTAPP is the location of DPV ETL.
• If a rule condition of Chars is used, the rule must contain a Position tag.
You can create cluster groups to combine multiple clusters from different sources and routines. The
clusters you create are available to others when they load the data source in DPV Reporting &
Analysis. You can also view, compare, and copy cluster groups.
Note
• For information about creating clusters, see Working with clusters in the DPV Reporting
& Analysis online help.
• When you create a cluster in DPV Reporting & Analysis and save it to Teamcenter, it is
saved as an item of type Dimensional Planning And Validation Cluster, attached
to the inspection device.
For a routine revision, the default copy action for cluster revision attachments is Copy as
reference.
Learn more about revising routines.
• When creating a new revision of a cluster group, use the Relate to Latest option to relate each
cluster revision within that cluster group revision to the latest cluster revision or to keep at the
current revision level.
• Use the List Cluster Groups command to copy the clusters and cluster groups to a folder
for easy selection for revision and release.
The most common and recommended way to create a cluster group is to use DPV Reporting &
Analysis and save it to Teamcenter.
For information about creating clusters, see Working with clusters in the DPV Reporting & Analysis
online help.
1. In My Teamcenter, click Home or the folder where you want to create the cluster group.
2. Choose File→Item.
4. From Item Type, select Dimensional Planning And Validation Cluster Group.
5. Click OK.
Note
Use Paste... and the Dimensional Planning And Validation Cluster Group Content
relationship type.
You can view the cluster groups that a routine’s clusters belong to and every revision of those cluster
groups. You can also copy the cluster groups to the clipboard so you can place them in a folder where
you can release or revise them or add them to another routine.
1. In the Manufacturing Process Planner, click the tab associated with the process structure.
2. Right-click the routine for which you want to view cluster groups, and choose List Cluster
Groups→One Revision.
Note
The routine must be of the type MEVisInspection, MEHHInspection,
MECMMInspection, or MEInspection to use the List Cluster Group command.
A list of cluster groups associated with the routine appears, sorted by cluster group revision
name. You can view the cluster’s name, item and revision IDs, and the release status.
Tip
• To change how the list is sorted, click the header, such as Item ID.
3. (Optional) To copy the cluster group revisions to the clipboard, do one of the following:
• Click Copy All to copy all revisions to the clipboard.
• Hold down the Ctrl key (to select non-contiguous groups) or Shift key (to select contiguous
groups) and select the desired cluster group revisions in the dialog box and click Copy
Selected.
You can compare the cluster groups associated with two different revisions of a routine. You can also
copy the cluster groups to the clipboard so you can place them in a folder where you can release
or revise them or add them to another routine.
1. In the Manufacturing Process Planner, click the tab associated with the process structure.
2. Right-click the revision of a routine against which you want to compare another revision, and
choose List Cluster Groups→Two Revisions.
Note
The routine must be of the type MEVisInspection, MEHHInspection,
MECMMInspection, or MEInspection to use the List Cluster Group command.
A list of revisions of the routine appear. By default, the revision on which the initially selected
revision is based is selected and highlighted in italics bold.
Example
It you are comparing routine revision E against routine revision C, and revision E was
created based on revision C, the following list of revisions appear for you to select, with
routine revision C in italics bold.
3. Select the routine revision against which you want to compare the initially selected routine
revision, and click OK.
The Routine’s Cluster Group Revision Report dialog box appears.
• A blank row in one list indicates that the cluster group in the same row in the second list is
not present in that revision of the routine.
• Highlighting indicates that a cluster group revision contains cluster revisions that are newer
than those in the cluster group revision. For example, cluster group revision grp1 contains
cluster revision c2, revision A. However, there is a newer revision of c2 (revision B).
• An asterisk in the report indicates that the cluster group revisions do not match. The
E-Report Group revision differs.
Tip
• To change how the list is sorted, click the header, such as Item ID.
4. (Optional) To copy the cluster group revisions to the clipboard, do one of the following:
• Click Copy All to copy all revisions to the clipboard.
• Select a cluster group revision in the dialog box and click Copy Selected.
</datumXForms>
</datumXForms>
A datumTransform element has attributes that specify whether or not to use feature vectors
and the axes for the primary, secondary, and tertiary datums. For a detailed explanation, see
the table of XML elements.
Example
<datumTransform useFeatureVectors="YES" primaryAxis="X"
secondaryAxis="X" tertiaryAxis="X">
3. Within datumTransform, define the primary, secondary, and tertiary datums and their features.
<?xml version="1.0" encoding="UTF-8" ?>
</datumXForms>
The primary, secondary, and tertiary consists of the features. For a detailed explanation, see
the table of XML elements.
Example
<Primary Features>
<feature id="" x="" y="" z="" i="" j="" k="" i2=""
j2="" k2="" offset=""/>
For tips and cautions, see the procedure for creating datum transformations in DPV Reporting &
Analysis.
4. After creating the .xml file, click the cluster, and choose File→New Dataset.
6. From the Type list, select Dimensional Planning And Validation Datum Transform.
Teamcenter can store the mapping between features across measurement routines so you can
compare measurements from different inspection devices (referred to as device compare). The
mapping can then be retrieved when queried for in DPV Reporting & Analysis.
1. Review the Excel Engineering datasets belonging to the routines to determine the common
features to be mapped.
3. Add a new worksheet with the name FeatureMap and copy the Feature label column from the
FeatureInfo worksheet and paste it in the FeatureMap sheet.
Example
The following shows an example of adding the Feature Label column with three
features.
4. In the FeatureMap worksheet, enter the mapping for the different routines in the columns: one
column per routine with mapped features:
• Enter the routine ID and revision in the same row as the Feature Label heading.
• Enter the feature to which the initial feature is to be mapped in the same row as the initial
feature. Separate the routine ID and revision using a ~ character, as shown in the example.
Note
Only the feature names are used during the mapping. The attributes are not entered in
the mapping worksheet. It is assumed that all the attributes of the respective features
are mapped.
Example
In the following example of an Excel workbook with feature mapping defined, Column
A lists the features that belong to the routine associated with this Excel workbook
(ExampleRoutine). It has three features: ftr1, ftr2, and ftr3. The Columns B and C
list the IDs and revisions of the routines to which these features will be mapped.
In the example:
• ftr1 of ExampleRoutine is mapped to feature5 of the routine with the ID GMO003
and revision 1.
Note
To delete the feature mapping, delete the worksheet or the row of mapping.
When you are done editing a measurement routine revision, it is recommended that you release it
before using the routine in the inspection process. Releasing a routine and its clusters locks the
routine so no changes can be made. Perform the approval process using the Teamcenter workflow
engine. For information on how to model and apply a workflow that is suitable for your needs, see
the Workflow Designer Guide. Releasing a routine and all its attachments freezes them so no more
changes can be made to the features or forms.
Until a measurement routine revision is sent through a workflow toDPV ETL,DPV ETL continues to
use previously sent revision. When a measurement routine revision is sent to DPV ETL, Teamcenter
creates a .plmxml representation of it and manages that file in its vault. DPV ETL reads the data
and processes it.
Each measurement routine revision has a unique identifier based on standard Teamcenter
functionality. In Teamcenter, the routines themselves are revised, but the features and the features
attributes are not under revision control.
Note
DPV ETL may run on a different computer from Teamcenter. The Teamcenter .xml files for
released routines are stored in the Teamcenter vault. If there is a communication failure
between the DPV ETL computer and the Teamcenter computer, the updated .plmxml files
are not visible until communication is restored.
• For basic information about creating a revision of an item in Teamcenter, see the Teamcenter
Basics.
• You can choose to revise each cluster revision attached to the routine and relate it to the latest
item revision.
• It is recommended that you release and/or revise routines before releasing or revising cluster
groups and clusters.
1. In My Teamcenter, select the routine that you want to create a new revision of and choose
File→Revise.
The Revise dialog box appears.
2. (Optional) In the Define the basic information for the new item revision pane, type the name
of the new revision.
3. (Optional) Type a description of the revision and choose a unit of measure for the revision.
4. Click Next.
The Define additional item revision information pane appears.
6. Click Next.
The Define attached objects pane displays the clusters, cluster groups, forms, and Excel
Engineering datasets attached to the routine. Copy as Reference is the default (all changes to
the reference copy affect the original object).
Note
Clusters are listed under Manifestations.
7. Choose copy options for the objects related to the source revision by clicking the icon to the
right of the object in the tree.
8. Click Next.
The Select open option and alternate id display option pane appears.
9. (Optional) Set the open, display, or checkout option for the new revision.
Tip
Use the List Cluster Groups command to copy the clusters and cluster groups to a
folder for easy selection for revision and release.
3. Right-click the routine and choose Paste As, as shown in the figure.
Note
The commands available to you are determined by your administrator.
Example
Enter underbody222left if the
routine is known by that name
on the shop floor even if it is
UB_222LH in Teamcenter.
Note
The shop floor name must
match the name in the raw data
file when working with certain
data types.
5. In the New Process dialog box, from the Process Template list, select ExportRoutine_To_AI.
The file names automatically fill in.
6. Verify that the targets specified in the New Process dialog box are correct.
7. Click OK.
The Information dialog box appears.
8. Click OK.
Example
D:\ETLDPV\RawData\FFX_ASM\000057_Perceptron\000001_X0_Perceptron
3. From the main structure view, and not the Attachments view, select the device and its immediate
parent.
6. Verify that the targets specified in the New Process Dialog for Plant Name and Routine are
correct.
7. Click OK.
The device is automatically sent to DPV ETL for processing.
Example
If you change the shift timings in the DPVShiftStartTime form attached to the plant, you
can use this workflow to export the plant information to DPV ETL.
4. In the New Process dialog box, from the Process Template list, select ExportPlant_To_AI.
The file names automatically fill in.
5. Verify that the targets specified in the New Process dialog box are correct.
6. Click OK.
Note
If a plant name exceeds 30 characters, the application interface (AI) objects exported for
that plant will not be downloaded to DPV ETL.
Application Interface (AI) objects are created in a user’s Newstuff folder when inspection devices,
common scripts, or routines are exported to DPV ETL through a Teamcenter workflow. The AI object
contains a PLM XML file with the information you exported.
Tip
You can view the status of an AI object by expanding the object.
DPV ETL periodically scans Teamcenter for AI objects (or modified AI objects), identified as belonging
to the plants to be downloaded, and downloads the PLM XML into the DPVDevice and DPVRoutine
folders under the FLINK/xmlcfg folder in the DPV ETL configuration:
It translates the PLM XML into a common XML format for uploading. PLM XML files that fail to
translate are placed into DevicePLMXMLFailed or RoutinePLMXMLFailed folders.
Tip
You can monitor this process using the using the DPV Error Viewer. For more information,
see Viewing DPV ETL status in the DPV help collection.
When the DPV ETL consumes the contents of an AI object, it sends a message back to Teamcenter
confirming it. On a daily basis, it removes any consumed AI objects that are more than 24 hours
old. It removes them at a hard-coded time of 0:00:00 (the time is the local time on the DPV ETL
installation) or when the DPV ETL is restarted.
The DPV ETL user account must have been set up with access to remove AI objects.
Note
• The DPV ETL does not delete the AI objects. It just removes them from the Newstuff
folders. The AI objects are still in the Teamcenter database.
• Only automatically created DPV AI objects are removed from Newstuff folders.
• If an AI object appears in more than one user’s Newstuff folder, the AI object is
removed from all users’ Newstuff folders.
To provide the DPV ETL account with access rights to remove Application Interface (AI) objects from
Newstuff folders, add the following ACL to the Teamcenter installation:
Has Type (Newstuff Folder)
It sets the rules that grant AI object removal privileges. Add the ACL to your Teamcenter installation
using the CreateAIRuleInACL executable. If the Teamcenter installation’s rule tree is different than
the default rule tree or it has write restrictions, you need to set up the rule manually.
For information about adding the rule, see Creating the application interface (AI) rule in the access
control list (ACL) in the Installing the Dimensional Planning and Validation Solution guide in the
DPV help.
For information about setting up rule trees manually, see the Teamcenter Upgrade.
The first time you start DPV ETL, it downloads all pending exported objects: measurement
routines, inspection devices, and plants. The exported objects are application interface (AI)
objects and were created using the export to AI workflows. The objects are downloaded and
translated as routine/device configuration files in the %DPVETLENTAPP%\DPVRoutine and
%DPVETLENTAPP%\DPVDevice folders.
After exporting any pending objects, DPV ETL sets a date-time filter of either:
It applies the date filter to all queries so it only downloads objects exported after the last successfully
downloaded object.
(Optional) To have DPV ETL check for all objects and ignore the date-time filter, do the following to
remove the CreatedAfterFilter from the registry key. The CreatedAfterFilter value only needs to be
deleted if you have AI objects pending to be downloaded prior to the last successfully downloaded
AI object.
2. Using the registry editor (regedit), delete the CreatedAfterFilter value from the registry key. :
The registry key is located here:
HKLM\Software\Siemens\DPVETLENT
• dpv_restore
Loads deleted data back into the database using the data file that dpv_archive created.
• dpv_purge
Deletes records permanently based on the set of selection criteria. It does not create a data
file for restoring the data.
The selection criteria are stored in the database and read whenever the utilities are run. You use
Teamcenter to enter the criteria and the Teamcenter command window to run the utilities.
Note
• You should also perform all the basic administrator tasks for the database you are
using for dimensional planning and validation as you do for any database, such as
adding users and backing up the data.
2. Click the Advanced tab, and select Dimensional Planning and Validation Archive Criteria.
3. Select the selection criteria by which to automatically archive or purge the database. You can
specify one set of criteria per plant and inspection device type.
4. Click OK.
5. Click Close.
Note
• If you use the same plant ID and inspection device type combination in a second set of
selection criteria, it overwrites the earlier criteria (that is, the number of months/days
and minimum number of records).
• You can add any number of plant and inspection device pairs to the criteria list, each
with its own time and records criteria. All pairs are archived or purged. The number
of records criterion, described next, is evaluated, and the decision whether or not to
archive or purge is performed independently for each plant and inspection device pair.
All data archived from running dpv_archive is written to a single output file.
• Time and minimum number of records work together to specify the criteria for
archiving or purging, so you need to specify both time and number of records. When
dpv_archive or dpv_purge is run, the program first determines if the number of
records criterion is satisfied.
Example
In this example, if in a six-day period only 50 records were created, the records would not
be archived because the archiving would result in fewer records remaining in the database
than was specified for the given plant ID and inspection device type pair.
No of Records 100
In this example, when either dpv_archive or dpv_purge is run, the program first
determines if the number of records criterion is satisfied. If it is, it deletes all the records in
the database belonging to the Taipei plant that are from any CMM device and are greater
than six months old. If dpv_archive had been run, all records would be written to a data
file from which they could later be restored. For the number of records criterion to be met
in this scenario, there must be 101 or more records for the Taipei and CMM combination
that are six months or younger.
Tip
• On a Windows system, click the Start button and choose
Programs→Teamcenter→Command Prompt.
2. At the Teamcenter command prompt, run dpv_archive <filename>, where filename is the name
of the file to contain the archived data. The file must include an extension, such as .dat.
Example
dpv_archive measdata_Jan-15–2012.dat
Note
If you want a regular process, you can use cron or other system tools to set up a regular
running program.
Tip
• On a Windows system, click the Start button and choose
Programs→Teamcenter→Command Prompt.
Restore data
To restore archived data, run the restore utility with the file name containing the archived data.
1. Access a Teamcenter command window.
Tip
• On a Windows system, click the Start button and choose
Programs→Teamcenter→Command Prompt.
2. At the Teamcenter command prompt, run dpv_restore <filename>, where filename is the
archive file to be restored.
Example
dpv_restore measdata_Jan-15–2012.dat
Getting started
Note
To view the time and date of measurement events in DPV
Measurements, after updating Dimensional Planning and
Validation (DPV) and Teamcenter to 10.1, you must update each
of your measurement databases.
See the Teamcenter Upgrade.
Start DPV
In the navigation pane, click DPV Measurements .
Measurements
Note
To view the time and date of measurement events in DPV Measurements, after updating
Dimensional Planning and Validation (DPV) and Teamcenter to 10.1, you must update
each of your measurement databases.
See the Teamcenter Upgrade.
1. In the Teamcenter rich client, click DPV Measurements in the navigation pane.
Note
If DPV Measurements does not appear in the navigation pane:
a. Beneath the navigation pane, select Configure Applications (>>) and choose
Navigation Pane Options.
b. From the list of available applications, select DPV Measurements and use the +
to place it in your list of primary or secondary applications.
c. Click OK.
3. From the list of routines IDs that appears, select the routine whose data you want to display.
• Use JSN and enter the JSN (build label) of the data.
Note
The exact JSN is required. Wildcards are not supported.
5. Select one of the following to choose to display features along with the events:
• Display events and their features to display features with the events.
• 1 – Active
• 0 – Inactive
Note
In the event_type column, normal jobs are listed as N and duplicate jobs as D.
7. If you choose to view features, use the scroll bar to scroll to the right to view the features
in the last columns.
Note
The feature column headers consist of the feature name and feature attribute code.
Note
• Sort the data on any column by clicking the column header.
Note
By default, all users can change the activation state of events. To protect your data, define
the preference DPVAdmin to hold the names of groups of users who can change the
activation state. Groups not in DPVAdmin can read the events but they cannot change
the activation state. If no preference is defined, all users will have the privilege to change
the activation state.
2. Highlight the data you want to activate or deactivate. You can make multiple selections.
3. Click either:
• Activate
• Deactivate
Note
These options activate or deactivate all the selections even if some of the selections
are already activated or deactivated.
DPVAdmin
DESCRIPTION
By default, in DPV Measurements, all users can change the activation state of
measurement data events (deactivate or activate them). To protect your data, define
DPVAdmin to hold the names of the groups of users who can change the activation
state. Groups not in DPVAdmin can read the events but they cannot their activation
state. If no preference is defined, all users have the privilege to change the activation
state.
Note
This preference is not included in your Teamcenter installation. You must
add it to the database.
VALID
VALUES
String. Group or groups who can deactivate/activate data. Separate
each group with a comma.
DEFAULT
PROTECTION
SCOPE
Site preference.
DPVClusterGroup Revision_DefaultChildProperties
DESCRIPTION
Specifies whether a specific relationship between two item revisions is listed
when you select the Paste Special command. For DPV, the relationship
DPVCLUSTERGROUPCONTENT is defined between clusters and cluster groups.
Therefore, select this value to have this relationship appear in the Paste Special
command in Teamcenter.
VALID
VALUES
One of the following relationships. To show the DPV cluster/cluster group relationship,
select DPVClusterGroupContent.
IMAN_master_form_rev
TC_Generic_Architecture
structure_revisions
IMAN_specification
IMAN_requirement
IMAN_manifestation
IMAN_reference
IMAN_UG_udf
IMAN_UG_altrep
IMAN_UG_scenario
IMAN_Simulation
IMAN_Rendering
IMAN_Motion
IMAN_3D_snap_shot
view
release_status_list
IMAN_external_object_link
TC_WorkContext_Relation
representation_for
IMAN_MEWorkInstruction
TC_ProductManua
BOM_Rollup
TC_Is_Represented_By
TC_Attaches
TCEng_rdv_plmxml_configured
TCEng_rdv_plmxml_unconfigured
TC_sst_record
ProcessSimulate_Details
KinematicsRelation
DPVClusterGroupContent
DEFAULT
VALUES
The values listed under Valid Values.
DEFAULT
PROTECTION
SCOPE
Site preference.
DPVClusterGroup Revision_shown_relations
DESCRIPTION
Specifies whether a specific relationship between two item revisions is listed
when you select the Paste Special command. For DPV, the relationship
DPVCLUSTERGROUPCONTENT is defined between clusters and cluster groups.
Therefore, select this value to have this relationship appear in the Paste Special
command in Teamcenter.
VALID
VALUES
One of the following relationships. To show the DPV cluster/cluster group relationship,
select DPVClusterGroupContent.
PSBOMViewRevision
IMAN_specification
IMAN_requirement
IMAN_manifestation
IMAN_reference
IMAN_UG_udf
IMAN_UG_altrep
IMAN_UG_scenario
IMAN_Simulation
IMAN_Rendering
IMAN_Motion
IMAN_MEMfgModel
IMAN_snapshot
IMAN_3D_snap_shot
IMAN_external_object_link
IMAN_MEWorkInstruction
TC_ProductManual
BOM_Rollup
TC_Attaches
TCEng_rdv_plmxml_configured
TC_Is_Represented_By
TCEng_rdv_plmxml_unconfigured
ProcessSimulate_Details
IMAN_MEFeature
Site Specific
Corporate Specific
DPVClusterGroupContent
DEFAULT
VALUES
The values listed under Valid Values.
DEFAULT
PROTECTION
SCOPE
Site preference.
DPVClusterGroupContent_relation_primary
DESCRIPTION
Specifies whether a specific relationship between two item revisions is listed
when you select the Paste Special command. For DPV, the relationship
DPVCLUSTERGROUPCONTENT is defined between clusters and cluster groups.
Therefore, select this value to have this relationship appear in the Paste Special
command in Teamcenter.
Note
All <relation_business_object>_relation_primary preferences are obsolete
and are replaced by relation properties. Use the Business Modeler IDE to
create and manage relation properties.
For more information about relation properties, see Configure your business
data model in BMIDE.
VALID
VALUES
DPVClusterGroup
DPVClusterGroup Revision
DEFAULT
VALUES
DPVClusterGroup
DPVClusterGroup Revision
DEFAULT
PROTECTION
SCOPE
Site preference.
DPV_ccuaservice_url
DESCRIPTION
Specifies the URL for the Custom Cache Updating Application (CCUA) Service used in
creating triggered reports.
For more information, see Working with triggered reports in the DPV online help.
VALID
VALUES
Set the URL, such as http://pni6w032/CCUATrigger/CCUA.asmx.
DEFAULT
VALUES
None.
DEFAULT
PROTECTION
SCOPE
Site preference.
DPV_logdatapurge_days
DESCRIPTION
Sets the number of days to retain log data.
For more information, see Modify Teamcenter Preferences in the Installing Dimensional
Planning and Validation Solution guide in the DPV help collection.
INTEGER
Specify the number of days to retain the log data. If it is set to x, log data that is more
than x days old is deleted automatically (no other user action is required).
DEFAULT
VALUES
None.
DEFAULT
PROTECTION
SCOPE
Site preference.
DPV_rawdata_location
DESCRIPTION
Specifies where the measurement data is stored, either in Teamcenter or an external
measurement database.
For more information, see Defining measurement databases in the Installing
Dimensional Planning and Validation Solution guide in the DPV help collection.
VALID
VALUES
0 The measurement data is stored within Teamcenter.
1 The measurement data is stored in an external measurement
database.
DEFAULT
PROTECTION
SCOPE
Site preference.
bill of process
Positions measurement routines within the structure of the overall manufacturing process and acts
as a mechanism for relating the product data to the measurement routines. The measurement
routines are operations within the plant.
bill of resource
Defines the items on the plant floor used to measure a routine, including stations, inspection devices,
remote transfer agents, and scripts. The top level is a plant of the type of MEPrPlant.
cluster
A logical subset of feature attributes that organize result set data related to a specific task, report, or
analysis. Clusters and cluster groups are used to filter data, compare correlation coefficients, perform
Principal Component Analysis (PCA), and run profile and summary reports.
correlation coefficient
A number between -1 and 1 that measures the linear relationship between two feature attributes.
A correlation coefficient of 1 indicates a perfect linear relationship; -1, a perfect linear relationship
with negative slope between the two; and 0, no linear relationship.
covariance
A measure of how great the correlation is between two or more sets of random features. In
3-dimensional terms, covariance measures the distance between feature attributes to determine how
X, Y, and Z dimensions vary from the mean with respect to each other.
Cp
A short-term indicator of process capability, Cp = (USL - LSL) / 6 * Standard Deviation. Cp indicates
how cohesive a group of values is without referencing the variability of the process.
Cpk
An adjustment of Cp for the impact of non-centered distribution, Cpk measures how close a process
is to its specification limits, relative to the variability of the process. Although data can exist outside
the specification and can still have a positive Cpk value, in general the larger the index, the less
likely that any item will be outside specifications.
dataset
Datasets manage data files created in other software applications. When you double-click a dataset
to open it, Teamcenter launches the software application associated with the dataset.
datum transformation
A subset of features you transform into a new datum scheme. In addition to providing more exact
measurement data, datum transformations allow more data to be collected from fewer measurement
device setups.
derived feature
A feature that is not measured and therefore does not actually exist in a data source, but instead
derives its value from the mathematical calculation of two or more existing, measured feature
attributes. For example, a derived feature midpoint can be calculated from the variation of two
feature attributes. The classification accuracy of tolerances based on derived features is typically
higher than that of the original features.
DPV Parser
DPV ETL task that reads the raw data in a measurement data file using a device-specific parsing
script. This data is then passed in a common XML format (DML) to DPV Validate.
DPV Validate
DPV ETL task that validates the measurement data it receives from DPV Parser. The correct
data is inserted into the SQL database for DPV Reporting & Analysis and Teamcenter community
collaboration to access for viewing and analysis.
engineering data
Defines what products are to be measured and what should be measured on them. You define the
engineering data using the Manufacturing Process Planner.
feature
A group of feature attributes that together define the geometric location, vector direction, and other
measurement characteristics of a point on the 3D model. Features can define different types of
geometry, including holes, tabs, or slots.
feature attribute
Feature attributes define a feature's specific measurement characteristics, based on such criteria
as x, y, and z location, anchor and vector coordinates, and specification limits. You can define
your own feature attributes.
hierarchical navigation
Method of locating measurement routine data on the Web Part, by navigating down to the item you
want to view, one level at a time, from a broad level down to a specific routine.
measurement data
Data obtained from inspection devices as a part is being measured and is processed and analyzed
to create Statistical Process Control (SPC) information. It includes the value of a feature or the
date at which the measurement was performed.
non-hierarchical navigation
Method of locating measurement routine data on the Web Part, by selecting a free-form navigational
structure with access to multiple items at once.
outlier
Any feature attribute value located outside the distribution range specified by a given mean and
standard deviation (in other words, any value that is markedly smaller or larger than other values).
parsing script
Translates the raw measurement data from inspection devices to the standard loading format
(Document Markup Language) so the data can be stored in Teamcenter for analysis and backup.
DPV provides standard scripts for translating data from the most common inspection devices. DPV
administrators can also create custom parsing scripts.
Pp
A long-term indicator of process performance as it applies to specific samples of feature attributes.
Ppk
A process performance index usually used for long-term analysis to indicate how your process has
performed in the past rather than how it will perform in the future. Ppk basically tries to verify that
samples generated from the process are capable of meeting customer requirements.
routine
Method or procedure devised to collect measurement data from a specific program and part using
a specific type of measurement device, such as a vision, Coordinate Measuring Machine (CMM),
or handheld measurement system.
rules
Conditions that specify how to determine the name of the feature attribute code if it is not explicitly
specified in the raw data measurement file. Rules are stored in the attributes rules XML file.
You can add rules to match your company's measurement data or modify existing ones. You edit
them in the Attribute Rules XML Editor.
saved location
On the Navigation page of the Web Part, a saved path to a frequently-used folder or routine in the
navigation structure. This is used for quick access without using a hierarchical or non-hierarchical
navigation.
Six Sigma
A disciplined, data-driven approach to eliminate defects, driving towards six standard deviations
between the mean and the nearest specification limit in any process. This measure of quality offers
a simple and straightforward indicator of process performance as it applies to specific samples
of feature attributes.
standard deviation
Expressed by the Greek letter sigma σ, this value is obtained by mathematically adjusting the data.
It is the square root of the mean average of the squares of the deviations of all of the individual
measurements from the mean average value X.
summary calculation
Calculations performed on measurement data to determine such statistics as the percentage that
is out of tolerance and Six Sigma. You view the calculations when you navigate to a measurement
routine in the DPV Viewer Web Part. See also Six Sigma.
variance
A measure of the spread of data in a data source closely related to standard deviation (the average
squared deviation of a value from its mean).
VisAutomationApp
Configuration of Teamcenter lifecycle visualization, similar to Teamcenter lifecycle visualization
mockup, but has no menus or toolbars. It processes graphical reports created in Visualization
Illustration.
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