Prediction Correlation Library File Overview
A
Prediction Correlation Library file stores the in-house part numbers that have been mapped to part numbers in
Windchill Risk and Reliability libraries and user libraries, which are enabled
Prediction Parts Library files. For more information, see
Prediction Parts Library Files.
Multiple occurrences of this file type can exist in a Project. You can also place them in the Common Library. For more information, see
Common Library.
All enabled
Prediction Correlation Library files are searched for part number matches in the order specified in the Project properties. For more information, see
Setting the Search Order for System and Library Files.
During a part number search, enabled Prediction Correlation Library files are searched first. If a match is found in one of these files, the part number to which the in-house part number has been mapped is used to search the Windchill Risk and Reliability libraries and user libraries for the mapped part number. The data for the mapped part is then copied from the library file to the part-related panes in the System file.
The table in this library file supports the filter bar in the same manner as tables in the
System file. Descriptions of table options appear in
Prediction Correlation Library File Options. Clicking
< Click here to insert a new record > in the last table row inserts a record. For more information, see
Entering and Mapping In-House Part Numbers.
You can delete records as described in
Deleting a Table Row. You can also import records into a
Prediction Correlation file. Under
Parts Library Search in the
Options window,
Correlated part number field determines whether in-house part numbers are saved to a text field in the
System file. For more information, see
Parts Library Search User Options.
For predictions, you can choose to save in-house part numbers to any one of the following fields for use in building and updating Parts Library files: Alternate Part Number (default), CAGE Code, Logistics Control Number (LCN), or User-Defined Text.