|
 Printer Friendly |
Due diligence in modeling, checking for missing yields
Applies to: Spatial Woodstock 2006.8
How do you verify that all development types are assigned proper yield data? There are two potential yield errors in models, yield data is missing for a development type, or the incorrect yield data is assigned to a development type. You can easily check for the former error, and not so easily for the latter, using the reporting functionality in Spatial Woodstock.
The purpose of this tech tip is to describe a reporting method for identifying development types that lack yield data in models. Preliminary results from our 2007 customer survey suggest that over 75% of respondents were not aware of this functionality.
You can create summary reports of yield data in the Reports section as follows:
*TARGET MyReportName.dbf
YieldTableName
This tabular report includes a column for each theme in your model (which collectively define the development type), a column for the internally-assigned yield number, a column for the yield table name and a column each for the minimum and maximum yield value found. If you wish to also include yield data points, simply place a number after the yield table name in the report declaration above.
You can identify missing yields in this report by searching for development types (records) that lack a yield number (a blank cell). This means that when Spatial Woodstock scanned the Yields section, it did not make a match between that development type and that yield table. These records will also lack a minimum and maximum volume. The DBF format allows for easy sorting and filtering (Spatial Woodstock includes such tools).
Reporting yields offers a direct, quick and easy method for checking for missing yields in models. For a complete description of this functionality, see Chapter 12, Reports Section, page 129 of the Woodstock User Guide (v 2006.8), or the Woodstock online help (Reports section > Reporting Yields).
|
|
Stora Enso Predicts a 2.5% Savings
“We asked, ‘If we had made the decision and optimized the problems, how much money would we have saved?’” The answer was approximately 2.5 percent.”
- Continue reading...
- View all case studies...
|
 |
|
|
|
