An important part of our BIM strategy is the validation and auditing of our BIM Geometry models. This has traditionally been a very analogue process of running through company standard compliance checklists and checking the model error logs for duplicate elements, view naming compliance, view template usage, imported linestyles..... yawn..... duplicate elements and so on. This process can easily take half a day and is therefore normally done at key model sharing stages. I wanted to resolve this, I believe every shared model should be audited for quality in order to minimise errors and part of our BIM delivery QA - enter Dynamo.
Using the existing paper based checklists as guidance along with a wishlist of extra checks i'd like to conduct i set about creating the equivalent checks but all beautifully automated with Dynamo. This proved far easier and more intuitive than i thought, nodes already existed for many of the checks i wanted to do... "get the views... get the names... filter ones which don't have... etc. etc".
Once i had the data and results i needed an interface with which to display the results, for this i used Excel, i love excel, once the data is in excel, a few If () statements are easier to write and you can quantify results easily.
The interface sits as a shared spreadsheet on the server with some simple scripts which clear the data when it's closed. Anyone in our organisation can then run the audit with no user input required simultaneously from Dynamo and print the results when a model is issued.
The hope is that as Dynamo evolves we can automate more and more checks on our models before they are Shared on the CDE.
The audit is complete within a minute, a time saving of easily a couple of hours from the traditional process, this means every model that leaves our office has been audited and is required to pass a certain base level of quality control before Document Control will issue models externally.
Future development is already in place to export this data as the audits are run and store this valuable data in a SQL database. This data will then be used for useful analytics and to give an overview of model health throughout the organisation.