Hello uniquename,
Firstly of all thank you for your reply and secondly I would like to apologize for the late reply.
I am afraid I did not make myself clear in my first post, so I will try to illustrate the problem I am facing with another example.
I want to model a linear production chain which comprises many independent processes/steps.
These processes however, utilize many common materials and resources. In my first post I used the example of electricity and compressed air.
What troubles me is the modelling approach of such processes (be it materials or energy). For better visualization purposes, I would prefer to have a main plan, where I could put all the necessary flows for my production chain and associate them with the individual production steps.
This approach is working fine with the Sankey diagrams by switching between the various impact categories and having the visualization of the flows. The "problem" occurs in the raw data analysis and the contribution analysis of each process, since the impact of each process appears seperately without being allocated to the production steps.
The only way I have found so far to cluster the production steps/processes and their comprising sub-processes and flows is to create subnets. However, with this approach I have to put all the necessary processes in the subnet, thus losing in visualization from the main plan. Another drawback of this approach is that, whereas in the first modelling approach I could simply use one process (e.g. electricity) and connect it with all the required production steps, with the subnet modelling approach I have to separately create them.
This is quite cumbersome, especially for example if I want to use a different dataset for electricity and run sensitivity scenarios. Instead of replacing a "main" electricity process, I have to edit each production step and replace the electricity datasets separately.
The previous LCA software I had been using allowed the user to manually assign a group name to all the processes and sub-processes (either custom made or proprietary) used in the model. In this way, in the impact assessment phase, the results could be clustered and sorted accordingly, providing this way a great flexibility for contribution analysis in form of charts and tables.
To conclude, my question would be whether there is a similar function in Umberto or if somebody could suggest a workaround for my problem.
Kind regards,
Chris
