Machine Learning: Report A

MACHINE LEARNING REPORT A OLIVER BALDOCK. DECEMBER 2018. ARCH7043.

The aim of this report is to begin to investigate and understand the workflow processes of the Feilden Clegg Bradley Studios. As an architecture practice with over two hundred employees in four offices, the firm has worked in most, if not all, sectors of construction since its formation in 1978.

The firm and its staff are split into ten groups spread across the four offices. Each group tends to loosely focus on a certain sector so that staff with more specialised knowledge can be placed on to more relevant projects.

Excluding a few anomalies, the majority of work is completed in either Microstation or Revit with the tendency, especially following recently more regular in-house training, to move towards the latter as projects progress. According to Figure 1, which looks at the status of projects across the entire office since January 2018, on average 20% of projects are in Revit, 60% in Microstation, and 20% are classified as Other, which includes bid work projects, CDA and guardianship roles. Of course, once a project is in Microstation, for example, it does not limit it from being translated into Revit. This often happens in later stages, although the reverse is less likely.

The choice of whether to use Microstation or Revit to start a project is usually decided by the resources available and the team’s experience in Revit, rather than being a client driven decision.

Having said that, this choice is also highly dependent on the project sector. Figure 2 shows the difference between FCB’s housing sector, which accounts for a large proportion of our work, and the education, culture and mixed use sectors. The data available for our health and commercial work was too sporadic for easy comparison.

Within housing, 21% of FCB’s projects are in Revit. This value rises to 30% for mixed use scheme, typically master-planning work, and 34% for education.Within our cultural sector, this drops to 8%. The reasons for the peak in Education and trough in the Cultural sector will be explored later.

As mentioned previously, it is often the case that a project will start and remain in Microstation from Stages 0 - 3 before being translated into Revit for Stage 4 - 6 post-planning. Figure 3 shows that the use, on average, of Revit within the office peaks at 45% at Stage 4 before dropping, as, especially in housing, FCB find themselves as design guardians rather than being novated, which is classified as ‘Other’.

Figure 4 examines more closely the workflow of a particular housing project, which I have worked on since 2017, from Feasibility to Stage 5. The major points of discussion that arose from this workflow analysis, noted in red in Fig.4, were the following: When the project started in Microstation, we used Sketchup to facilitate the need

for a 3D model. The coordination between Microstation and Sketchup was both an inaccurate and lengthy process, especially when a variety of options were being explored quickly.

The coordination of elevations and sections for planning within Microstation, whilst the design was still in flux, created many inaccuracies that were not fully resolved until we moved into Revit at Stage 5. It was also another lengthy process.

Coordination with other consultants was often a lengthy process that allowed for further inaccuracies.

The continuous need for 3D awareness required the constant rebuilding of a Sketchup model to ensure the accuracy of views.

One solution to these issues is found in the fact that this housing project is London based, which meant that factors such as minimum unit, room and core sizes had already been predefined by the London Housing Design Guide. The ideal tenure mix, number of units and net saleable area were also pre-defined by the client. Constraints set by the site and context defined the maximum height of building. Using Rhino, Grasshopper, Honeybee, an environmental plugin, and Galapagos, an evolutionary solver, a series of massings and forms could be produced giving the chance, at the very early stages of feasibility to explore a vast range of plausible options quickly.

These tools can also produce more objective data, such as current NSA, overshadowing values and wall to floor ratios for costing far quicker than if done by hand. These values are also a useful double check to ensure accurate coordination between 3D models and Microstation drawings.

A further coordination issue with Microstation lies in the production of schedules.

We needed to know the NSA, GIA, GEA, room areas, tenure type and unit orientation for every option we produced. With the number of units almost exceeding 200, the creation and triple checking of these schedules in Excel took up to a day, especially when discrepancies were found.The simple answer to this question is Revit. All these issues, including coordination with consultants, production of options and 3D views, can be done in either Revit itself, Dynamo or Enscape.

So why not just use Revit?

The reason here was training and a short project timespan. The time required to train the team and build the BIM model outweighed Microstations co-ordination inefficiencies at Stage 4, thus the move was put off until Stage 5, when a delay in tender submission allowed the necessary time.

Other housing projects, and most education projects, have been in Revit since Stage 1. In particular, for the school I worked on briefly, Revit was the better program choice. From Stage 0 a set of required room areas, relationships and a predefined massing were set out within a clear strategy that placed us as a coordinator between client and consultant. However, whilst Revit helped solve these coordination issues, Sketchup was still used as the preferred program for quick design discussions.

Thankfully, the Revit to Sketchup workflow was a simple one, producing a clean, working model, which could be edited and adjusted easily.

In contrast, almost all of FCB’s current culture projects undertake some sort of restoration work.

The creation of an accurate BIM model for existing buildings is an even more arduous task, and often working more closely with on site contractors using simpler CAD drawings can be easier. However, given the rising prevalence of 3D scanning, we may see a shift in this sector. FCB’s recent restoration of the Southbank Centre saw the creation of a detailed BIM model consisting of 50+ distinct floor levels, allowing a far greater understanding of the constraints and possibilities of design.

Ultimately, the design process will continue to contain a mixture of processes.

Machine learning can help both within those processes and in moving between them, but at this point, it can not, and should not replace the designers.

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APPENDIX

FIG 4: HOUSING PROJECT WORKFLOW