Sweco Case Study

Improving efficiency and accuracy in hydroelectric redevelopment projects

Gustav Skans is a civil engineer with more than 30 years of experience within hydropower development and structural engineering, who is currently employed by Sweco. Sweco is Europe’s leading engineering and architecture consultancy, with yearly net sales of approximately 2 billion EUR.


“It doesn’t cost much to do laser scanning, and you will get much better quality. It is advisable to try and avoid using surveyors only to measure terrain and existing structures with the use of a total station. It is instead preferable to prepare 3D scan data as this enables one to collect and process all the information that is needed for an existing building, or terrain for a green field project, and it can often be delivered within the same day or two. Scanning will provide data on basically everything that is visible, and you can later filter out what you don’t need in your design” – Gustav Skans, Civil Engineer at Sweco.


The Need


Exterior of the hydroelectric powerplant in Sweden, in use since 1918

Sweco have been using 3D scanners for a long time, including the use of airborne lidar. For Gustav Skans, who often works on redevelopment projects for existing hydroelectric power plants, 3D measurement data often proves to be extremely convenient.

This is because many of the existing hydropower plants and dams he works on are nearing the end of their expected lifespan, and sufficient as-built documentation is often lacking. This is the case with one of his current projects in a hydroelectric powerplant in Sweden that is more than 100 years old and is in need of some renewal measures. The entire machine hall and most of the waterways needed to be scanned in order for the redesign and upgrading of the power station to take place.

Before using Undet for SketchUp, although he was able to request point cloud data to be collected, he did not have a way to turn this into initial design plans in SketchUp. With no solution in place, it meant that processing data was extremely time-consuming. The effect of this being that answering client queries could take a week or more, and projects progressed slowly. Therefore, he was looking for a solution to use point clouds in SketchUp that would speed up his work and provide more accurate results to clients.

Undet for SketchUp is a plugin that enables users of SketchUp to create 3D models based on point cloud data. That includes features such as ground meshing tools to extract ground surface levels from point cloud data, an auto extraction feature to maximise accuracy when extracting/extruding/fitting the SketchUp plane to point cloud points and a point cloud clipping box to control the information available in the model view. Undet for Sketchup is also 2-3x faster than its rivals at processing point cloud data.


Point cloud showing machine hall and one of the generators and some walls, while being drafted in SketchUp using Undet. Scanners visible on the machine hall floor.

Point cloud from interior of the machine hall first commissioned in 1918. Skylift model placed inside the Undet point cloud to plan space requirements. One scanner visible behind the skylift.

The Solution – Undet for Sketchup


“I like how nicely done and clever the program is, and how easy it is to learn to use. I found Undet´s YouTube videos very helpful in providing ideas on how the program can be used” – Gustav Skans, civil engineer at Sweco.

With Undet for SketchUp’s terrain modelling tool excavation, concrete and steel quantities can now be efficiently summarised.  With a full data set, mistakes are also less likely to occur because the risk of using poor or outdated as-built information is eliminated.

Being able to process data more quickly means that most client inquiries and questions can now be responded to within one to two days and with better accuracy. Providing not just a faster service to clients, but leading to the following key results:

  • Speed – Quick establishment of as-built conditions and digital terrain models. Approximately reducing time expenditure by 5 to 10 times.
  • Increased Accuracy – With a full data set, mistakes are less likely to occur because the risk of using poor or outdated as-built information is eliminated.
  • Communications – Can process information and provide ideas and solutions very quickly to clients, normally within 1-2 days.
  • Staffing – Easier to convey solutions and viable options at an early stage within the design team.



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