Trimble’s Laser Scanning and 3D Modelling Helps EC Electric Save 90% in Labor Costs

EC Electric, a northwest-based electrical contractor saved 90% in labor costs by capturing pre-construction as-builts and building 3D models with Trimble TX 3D Laser Scanner and Trimble RealWorks Scanning Software.

EC Electric is one of the leading electrical contractors of Pacific Northwest with its portfolio spanning across commercial construction, technical systems, traffic management and service. In 2012, EC Electric was given a contract for the major expansion of Pierce Country, Washington’s Chambers Creek Regional Wastewater Treatment Plant. The project included creation of a virtual model of the facility using BIM and 3D as-builts as part of the project for reducing labour and improving productivity.

The project

The $342-million expansion project of the Chambers Creek Regional Wastewater Treatment Plant included many improvements with regards to increasing daily sewer capacity from 28.7 million to 45 million gallons; and replacing and repairing the ageing infrastructure. The construction of the plant also included establishment of a substantial new electrical package, and establishment of new controls and systems and upgrading power distribution.

But there were challenges. The professionals at EC Electric concurred that the project scope was large, and they were facing an accelerated schedule, including a cost of $250,000 for just data capture, which strained the budget.

The technology

To address the high costs associated with the data capture process, EC Electric purchased Trimble TX6 3D laser scanner since it claimed to offer the right combination of speed, range, and accuracy for capturing precise 3D spatial data. The scanner includes a built in wi-fi because of which stakeholders can remotely control the scanner via a tablet, mobile-phone or computer. A typical scan by the laser scanner is completed in approximately three minutes and can measure 1 million points per second.

EC Electric also purchased Trimble RealWorks Scanning software to use the data captured by the laser scanner and to quickly and efficiently create 3D models. The software allows users to import point cloud data from virtually any source and process it, analyze it and create high quality 3D models.

The process

Using  TX6 Scanner on the field, EC Electric was able to collect 3D point cloud data of the entire facility which was used with the RealWorks software for processing and analysis. The software was able to automatically register and classify 2000 Chambers Creek TX6 Scans with or without targets. This helped save substantial time in identifying elements. For instance, trees, foliage, and non-essential terrain were easily separated into a different cloud.  The software was then able to automatically ‘stitch’ or ‘combine’ the individual scans together into one big composite 3D point cloud model. The 3D point cloud model was then exported to the Autodesk Revit software to create as-built models of the facilities existing condition and a 3D model of the treatment plant using registered and classified data of TX6 and RealWorks.

By using TX6 Scanner on the field to capture data, EC Electric was able to immediately bring down the manpower costs to one-fourth. Instead of sending four people on the field like as estimated earlier, only one person was required to be on field with the scanner for data capture. In 25 days, EC Electric ran 60-70 scans per day, capturing at least two terabytes of data. Other than reducing manpower, the speed and accuracy of the scanner helped — 500,000 points per second and an accuracy of 2mm precision meant a significant increase in productivity.

Value proposition

By using TX6 3D system, EC Electric was able to complete the scanning of the entire project (as defined in the scope) in 300 hours – a 90% reduction in labor from the original test estimated. The system eliminated the risks for the electricians to work in confined spaces and in risky environments. Also, by using the software, EC Electric managed to conclude the project under the budget, especially as costs were reduced for scanning and collecting spatial data; and working with point cloud data was much more efficient, thereby reducing the modeling costs also.