Significant savings with mobile scanning: Infinited Fiber Company virtualized its factory spaces quickly and cost-effectively

Estimated reading time: 4 minutes

Infinited Fiber Company is constructing a large recycled fiber plant in Kemi within the premises of an old paper mill. The company required precise information about the space for equipment placement and commissioned both indoor and outdoor mobile scanning from Elomatic. This approach resulted in substantial savings in both time and money.

Infinited Fiber Company has globally unique technology to turn textile waste that would otherwise be landfilled or incinerated into high-quality fibers for the textile industry. In pursuit of their mission, the company is currently preparing to establish a flagship factory in Kemi within the premises of the old paper mill.

Point cloud as the foundation for design

Before commencing construction, Infinited Fiber Company needed access to point cloud data of the existing environment. A point cloud is a three-dimensional dataset composed of millions of individual points within a given area. This data enables precise positioning of equipment.

“Our design team is spread across Europe, and the distances to the factory are significant. Travel is costly and inefficient. Moreover, human memory fades after a few minutes, whereas a virtual model is always accessible,” explains Matti Reivonen, the Design Manager at Infinited Fiber Company.

The project could have been executed with a stationary scanner, but it would have taken significantly more time, with no added value in terms of accuracy.

Mobile scanning emerged as the optimal choice

The decision was made to conduct the measurements through mobile scanning, a cost-effective and speedy method as it is performed on the move. An alternative would have been traditional stationary scanning, where a device scans its surroundings from a fixed position. While this method can capture small details and provide highly accurate point cloud data, it is time-consuming, requiring the scanner to be moved over a thousand times for comprehensive data.

Heidi Laitinen, Project Manager at Elomatic, mentions that mobile scanning achieves sub-10 mm accuracy, which was adequate for this purpose.

“The factory has a vast amount of open space, making the mobile scanner an ideal choice. The project could have been executed with a stationary scanner, but it would have taken significantly more time, with no added value in terms of accuracy. Stationary scanners excel in scenarios like scanning paper machines where space is tight, and there are many details.”

Scanning conducted in two phases

Elomatic experts conducted indoor scans in February 2023 and outdoor scans later in the spring after the snow had melted. Before scanning, Elomatic performed risk assessments to address factors such as navigating dark and tight corners.

The project also involved total station measurements, which enabled the creation of coordinates and the alignment of the factory with its intended location. Thus, the new point cloud data aligned correctly with the previously established design model.

“Total station measurements can be thought of as the backbone, and the point cloud forms around it during scanning. Total station work is demanding because it involves a delicate device influenced by various factors such as temperature fluctuations and vibrations. There’s no room for errors as we need millimeter-level accuracy across a large area to generate precise point cloud data,” emphasizes Laitinen.

Designers empowered with a browser-based service

Elomatic provides customers with the point cloud data generated through scanning. For mobile scanning customers, Elomatic also offers a browser-based cloud service application, iReality3D. In this way, the persons selected by the customer can view the generated data, make their own notes, and download point clouds.

“Point cloud files are exceptionally large and occupy a considerable amount of space on network drives. With our cloud service, designers can access data even on their mobile devices. Navigation within the service is possible within the 3D point cloud or through 360-degree photo views captured by the device,” adds Laitinen.

Elomatic was the only one in Finland offering mobile scanning to us. We saved significant sums.

Successful outcome

Laitinen expressed satisfaction with her team’s results in Kemi, stating that each team member excelled in their respective areas. She also praised Infinited Fiber Company for their excellent cooperation and said that it is by no means a given that the customer is easily reachable.

Reivonen was also pleased with the outcome.

“It was evident that Elomatic’s scanning team consists of highly skilled professionals. Additionally, having access to a more detailed point cloud dataset and the iReality3D service, which provides a more realistic view, proved beneficial. Both are essential at different stages of the design process.”

Mobile scanning still uncommon in Finland

Elomatic has been using mobile scanning technology since 2021.

“There aren’t many players like us in Finland yet. We can produce data much faster, resulting in cost savings,” explains Laitinen.

“Elomatic was the only one in Finland offering mobile scanning to us. Fortunately, based on our trust in their expertise, we knew the service would be of high quality. We saved significant sums,” Reivonen adds.

Elomatic’s experts also contributed to the project by providing device design. According to Reivonen, this was highly valuable.

“It’s beneficial when the measurement team understands what designers need from the data.”

How does a point cloud form during scanning?

A point cloud is created during scanning when the scanner’s SLAM (Simultaneous Localization and Mapping) sensors rapidly measure millions of data points within the environment while simultaneously tracking the scanner’s position. Each point receives its own set of coordinates in a three-dimensional coordinate system, providing x, y, and z values. As hundreds of millions of points accumulate, a highly accurate representation of the environment emerges, allowing for the identification of features such as the location and dimensions of load-bearing structures.

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