Quvo – Levenseat Renewable Energy: Optimized waste material management thanks to volume monitoring with LiDAR
Not all waste materials can be effectively recovered and recycled from the waste stream. To minimize landfill disposal, the remaining waste, known as residual waste, undergoes thermal treatment to generate energy. Levenseat Renewable Energy Ltd., a Scottish resource management company, operates a large waste treatment facility dedicated to this purpose.
Before the residual waste can be treated and incinerated, the incoming material is initially delivered to a spacious hall of 52 by 52 meters. This hall serves as a temporary storage area for the incoming material, predominantly municipal solid waste, which is not sorted yet. Subsequently, the waste undergoes processing in a material recovery facility to extract recyclable materials. Given the substantial size of the hall at the Levenseat site, precise data on current material levels is essential for efficient logistical planning and inventory management, as accurate inventory information allows for optimized processing and minimizes safety risks.
By deploying Blickfeld’s Volume Monitoring solution our partner Quvo has successfully replaced the previous, inaccurate measurement methods at Levenseat. The new solution provides the company with precise volume data in real-time, offering better control over the incoming material and enhancing overall operational efficiency.
Previously, the immense size of the waste stockpiles and the frequent movement within the hall to sort the material made it nearly impossible to accurately determine their volume using existing methods. Estimating incoming municipal solid waste relied on visual assessments and truck counts, resulting in distorted inventory data and ineffective inventory management.
In cases where excessive material accumulated in the storage facility due to process delays, such as outages, safety concerns arose. The sheer volume of waste posed fire hazards, pushing storage capacity to its limits and potentially requiring truck diversion, which negatively impacted logistical efficiency. Conversely, underutilization of storage space led to missed opportunities at times, as available processing resources were not fully leveraged, and less output was produced than what could have been achieved, which was ultimately reflected in the numbers.
To tackle these challenges, an automated, robust system was needed that provided accurate inventory data in real-time to enable efficient waste storage space utilization, logistical planning, and strategies to mitigate safety and economic risks.
Four Blickfeld Cube 1 LiDAR sensors were mounted to the hall ceiling to cover the large storage area. The laser-based technology continuously gathers data, constructing a detailed 3D image of the waste pile surfaces. The associated perception software utilizes this information to calculate the volume accurately. The volume data is then displayed on a user-friendly dashboard, granting the Levenseat team instant visibility of their current inventory levels with a simple click, even when they are off-site. This precise real-time data eliminates the need for manual inventory estimations and calculations, saving time and reducing efforts.
Thanks to these developments, Levenseat has gained the ability to enhance the efficiency of its waste storage facility and logistics through prompt responses to the current material situation. By making informed decisions about truck orders and adjusting processing loads accordingly, the company ensures an optimized operational workflow. This capability allows Levenseat to maintain the processing machine at its optimum capacity, proactively addressing safety risks and minimizing processing delays. As a result, Levenseat achieves improved efficiency and effectiveness in managing its operations.
Plans are underway for additional installations at a second site to expand the sensor system. This expansion will enable Levenseat to have real-time inventory data at multiple locations, allowing for enhanced inventory management, capacity planning, and overall operational efficiency across all sites.
