The current problems of the wagon space measuring:
Inefficiency: traditional manual measurement is time-consuming and labor-intensive, making it difficult to meet the demands of large-scale operations.
Inaccuracy: Manual measurement is easily limited by the skill and experience of the operator and is prone to error.
Limited automation: Many of the existing automated measuring devices are not yet able to adapt to different sizes and shapes of goods to perform fast and accurate measurements.
Inconvenient data management: The integration, analysis and storage of collected data may not be efficient enough to influence decision making.
Cost control: It is costly to invest in and ensure the operation of high-precision measuring equipment.
Luminwave’s solutions for measuring wagon space:
Fast measurement: the TOF camera can perform a 3D spatial scan every millisecond and quickly provide information about the load volume.
High accuracy: Determine the distance of objects through electromagnetic wave flight time, high accuracy, good detection rate for different sizes and shapes of goods.
Easy integration: The TOF system can be easily integrated into existing logistics management systems and is suitable for a wide range of applications.
Automated data processing: The TOF system, coupled with advanced algorithms, can realize automatic data collection, processing and storage, supporting instant analysis and decision-making.
Cost-effectiveness: Although the initial investment is relatively high, the improved efficiency and accuracy can significantly reduce long-term operating costs.
Value of the solution
Improved operational efficiency: Fully automatic volumetric measurement reduces operating time and increases freight throughput.
Cost savings: Improved loading efficiency and reduced risk of miscalculation directly reduce transportation and operating costs.
Improved service levels: The ability to provide more accurate freight calculations and estimates increases customer confidence and satisfaction.
Improved data governance: The data collected can be used for in-depth analysis to uncover potential optimization points and innovation opportunities.
Improved sustainability: Optimizing load factors helps to reduce mileage and carbon emissions in line with environmental standards and regulations.