The Logistics Situation
A global leading company in the beverage industry was facing recurring logistical challenges in its distribution operations. With a high volume of daily sales, the process of verifying products on delivery trucks relied entirely on manual inspection.
In this model, an operator would check the invoices and compare them with the loaded items. This approach, besides being time-consuming, was prone to human errors, leading to rework, delivery delays, and negatively impacting operational efficiency.
The complexity and volume of the operations increased the risk of discrepancies, which undermined client’s trust.
The Emerging Challenge
In this case, the urgent need was to optimize the operation by significantly reducing the time spent on vehicle checks, and increasing the accuracy of merchandise verification.
This required the solution to be sufficiently robust to integrate itself into the existing operational workflow, while maintaining accuracy and speed in the verification process.
Another important aspect was to ensure that the new system was scalable and capable of handling demands spikes, without compromising operational security or consistency.
Mouts’ Solution
To address these challenges, Mouts implemented a computer-vision based solution, using an intelligent algorithm to automate the verification process.
The innovation eliminated the need for manual verification, replacing it with a system that automatically reads and analyzes the products.
The operation workflow was redesigned to integrate the new technology:
The Results of the Solution Implemented by Mouts
Adopting the solution brought significant improvements in various aspects of the operation:
This advance not only optimized internal productivity, but also strengthened the company’s image as an innovative organization committed to operational excellence. The positive impact on operational performance indicators and client satisfaction highlights the strategic value of the implemented solution.
Technologies Utilized by Mouts
Python
Due to its versatility and robustness, this language was selected to be the primary developer of the algorithm.
The combination of OpenCV and TensorFlow libraries was fundamental in achieving the desired results.
This integration between the libraries allowed the algorithm to be not only accurate but also efficient, ensuring a fast and reliable verification process.
Azure
The selection of Microsoft Azure as the cloud platform was crucial for ensuring the scalability and security of the solution.
This cloud infrastructure allowed the solution to be easily scalable, ensuring high availability even during periods of high demand.
Count on Mouts’ expertise to find the best technological solution for your logistics scenario.