IMS International Metal Supply
Data Control System Automation in an Industrial Environment
International Metal Supply (IMS), formerly known as EPUR METAL, is a France-based company specializing in the purchase and sale of non-industrial and recycled metals since 1969.
IMS provides reliable and professional service to international clients, offering high-quality metals for industrial use. Despite being located in France, IMS operates globally, ensuring efficient and personalized management in the trade of metals and raw materials.
IMS faced issues with data accuracy in its primary data retrieval software, where manual intervention often led to errors. These errors not only impacted internal control accuracy but also compromised trust in data values within an industrial environment with strict legal responsibilities.
This project implements a monitoring system that allows data duplication and its comparison within the primary software, detecting potential discrepancies or errors and enabling a faster response.
After a year of operation, values from the data monitoring and retrieval software show a high error rate
Our Solution
The first step was to implement a data duplication system using Dini Argeo’s native software. This allowed us to capture data independently of the main system’s manual data entry process. This strategy establishes an additional security layer by providing a second set of values that can be compared to detect any discrepancies.
Based on the data obtained, we developed a simple program that compares values from the data retrieval software and Dini Argeo’s native software. This program identifies any discrepancies, selects the correct value, and generates an automatic alert for the operation manager.
The alert system uses Make to automate the delivery of a detailed report with collected and compared data, allowing the team to react quickly to any anomaly and ensuring precise, real-time data control.
Results
monthly system maintenance cost
final cost of materials, installation, and programming
Reduction of human errors in data entry
