Aboudey E.

Maintenance Technician Test

- Corrective and preventive maintenance on automated robots.

- Programming of Siemens and Omron PLCs.

- Writing monthly reports.

As part of this project, I carried out an in-depth study on data from a CMMS (Computerized Maintenance Management System) to optimize the maintenance and reliability of radiology equipment used in a hospital environment. The main objective was to transform raw maintenance data into actionable information to improve the technical management and availability of the equipment.

The work consisted of collecting, cleaning, and structuring data from multiple sources (intervention reports, breakdown histories, downtime, maintenance costs, etc.). I then implemented statistical analyses and interactive visualizations to track key performance indicators (MTBF, MTTR, failure rate, intervention frequency, etc.). These indicators helped identify the most critical equipment and propose appropriate preventive actions.

The tools used for this project include Python (pandas, matplotlib, seaborn) for data processing and analysis, SQL for queries and extractions, as well as Power BI for creating dynamic dashboards for technical managers and biomedical engineers.

Thanks to this data-driven approach, the project has improved visibility into equipment performance, anticipated failures, and streamlined maintenance costs.

This work is part of a global approach to predictive maintenance and optimization of technical resources, demonstrating the concrete impact of data analysis in the biomedical field.