حكيم الفرشيشي

This role at B4Creation involves working as a Software Services Engineer and leading the Industry 4.0 team since September 2023.

The position includes responsibilities such as software deployment and configuration, technical support and troubleshooting, as well as system monitoring and maintenance to ensure reliable operation of industrial solutions. It also involves producing technical documentation and user training, while ensuring security and compliance across deployed systems.

In parallel, as a Team Lead for Industry 4.0 projects, the role includes project management and planning, system design and architecture, as well as research and development activities focused on industrial digitalization. Additional responsibilities include maintenance and continuous support of production systems and software solutions.

Keywords: Industry 4.0, Software Engineering, Project Management, System Architecture, Deployment, Troubleshooting, Monitoring, IoT, Digitalization, Team Leadership.

This project focuses on the application of deep learning techniques for the automatic classification of thyroid nodules, within the Laboratory of Biophysics and Medical Technologies (LRBTM). The goal is to assist in the early detection and diagnosis of thyroid cancer by analyzing medical imaging data.

The proposed approach is based on transfer learning using the InceptionV3 convolutional neural network, enhanced with a Convolutional Block Attention Module (CBAM). The CBAM mechanism improves model performance by enabling it to focus on the most relevant spatial and channel-wise features in medical images, leading to more accurate and robust classification results.

The system is implemented in Python and leverages deep learning libraries for image processing and model training. It includes medical image preprocessing techniques to improve data quality and consistency before feeding it into the neural network.

Additionally, SQLite3 is used for lightweight database management to store metadata related to the images, predictions, and experimental results.

Overall, this project combines advanced CNN architecture and attention mechanisms to improve automated thyroid nodule classification, contributing to more efficient and reliable medical decision support systems.

This project was carried out at FONDINOR and involved industrial electrical and control system work.

The main tasks included the design and implementation of a control system for an induction furnace, as well as the wiring of an electrical control cabinet. The work focused on ensuring safe and reliable operation of the furnace through proper electrical integration, control logic, and power management.

The project required understanding industrial electrical schematics, connecting and organizing electrical components inside the cabinet (such as contactors, relays, protection devices, and controllers), and ensuring compliance with safety and operational standards.

Overall, this experience strengthened practical skills in industrial automation, electrical installation, and control system commissioning, particularly in the context of high-power equipment such as induction furnaces.

This project at Votorantim Cimentos (Ciment Jbel Oust) focused on the study and design of an intelligent storage system to improve material handling and inventory management efficiency within the plant.

The solution explored the use of IoT technologies, including ESP32 microcontrollers, MQTT communication protocol, and Node-RED for real-time monitoring and control. These tools were used to enable connected devices, data acquisition, and visualization of storage conditions and stock movements.

The work aimed to optimize warehouse operations through automation, improved traceability, and smarter decision-making using connected systems and industrial IoT concepts.