Abdelmoula Khdoudi

Université Moulay Ismail de Meknes | UMI

In the context of Industry 4.0 and smart manufacturing, production factories are increasingly focusing on process optimization, high product customization, quality improvement, cost reduction, and energy saving by implementing a new type of digital solutions that are mainly driven by Internet of Things (IoT), artificial intelligence, big data, and...

The detection and localization of small and tiny defects on high-resolution images is considered one of the main challenges in the field of computer vision. In the manufacturing industry, the production speed and cycle time are considered the major target of a production process. For such reason, automated quality detection is getting even more com...

This study explores the application of machine learning algorithms for supporting complex product manufacturing quality through a focus on quality assurance and control. We aim to take advantage of ML technics to solve one of the complex manufacturing problems of the tempered glass manufacturing industry as a first attempt to automate product quali...

This study introduce the application of machine learning algorithms for supporting the manufacturing quality control of a complex process as an alternative for the destructive testing methodologies. The choice of this application field was motivated by the lack of a robust engineering technique to assess the production quality in real time, this ar...

Key performance indicators are tools for management, decision support and forecasting; they reflect the strategy and vision of the company in terms of objectives and allow to always staying in step with the expectations of the stakeholders. Accurate forecasting of the indicators allows decisions to be reoriented to ensure performance optimization w...

This research investigates the applicability of Deep Reinforcement Learning (DRL) to control the heating process parameters of tempered glass in industrial electric furnace. In most cases, these heating process parameters, also called recipe, are given by a trial and error procedure according to the expert process experience. In order to optimize t...

The overall equipment effectiveness (OEE) is a performance measurement metric widely used. Its calculation provides to the managers the possibility to identify the main losses that reduce the machine effectiveness and then take the necessary decisions in order to improve the situation. However, this calculation is done a-posterior which is often to...

In the present paper, a method of defining the industrial process parameters for a new product using machine learning algorithms will be presented. The study will describe how to go from a final product characteristics till the prediction of the suitable machine parameters to produce a good quality of this product, and this is based on an historica...

In the present paper, a method of defining the industrial process parameters for a new product using machine learning algorithms will be presented. The study will describe how to go from the product characteristics till the prediction of the suitable machine parameters to produce a good quality of this product, and this is based on an historical tr...