AI4CI - Data Management and Digital Transformation in Industrial Process Automation

This course, Data Management and Digital Transformation in Industrial Process Automation, focuses on providing the tools and knowledge necessary to effectively manage the data generated in industrial processes, as well as to implement digital transformation strategies that drive efficiency and sustainability.

Through case studies and cutting-edge studies, participants will learn how to integrate digital solutions that not only increase productivity, but also enable businesses to quickly adapt to market changes and new consumer demands. 

The relevance of this course lies in its ability to prepare professionals to face the challenges of Industry 4.0, thus fostering a smarter and more connected future.

About the AI4CI Master's 

This course is part of the European AI4CI Master Artificial Intelligence for Connected Industries. 

The AI4CI master is a European master opened at the universities Conservatoire National des Arts et Métiers (Cnam), Paris, France; Canm Grand Est (CGE), Mulhouse, France; and National Technical University of Ukraine (NTUU), Kiev, Ukraine; and as of the next academic year as well at the University of Ulm, Ulm, Germany; University Babeș-Bolyai (UBB), Cluj-Napoca, Romania, Avignon University, Avignon, France and Polytechnic University of Catalonia (UPC), Barcelona, Spain.

The master training program covers:

• Fundamentals of artificial intelligence and machine learning applied to networked systems
• Automatics and advanced automation, for industrial networks and robotics
• Advanced network architectures, IoT, and computer systems

The master teachers include world-class academics from our European partners and industry experts active in the master technical areas on international, European and national collaborative industrial research projects, standardization and open-source bodies.

Pedagogical objectives

• Explain the different layers that can coexist in IoT architectures in the industrial environment
• Know the main existing hardware solutions for data capture
• Know the main wireless communication technologies that can be found in the industrial IoT
• Know the possible functionalities offered by data integration platforms

Topics

1. Industry 4.0
2. Main sources of Industrial IoT information
3. Layers and architectures
4. Main protocols of each layer
5. Industrial IoT Gateways
6. New wireless communication technologies

Prerequisites

• Academic training in fields related to engineering, industrial automation, computing, information technology or related disciplines.
• Basic knowledge of industrial automation principles and industrial processes may be required. Familiarity with concepts of data management, data analysis and digital transformation. Experience in the field of industrial automation or data management may be beneficial.