Semester A
Mandatory
Introduction to Industry 4.0 and 5.0
The course aims to develop an in-depth understanding of the evolution and future of industrial automation, data exchange, and manufacturing technologies. It introduces the technologies of Industry 4.0, including Artificial Intelligence, Data Science, Machine Learning, Deep Learning, Industrial Internet of Things, Cloud Computing, and Edge Computing, with emphasis on real-world use cases.
Learning Outcomes
1)
Understanding the core technologies of Industry 4.0: Artificial Intelligence, Machine Learning, Data Science
2)
Understanding Industry 4.0 and how it differs from previous industrial revolutions
3)
Identifying Emerging Technologies in Industry 4.0
4)
Understanding real-time data processing to boost productivity
5)
Description of the concepts of AI, Machine Learning, Deep Learning, and Data Science,
6)
Understanding data processing: cleaning, extraction, and feature selection
7)
Clarification, definition, and explanation of the terms, Industrial Internet of Things, and Industry 4.0
8)
An explanation of the role of the IoT and cyber-physical systems in Industry 4.0
General Skills
Data search & synthesis
Adapting to new techologies
Independent Project
Team Project
Interdisciplinary environment
Project Design & Management
Critical & self-critical thinking
Digital Transformation
Making technical decisions
Inductive & Creative Thinking
Syllabus
Week
Topic
1
Introduction to Industry 4.0 Technologies, Impact and Classification Tools
2
Principles of Data Science, Artificial Intelligence, and I4.0 Technologies
3
Cross-Industry Standard Process for Data Mining (CRISP- DM)
4
Machine Learning
5
Automated Solutions Based on Cloud and Local Implementations; Real Use Cases
6
Introduction to IoT and IIoT, Production Systems and IIoT Infrastructures
7
Communication Protocols, Key Development Directions
8
Introduction to Cloud Computing, Cloud Providers and Their Services
9
Introduction to Edge Computing, Real-World Applications and Implementation Challenges
10
Real-world applications
11
New Directions for Development
12
Ways to Address the Challenges of Industry 4.0
13
Project Assignment
Evaluation & Workload
Bibliographic Assignment
Project Implementation
Independent Study
Bibliography
Abdelmajied, F. E. (2022)
Hands-on Machine Learning with Scikit-Learn, Keras, and TensorFlow. O’Reilly Media
Géron, A. (2019)
Marinescu, D. C. (2023)
Misra, S., Roy, C., Mukherjee, A. (2021)
Ackerman, P. (2021)
IEEE Transactions on Industrial Informatics
IEEE Industrial Electronics Magazine
Journal of Manufacturing Processes
Journal of Manufacturing Processes
Sustainability
Course Information
Semester
Minutes per Week
180
Type
Specialized Knowledge
Requirements
Course Format
Synchronous
Asynchronous
Remote
e-class
Technologies & Tools
scikit-learn
Ι4.0 Technologies
CRISP-DM & ML
Cloud Computing
Edge Computing
IoT & IIoT