Industry 4.0 / 5.0:
- Design principles in Industry 4.0 / 5.0
- Industrial Big Data and Analytics
- Industrial Internet of Things (IoT)
- Smart Manufacturing and Technologies
- Smart Factories
- Smart Devices and Products
- Cyber-physical Systems
- Cloud Computing and Manufacturing
- Machine Learning and Artificial Intelligence in Manufacturing
- Digital Production and Virtual Engineering
- Soft Measurements and Computing
Automation:
- Automatic Control
- Control Theory and Applications
- Linear/Nonlinear/Optimal Control
- Adaptive/Robust Control
- Control Devices and Instruments
- Components and Technologies for Control
- Programmable Logic Controllers (PLC)
- Control System Modeling and Simulation
- Fuzzy-logic and Artificial Neural Networks in Control Systems
- Emerging Trends in Automation and Control Industry
- Industrial Automation and Control
- Manufacturing Systems and Automation Process
- Automation Process Control and Monitoring
- Telematics
- CAD / CAM / CIM / SCADA
- Computers for Control
- Computational Intelligence in Control
- Information Control in Manufacturing
- Intelligent Traffic Control
- Chemical Process Control
- Control in Agriculture, Biological and Medical Systems
- Modeling and Control of Environmental Systems
- Artificial Intelligence for Cyber-Physical Systems in Automation
- Machine Learning in Control Applications
- Education and Training in Automatic Control and Systems
Robotics:
- Industrial Robots
- Soft Robots
- Biorobotics and Medical Robots
- Sensors for Robots
- Mobile Robots
- Humanoid Robots
- Human-Robot Interaction
- Rehabilitation robotics
- Intelligent Robots & Systems
- Mechatronic Systems
- Multimodality Human-machine Interaction
- Robot Control and Learning
- Cognitive Approach for Robotics
- Flexible Automation
- Emerging Trends in Robotics Industry
- Industrial and Manufacturing Trends in Robotics
- Autonomous Systems and Drones
- Unmanned aerial vehicles (UAV)
- Robots for Space Exploration
- Robotics in Defense
- Underwater Robots Network Robotics
- Telerobotics
- Nanorobotics
Communications:
- Industrial Communication Technologies and Systems
- Emerging Trends in Communication Industry
- Industrial Networks and Automation
- Real-Time and Networked Embedded Systems
- Network Control and Security
- Web-enabled Manufacturing Control and Wireless Automation
- Wireless Sensor Networks for Robot Navigation
- Distributed Networks
- Network Architectures and Protocols
- Intelligent Network Components
- Next Generation Networks
- Communication Theory, Protocols and Signal Processing
- Telecommunications
- Telecommunications in Smart Cities
- Wireless and Mobile Communications
- 3G and 4G Mobile Communications Services
- Satellite and Space Communications
- Global Navigation Satellites Systems
- Sensor, Mesh, and Ad hoc Networks
- Underwater Sensor Networks
- Radio Communications Systems
- Energy Harvesting and Power Management in Communication Systems
- Telemetry and Telecontrol
Special Sessions:
Wireless Communication Security for Industry 4.0/5.0
Physical layer security (PLS) utilizes the physical properties of the wireless channel to protect data from eavesdroppers. PLS is in contrast to traditional security approaches, which rely on cryptographic techniques to secure data. PLS can be particularly effective in Industry 4.0/5.0 environments, where wireless devices are often deployed in close proximity to each other and the data they transmit is often sensitive. PLS can be used to complement traditional security approaches in wireless networks. By combining PLS with cryptography, security can significantly be improved in wireless networks. On the other hand Radio Frequency (RF) fingerprinting is a technique that can be used to uniquely identify a wireless device by analyzing its radio frequency (RF) signal. RF fingerprinting can be used to authenticate the identity of a wireless device, ensuring that only authorized devices are able to communicate. PLS and RF fingerprinting can be used together to provide a more secure wireless communication environment for Industry 4.0/5.0 applications.
This special session will provide an opportunity for participants to share their research findings, learn about the latest trends in PLS and RF fingerprinting, and discuss the challenges and opportunities in this area, targeting, in particular, industry 4.0/5.0. This session is of interest to researchers and practitioners who are working on the security of wireless communications.
In this Special Session, accepted presentations can include, but not limited to, in the following areas:
- Physical layer security (PLS)
- Radio Frequency (RF) fingerprinting
- Physical principles of PLS and RF fingerprinting
- Design and implementation of PLS and RF fingerprinting
- Performance analysis of PLS and RF fingerprinting
- Applications and use-cases for PLS and RF fingerprinting
- in Industry 4.0/5.0
- New trends in wireless communication security for industry 4.0/5.0
- Security in smart manufacturing, smart buildings and smart cities
Session Chairman:
Prof., Dr. Ali Kara,
Gazi University, Turkey
e-mail: akara@gazi.edu.tr
Machine Development for New Manufacturing Processes
In the era of Industry 4.0/5.0, the development of machines for new manufacturing processes plays a crucial role in driving efficiency, productivity, and innovation. On the one hand, high sensing capability is needed to support data driven decisions on the manufacturing industry. On the other hand, new processes, namely direct digital manufacturing, are under constant research and often require new equipment development or retrofitting.
This session will delve into the multidimensional aspects of machine development, encompassing hardware, software, and communications considerations. Insights into the latest advancements in machine development, understanding how hardware components, software systems, and communication technologies contribute to optimizing manufacturing processes. The performance of a new machine is a consequence of the specification definition robust mechanical design, materials, and components, optimizing structure, motion control, and ensuring ergonomic and safe operation electrical design and automation, addressing efficient power systems, safety features, and integrating advanced software control systems and user interfaces and communication protocols for seamless connectivity, synchronization, and real-time data analysis.
In this Special Section, accepted presentations can include, but not limit, in the following areas:
- Hardware aspects in machine design
- Retrofitting
- Sensors integration in manufacturing processes
- IIoT and edge computing
- Machine control software
- Machine-to-machine, machine-to-human, and machine-to-system communication
- Case Studies and Best Practices
- Efficiency, precision, and safety in manufacturing
Session Chairman:
Prof., Dr. Daniel Afonso,
Universidade de Aveiro, Portugal
e-mail: dan@ua.pt
Contribution Types:
- Keynote presentations
- Invited talks
- Industrial presentations
- Regular sessions
- Special sessions
- Posters Exhibition
- Round tables and panel discussions
- Virtual Sessions (on demand)
Integrating Human Factors in Operation Management Models
Efficient production and inventory management are crucial for modern businesses seeking to optimize resource utilization and meet customer demands. However, the successful implementation of these models is not solely dependent on technological advancements as humans play a pivotal role in determining the real-world effectiveness of these strategies. This is in line with the concept of Industry 5.0, also known as the "Human-Centric Industry", which places a strong emphasis on the role of humans in the various processes and the need to consider human physical, physiological, and cognitive factors when designing and adopting new strategies and processes. By doing so, optimization or simulation models can better reflect the complexities of real-world decision-making and improve their accuracy and relevance to the problems they seek to address.
Integrating human factors into operation management models requires a multidisciplinary approach that combines domain expertise, behavioral science, human-computer interaction, and adaptive learning techniques. As such, this special session aims to explore the diverse aspects of assessing and integrating human factors into production and inventory management models, offering valuable insights into bridging the gap between theory and practice. The special session will provide a forum for researchers, practitioners, and industry experts to share insights and best practices. Speakers are invited to present case studies, methodology, or new models that integrate worker well-being, productivity, and safety in Industry 4.0-based practices involving techniques and technologies such as Artificial Intelligence, Digital Twins, and real-time decision-making tools. The aim is to discover the latest developments and best practices to operationalize Industry 5.0 strategies in the manufacturing and logistics domain. In this Special Session, accepted presentations can include, but not limited to, in the following areas:
• Human-Centered Supply Chain Design
• Assessment and integration of human factors in planning, forecasting,
predictive, and scheduling models
• Integration of human physical, physiological, and cognitive variables in
Artificial Intelligence or optimization tools, Digital Twins, and Industry 4.0
frameworks
• Assessment of employee Engagement in Industry 4.0 practices
• Integration of Lean and Industry 4.0 Practices
Session Chairmen:
Prof. Robert Pellerin
Polytechnique Montréal (Montréal, Canada)
e-mail: Robert.pellerin@polymtl.ca
Prof. Samir Lamouri Arts et Métiers Paris
Tech (Paris, France)
e-mail: Samir.lamouri@ensam.eu
Cooperative and Multi-Agent Systems
In an era of rapid technological advancements, the potential of cooperative and multi-agent systems to revolutionize the industrial landscape cannot be overlooked. The emergence of Industry 4.0/5.0 has created a demand for intelligent and flexible solutions, and multi-agent systems have emerged as a promising paradigm for addressing these challenges. Cooperative and multi-agent systems (MAS) come to the front line in industry 4.0/5.0 when it is much easier to carry out a task collaboratively using two or more machineries, instead of using one single machine. MAS have captured lots of interest among scientists in the previous decade and now, they are one the rapidly emerging subjects among the industrialists. In MAS, an agent can be any machine, parts of machines, or robot. These systems use the power of communicating agents to receive/send information from/to their neighbors to reach a common task.
At the heart of cooperative and multi-agent systems lies the concept of decentralized decision-making. By enabling autonomous agents to interact, coordinate, and collaborate, these systems pave the way for enhanced productivity, efficiency, and adaptability in the industrial setting. Moreover, MAS provide a framework for tackling intricate problem domains, such as scheduling and resource allocation. By leveraging collective intelligence and distributed decision-making, industries can optimize resource allocation in real-time, reducing costs, improving productivity, and better overall performance.
Furthermore, the integration of cooperative and multi-agent systems with emerging technologies like Internet of Things (IoT) and Artificial Intelligence (AI) opens up endless possibilities. Smart sensors, data analytics, and machine learning algorithms can augment the capabilities of multi-agent systems, enhancing their ability to perceive, reason, and act in complex industrial environments.
The ARCI’ 2024 conference presents a unique platform for scientists and researchers to showcase their cutting-edge advancements in cooperative and multi-agent systems for Industry 4.0/5.0. By exploring novel algorithms, methodologies, and application domains, we can push the boundaries of what is achievable and contribute to the transformative power of these systems.
In this Special Session, accepted presentations can include, but are not limited to the following areas:
• Decentralized decision-making
• Coordination in multi-agent systems
• Multi-robot systems
• Scheduling and resource allocation
• Consensus and containment in multi-agent systems
• Formation and surrounding in multi-agent systems
• Multi-sensor and distributed sensing
• Fault-tolerant multi-agent systems
• Adaptive and robust methods in multi-agent systems
• Internet of Things and Artificial Intelligence (AI) in multi-agent systems
Session Chairman:
Prof., Dr. Mahdi Baradarannia
University of Tabriz, Tabriz, Iran
e-mail: mbaradaran@tabrizu.ac.ir
Special Sessions:
Authors are welcome to organize and manage special sessions during the conference. Each session must contain 4-6 papers in a related field as specified above.
Session organizers will get:
- Certificate of appreciation
- Free registration for the event
- Special publishing theme within conference proceedings