Guest Editors
Dr. Dinh Tran Ngoc Huy, International University of Japan, Japan.
Dr. Esra SİPAHİ DÖNGÜL, Aksaray Üniversitesi, Turkey.
Dr. Pham Van Tuan, National Economics University (NEU), Vietnam.
Dr. Hoang Thanh Hanh, Academy of Policy and Development, Vietnam.
Summary
The current advances in sensors and autonomous systems play a crucial role in Industry 4.0. These innovations in sensors and autonomous systems facilitate a seamless connection between physical and virtual worlds. This connection is anticipated to accelerate the significant development of new goods and services. As a matter of fact ‘sensors’ and ‘autonomy’ are the two major buzzwords they are used almost interchangeably in the context of industry 4.0. These two are the key components in smart manufacturing facilities as it enables faster and more efficient production and management processes. In general, industry 4.0 deals with the use of automation and data exchange in the scenario of manufacturing. Thus, these two concepts, sensors and autonomous systems, form up the “smart factory,” where humans, machines, and systems interact with each other to coordinate and monitor the progress along the assembly line. The sensor data collected from the networked devices are digitally controlled by the autonomous systems and it helps design, modify, create, and customize the products in real time.
Practically, sensors are the most important tool for the collection of data. To establish automation and interconnectivity in the manufacturing sector it is extremely important to have new innovative sensors. The efficient use of the sensors and autonomous systems helps to measure and sense various factors such as system monitoring level, fault prediction, preventive maintenance, and so on. These applications include inspecting inaccessible places in the industry to check faults. Furthermore, sensors and autonomous systems allow the horizontal and vertical integration of the manufacturing systems and exploit the benefits via optimization tools. Emerging applications of autonomous modules in industry 4.0 also drive the need for novel sensor technologies, architectures and strategies that facilitate machine to machine verification and validation. The reliance on autonomous systems on sensor-derived and wirelessly communicated metadata poses issues for ensuring safe operation in complicated surroundings.
In addition, the process of manufacturing requires the execution of complex tasks and seamless performance. Since complex operations are involved in an industry, there is a high chance to face unexpected scenarios. Therefore, it is vital to develop devices and systems that exhibit common-sense reasoning that can draw assumptions and conclusions on their own before deploying them in the industries. Furthermore, the sensors play a key role in the efficient operations of the industry; thus, the deployment of a long-life sensor node is essential to avoid breakdowns. Furthermore, there is a need for novel strategies for energy storage and data processing and developing intelligent systems that adapt to surroundings and facilitate self-maintenance. Integration of autonomous systems in the existing manufacturing facilities is another big challenge since hybrid and heterogeneous systems are involved. Besides, there is a need for a practical and innovative framework to facilitate the seamless exchange of information understandable by all the heterogeneous systems involved. Addressing the issues related to high investment and ownership costs is also essential.
Topic of interest include but not limited to
o Innovative wireless sensor networks and architectures for industry 4.0
o Context-aware autonomous systems for industry 4.0
o Role of sensors and autonomous systems in fault tolerance and enhanced productivity in industry 4.0
o Advances in information acquisition: sensing and visioning technology for smart manufacturing
o New sensors and autonomous systems for information integration in industry 4.0
o Sensors and autonomous systems for enterprise modelling and system integration for smart manufacturing
o AI-based scheduling sensor algorithms for smart manufacturing
o Human–robot interaction systems, machine-to-machine interaction for enhanced productivity
o Modeling of smart manufacturing systems under the context of sensors and autonomous systems
o Challenges and opportunities of sensors and autonomous systems in industry 4.0
Keywords
Sensors; Smart Manufacturing; Information Acquisition; Artificial Intelligence; Industry 4.0
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