Guest Editors
Dr. C Chandru Vignesh, Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology, India.
Dr. M. Newlin Rajkumar, Anna University, Coimbatore, India.
Dr. Adhiyaman Manickam, University of Moncton, Canada.
Summary
The deployment of automated technology in daily life increases due to technological advancements such as artificial intelligence and machine learning models. Thus, automation pervades various industries, including healthcare, industry 4.0, smart cities, military applications and spatial applications. With the implementation of robotic systems in smart factories, it is possible to do assistive labour alongside humans. Thus, contact between human and automated machine interfaces is conceivable in various applications that use automation. Moreover, with human-robot interactions, current advancements in IoT, digital twin technologies, tracking systems, and virtual reality mixed with augmented reality deployments are potential. The requirement for interaction between human and machine interfaces is motivated by cost considerations, time efficiency, and set up conditions. Additionally, interactions are required to implement a comprehensive environment committed to an effective work structure that cannot be achieved just via machine interfaces.
Further, a production unit may be automated to a certain degree via different automated technologies such as predictive analytic techniques, deep neural networks, fuzzy systems, and cognitive tools. Beyond a certain point, human help must conduct further examinations and handle emergency circumstances. Even if the production environment is entirely automated, monitoring the manufacturing processes is necessary to eliminate uncertainty in industries. Certain situations involving tight collaboration between humans and machines may be efficiently handled by sensors, data gathering systems, predictive technologies, and data processing units For example, data processing might be accomplished more efficiently using blockchain and edge/fog computing, therefore enabling distributed computing of data. Certain industrial applications that demand direct connection between human and machine systems may be addressed via the deployment of AR/VR technologies. Moreover, the use of humanoid robots and robotic arm-like structures in industrial processes may result in various benefits, including reduced labour costs for repetitive tasks. Some of the issues associated with human-robot interaction in smart factories may be addressed via proximity sensors, robotic force limits, safety-rated monitoring functions, and separation monitoring systems.
This special issue sheds light on the deployment of robots in smart manufacturing and the resulting human-machine interaction. Thus, researchers and industrialists must analyse critical elements such as safety measures, quality control, and monitoring. The investigation might be conducted using current advances in artificial intelligence and deep neural networks, which improve the efficiency of human-machine interaction.
Deployment of CAD and vision aided robots in smart manufacturing for effective automation-as-tool deployment in smart factories
Futuristic deployment of digital twins in the application of smart factories and manufacturing process
Provoking deployment of Industry 5.0 in relation with human-machine interface deployment
Deployment of Augmented and Virtual reality systems for enhanced interaction of human-machine interfaces in smart manufacturing
Reduction in risks and injuries in smart factories with effective human-machine interfaces
Deep neural networks with blockchain deployments in assisting human-machine interfaces in smart factories
Optimised integration of assistive technologies and predictive systems for achieving adequate QoS in smart industries
Deployment of human-robotic groups in the joint decision-making process in smart manufacturing
Shared vision and control methods for deployment of mixed human-robot interfaces in smart manufacturing
Keywords
Automation; Industry 5.0; Human Machine Interfaces; Edge computing; Smart Manufacturing
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