Special Issue(24-13): Advances in Smart Robotics for Manufacturing | International Journal of Automation and Smart Technology

SPECIAL ISSE TITLE

Advances in smart robotics for manufacturing

Summary:

The emergence of the second industrial revolution marks the beginning of the robotic workforce for various industrial purposes. Robots were placed in various sectors of manufacturing which reduces human intervention significantly and with enhanced production. However, the involvement of the robotic workforce is restricted in deciding due to the lack of context awareness and intelligent thinking. However, the arrival of artificial intelligence and machine learning confers robots the ability to think & interpret a given situation and allows them to make intelligent decisions whenever needed. The performance of these intelligent robots (also called Smart robots) is far better than traditional robotics. However, the usage of smart robotics for manufacturing is limited due to their inadequacies. Limited improvement in precise force sensing resulted in a delayed response of robots which reduces their adaptation in accomplishing delicate tasks. For designing the training module of smart robotics enormous datasets are required which is narrow for many industrial processes. Moreover, the intelligent decisions made by smart robots need to be quality controlled to ensure the correctness of the decision and to further improve the decision-making process. The interaction between humans and robots in the workplace is still limited due to the risk of injuries. In addition, wired robots still need costly equipment and infrastructure to deploy and run. Smart robots capable of having enhanced interaction with robots would be better assistants in the manufacturing process and enhance productivity.

Advances in fabrication materials and methodologies of robotics, with novel AI algorithms capable of reasoning, had a transformative impact in industrial manufacturing. Reinforcing robotic parts with soft materials (like silicon polymers, artificial muscles) confer them a delicacy in performance which also increases their precise force sensing and thus proved to increase their response time to nanoseconds. Moreover, robots reinforced with soft parts can do delicate tasks with intricate details like humans. A combination of wireless technology with solid-state battery powering in smart robots would further extend their applicability by enhancing their versatility. Moreover, the development of nature-inspired deep learning algorithms increases the appropriateness of decisions by smartly analyzing the given scenario which has far-reaching applications in the industrial manufacturing process. Moreover, adaptive deep learning modules enhance the context-awareness of smart robots (during handling machines) by analyzing various physical parameters (like vibrations, the heat emitted, friction, etc). Technologies like this would reduce the need for large data sets for designing a training module and also reduce human intervention during automated processes. Robotic interaction inspired by human social interaction (also called CoBots), can truly interact with humans in a human-like fashion and mitigated potential downfalls in human-robot interaction. Thus innovations in deep learning methodologies would create sophisticated smart robots capable of working faster and smarter will certainly boost the progression of Industry 4.0.

Therefore this special issue forms an ideal platform for researchers, entrepreneurs, and programmers to present their unpublished works, reviews, and perspectives on recent innovations in development of smart robots for manufacturing processes in various industrial sectors.

List of Interested topics include, but are not limited to, the following:

Trends in digitization and learning applications in the process of industrial manufacturing.

Innovations in robotic intelligence for planning and execution of industrial process.

Research in robotic sensors for perception and context analysis.

Advances in big data analytics for robotic functions.

Emerging advances in fault detection and predictive maintenance of industrial robots.

Innovations in the construction of soft robots for intricate jobs.

Advancements in computer vision for detection and recognition of human face.

Trend in speech and gesture recognition in work place for improved interaction with humans.

Advances in bio-inspired algorithms for mimicking human social interaction.

Research in construction of wireless smart robots for enhanced performance.

Trends in identification of sustainable alternative power source for complete robotic automation.