Industrial robotics research and the quest to bring artificial intelligence closer to human social needs began earlier than most people realize. From the jet stream propulsion machinery bird built by Archytas of Tarentum (350 BC), dozens of industrial applications in medicine, manufacturing and construction are quickly becoming a common feature of everyday life.
Whereas previous generations of industrial robots were designed for motion control, many modern robots are autonomous. This self-sufficiency phenomenon is due to the development of artificial intelligence control and social learning paradigm. Evolution was fast and interesting. The leap from primarily moving conveyor belts on factory floors to performing complex procedures such as repairing heart valves is very attractive. We are now considering the integration of humans and robots that will revolutionize the industry.
Currently, industrial robotic arms can collaborate with humans in complex tasks. So what should we expect in the future, and what is the reward rate for this development? Here is a brief overview of some little-known facts about industrial automation and its future impact.
industrial robotics
Due to the rigid nature of traditional industrial robots, major tasks have been limited to repetitive tasks. These tasks were easy to perform and required very little human supervision. This job was suitable for robots because they worked faster and more efficiently on product lines that did not require modifications over their entire lifespan. This feature makes the robot a suitable alternative to an aging workforce and improves the turnaround time.
The biggest problem with these systems was their capital and time intensive nature due to this lack of robot flexibility. In principle, a successful transition to a new assembly line or even a small software update required a team of integration experts.
Move quickly with modern robotic systems. As a result, both the integrated system software and the flexibility of the robot increased, resulting in increased operating capacity. Advances in collaborative robots now enable simpler operation and more user-friendly technology.
Following the push for advanced manufacturing in Germany (2011), the pursuit of digitalization and full industrial automation has become possible. Cyber-physical systems have been successfully integrated through this process, called Industry 4.0. CPS now enables manufacturing plants to simultaneously monitor, control and coordinate physical and engineering processes.
This drive for digital transformation has fueled the Industrial Revolution, increasing interconnectivity within factories. And as the organization improved, operational efficiencies improved and productivity increased. At the heart of these advanced manufacturing frameworks are the IoT and other advanced technologies available today.
Emerging Technologies
Human/robot collaboration produces better results. Although there have been other cases where robots have stolen and injured people (Kawasaki Factory, Japan, 1981), this happened before modern technology displaced traditional robotics. The rationalization effect of collaborative robots has realized the dream of humans and robots working together safely in the same space. When fully integrated, there are several new technologies that will make the dream of human/robot collaboration a reality.
internet of things
The first step towards full autonomy is the integration of IoT technologies. Think of a scenario where smart gadget technology and advanced computing can communicate state information between a central database and an entire production line! You are looking for a fully self-contained system that optimizes all your production processes from one central control hub.
The result is complete autonomy. Machines that work efficiently, run in different directions and run fatigue-free for long periods of time without human supervision. Highly mobile collaborative robots that are versatile and can be reconfigured and repurposed for a variety of manufacturing functions.
self-driving car
AGV is a service robot powered by location and mapping based algorithms. These algorithms improve organization and control, allowing you to navigate the plant floor and move materials as efficiently as possible. The technology is still in its infancy, with only nine companies operating. The AGV utility comes from streamlining manufacturing functions with tiered data scheduling and round-the-clock factory floor logistics.
For large manufacturing companies, especially the automotive industry, AGVs offer opportunities to improve capacity and make production more efficient. The only problem here is that full cloud-based integration is still a dangerous debate given the constant threat of cybercrime. But with the right systems in place, businesses can effectively alleviate these concerns.
Production management (island problem)
Because many industrial plants operate individually, it is difficult to develop blanket algorithms for entire manufacturing lines. But what if businesses could connect their factory networks and coordinate entire production lines via the cloud? Many experts say this is impossible, but recent advances in the Industrial Internet of Things have made it possible. The principle here is the ability to optimize and control production across a company’s entire infrastructure.
Production control is a key focus of most emerging technologies and, if achieved, will change the face of industrial automation for decades to come.
simulation technology
This new technology demonstrates how well it fits into the capacity of robots in general and the value stream of specific companies. The idea behind robot simulation is to see the economic value added by robot integration compared to maintaining the current workforce. Before purchasing robot support, simulation allows companies to pre-determine the ROI and feasibility and cost/benefit coefficients of robot integration.
Simulation is a complex process. However, it can be transformed in real life if it includes augmented systems such as virtual reality. The challenge is to create simulation patterns with better predictive capabilities that effectively predict variables in complex situations. On paper, simulation technology is a huge step in the right direction, but the list of environmental and operational factors makes it difficult to mimic real-world situations.
conclusion
The industrial automation process was formed 60 years ago. When American engineer George Charles Devol programmed the machine to work like a human arm, the potential of industrial robots was endless. Robots now operate within and beyond six degrees of freedom that were considered impossible 70 years ago. All development since then has been to improve this feature and effectively redefine human/robot interaction for years to come.
Source: Plato Data Intelligence
