The landscape of Robotics technology is evolving, pushing industries forward for a 360-degree approach to robotics. More so than before, today, robotic technology is progressing at a swift speed alongside its integration with technologies like Artificial Intelligence (AI), Simulation technology, Augmented Reality (AR), and Virtual Reality (VR). Robotics was always at the center of a future where industries are digital with automation at its core. However, industries that fully integrate AI and digital technology to enable automation with robots are still far away.
In the current world, car production and manufacturing is probably the industry with the highest level of robotic usage. One of the most prevalent uses of robotics and automation even in this industry is the Tesla manufacturing facility. Even though this is the case, Elon Musk, the CEO of Tesla, admits that robots are tough to automate and efficiently run without advancing digital technologies like AI and more innovative technologies like the Offline Robot Programming Software Platform or Robotic Simulation Services.
However, with the advent of Industry 4.0, the next industrial revolution, we will see some industries take a 360-degree approach to robotics through digital technology. Robotics technology is a crucial part of this transformation. Hence, enterprises will have to change their traditional policy to robotics with a new innovative and modern digital strategy to keep up with the changing industry and competitors.
With that said, industrial robotics is complex, in fact, very hard. With industries and production, the site the robots will have to work in is susceptible to all kinds of risks. These risks are not only limited to humans but also to the industry itself. Production environments generally contain various types of materials and substances that can create many unforeseen circumstances and problems. For example, rusts or corrosion of machine parts or robots, leaks, noise pollution, etc., are issues that the production will have to deal with almost regularly. Pair this with unforeseen problems in machines since they run all the time; industrial environments are very tough for robots to survive, which is why the 360-degree approach to robots is so important.
Not just the risks and problems for the robots, but the aftermaths of these problems and faults are more expensive to a production site. For instance, when a robot fails, or an installation of a new robot occurs, the actual production environment will probably suffer from its downtime. And industries do certainly not like downtimes. Downtimes lead to the stopping of whole production facilities and bar the production, resulting in the loss. Furthermore, this loss becomes more substantial if the materials or products that are not complete can go wrong. It will add the loss of materials and incomplete products to lower numbers of outgoing products from the factories.
Robotics in industries possesses more importance when it comes to error detection. Since production sites and factories can be dangerous and harmful for humans since they have to approach the machines to detect errors, it can be hazardous and even fatal in some cases. Hence, the emergence of drones and locomotive robots is rising in this department. However, industries are still taking the old approaches to use robotics and digital technology.
Industries generally shape robots around the production and use cases in the production sites rather than the inverse. Although typically, enterprises approach robotics as only a medium to replace human resources either in potentially dangerous places or tasks that may not be possible for humans to perform, the 360-degree approach to robotics in the future would only develop the technology further. Instead of this, industries and production facilities should shape themselves around robotics. Of course, it does not mean changing the particular industries’ end goal towards robotics and its implementation. Instead, it means to shape the industry so that it embraces robotics and involves it in the actual process and communication of the production sites.
Usually, robots in industries are linear, i.e., they are put in place of a human to speed up a process/task with a set of inputs fed to them by the developers or operators. They only do or set out to do specific functions inside the production line.
For instance, we can use a robot to put a product inside a box, put product stickers in packages, and seal the box. However, these robots only perform one task, i.e., a robot for placing products in a box cannot close it or put product stickers on it. Therefore, it limits the opportunities and possibilities that robotics can unlock. For instance, with the integration of technologies like AI, robots can become more dynamic and a part of the actual production process rather than the production line.
With AI and technologies like simulation, innovations like Offline Robot Programming Software Platforms are possible. With this, robots become more helpful; they can even participate in production processes to make them brighter and effective. Moreover, With the possibilities of self real-time optimization and self-diagnosis possible, robots will become able to report errors or possible errors in the future and solve those problems faster than humans ever can. And the time essential for robots to process what went wrong and determine if a possible solution is tiny.
In comparison, humans must first come across the errors, either after the error has already happened or detect it beforehand. Then such errors have to go through actual experts and need proper analysis. Only after this, a solution can come up which can fix the problem. But, unfortunately, the developers or the debug team may misinterpret the answer due to insufficient data or enough time. Even during this time, though, the situation can escalate, sometimes even forcing a downtime in the production. But the upcoming 360-degree approach to robotics would change it all.
With the integration of robotics from the start, alongside the significant goals of the particular industry, the actual use cases of robotics with more comprehensive and newer possibilities can emerge. It will let the industries access the actual use case they want from robots and the robotic technology more appropriately instead of focusing on what robots can do afterward, limiting the robotic possibilities. Only after integrating robotics with the actual goal or vision can an industry properly access what they need from robotics and other complementary technologies.
Every industry has a different need. Along with this need, various production systems and methods emerge. Hence, every industry or company may need something different from robotic technology. Even without using the latest or bleeding-edge technology, a company may fulfill its actual needs, i.e., every company need not use them. Hence, every industry needs to use and approach robotics differently to achieve their needs.
For instance, in a data-driven industry, the static robots that cannot communicate or process does not make sense. Since it's a data-driven industry, utilizing such technology in their robots will provide them with numerous benefits.
In an industry where robots and humans have to work together, human-robot collaboration makes much sense for the upcoming 360-degree approach to robotics. For instance, to perform a task like inspection of a faulty machine, robots can collect data from the air or the ground, while humans can analyze them and provide their insight. It becomes even more efficient with technologies like digital twins, AR, or VR.
3D models with digital twins can be much more efficient if industries integrate them with robotics. Automation becomes much closer while remote operations can thrive. With simulation technology, the training and testing of robots will become a digital endeavor rather than an inefficient, risky and expensive physical approach. Digital technology for robotics can enable rapid prototyping, higher form of product innovation, more advanced Research and Development (R&D), all the while remaining inexpensive, safe, efficient, and fast.
The 360-degree approach to robotics would also impact how we teach the robots as well. Technologies like offline robot programming (OLP) will enable robotics to evolve more rapidly. Offline robot programming replaces the traditional approach to teaching robots with Teach Pendants. Teaching pendants can be very slow, inefficient, and resource-consuming on top of being a significant cause of downtimes when it comes to teaching a robot. Pendants require robots to be out of production and in teaching mode the whole time during their programming. It increases downtime during the installation of robots and brings downtimes if the production house wants to upgrade the programming or coding.
But OLP replaces all that with a software model of teaching. The generation, testing, and verification of the teaching programs are possible through software simulations through OLP. OLP effectively eliminates the need to take out robots during its teaching process, allowing production to continue and robots to work even when training. OLP even opens a path for rapid maintenance, repair, and continuous upgrading of robots, all due to its teaching possible through software updates. Along with this, adopting simulation technology is another major win in terms of robot research and development. Simulations with AI can enable whole new ways of robot development, testing, and deployment. Pair this with technologies like Machine Learning, deep learning, and digital twins, AR and VR. Robots will then indeed be able to thrive. Companies like FS Studio that thrive in product innovation and advanced R&D technology can provide the industry with a much-needed push to propel themselves towards Industry 4.0. With over a decade’s collective knowledge and experience, FS Studio delivers a plethora of solutions for robotic technology and helps companies take a 360-degree approach to robotics.
Teaching robots is a time-consuming and laborious task, especially when you’re manually teaching robots. Particularly with robots of niche applications, use cases, and robots with complex movements or robots within specific environments like industries and production. Robotic technology is continuously evolving, and so is its complexity. However, robotic tech is also becoming easier to use, more accessible, and more adaptable with increasing complexity. Conversely, teaching robots through traditional approaches like Teach Pendants is getting more and more challenging and complex.
The Robotics industry is complex because of the sheer complexity of the technology and the cost of developing, building, and deploying a robot. Robot research and development and deploying robots are challenging tasks because of the sensitive nature of testing in robotics. Testing a robot is an expensive task. Consuming massive resources and time, testing robots along with training them is a very resource-intensive task.
However, due to the advancement of technology and the Fourth Industrial Revolution (FIR) inching closer and closer, industries are rushing towards digital technology and automation, which, in some scenarios like industries and production only possible with robots. Consequently, the importance of robotics in the production industry is increasing day by day. As a result, manufacturers and production sites are getting more eager to adopt their production line with robots with digital technology at its core. And manually teaching robots would only slow the production down and eventually leave you behind in the competition.
The Complexity in Robotics
With robotics comes its complexity. A robot is not a single entity but an integration of several different parts, components, and systems working together. These parts, components, and systems are usually various mechanical parts, motors, actuators, hydraulics, sensors, processing systems, networking interfaces, and many more. These components are very hard to build and even complex to perfect. Furthermore, integrating these parts to work together simultaneously with efficient cohesion to achieve a system that can perform specific tasks is complex on another level.
The integration may well be complete and the robot ready. But another major hurdle comes in the form of programming/coding the robot. Programming a simple robot with a particular function may be easy, but the robots that have to perform complex tasks while performing complex movements with precision are strenuous. This difficulty only scales up for industrial robots that have to accomplish tasks with accuracy and repeatability and perform various activities and functions within the production environment.
Why Manually Teaching Robots Will Hold You Back?
Programming a complex robot also requires a complex teaching process. The traditional approach to programming and coding robots is to use teaching pendants. Teaching pendants are a device that helps robot operators to control and program an industrial robot remotely. For example, these devices can code or teach a robot to follow a specific path or perform certain actions in a particular manner. With teaching pendants, robot operators or developers have to teach these robots manually.
Manual robot teaching may be easier on robots with low movement paths, simple actions, or singular axes. But industrial robots are a whole another story. They need to be constantly working in a usually adaptive and harsh environment of production. Such robots are complex and also very sensitive. Hence training the robots with teaching pendants is a difficult task. It is a very time-consuming task with the requirement of the teaching personnel to be present at all times. Furthermore, the robots have to be in teaching mode during all this time which means they cannot perform other tasks. Add this to the fact operators have to take them out of production during this long teaching process. All this makes manual teaching very cumbersome.
The downtime while teaching the robots is a massive issue to production. Moreover, this downtime is not only a one-time thing. Since industries have to be at the top of their game to thrive, they need to evolve and adapt over time. New changes and upgrades are necessary. Maintenance and repair works are inevitable. And even the failure of robots is not a common thing. All this requires teaching pendants, which is again very slow and a tedious approach to programming robots. It will add more delays, difficulties, costs and consume more resources. And this is a massive bottleneck for production.
Instead of wasting time in this slow and cumbersome manual approach, using new and better solutions with automation at its core is the way to go.
Learn About Offline Robot Programming
Offline Robot Programming is an “offline” approach to robot programming. Offline Programming (OLP) is a software solution to manually robot teaching by replacing the teaching pendants with simulation software. This “offline” solution teaches the robots virtually through software remotely. Thus, OLP takes leading away from the manual approach and takes out the requirement to remove the robots from production.
Although Offline Robot Programming is not a new technology, its evolution in recent years puts it in the spotlight in robot programming and the whole paradigm of robotics. It’s because of the advantages and benefits of using offline robot programming. Offline robot programming replaces the teach pendants with a more elegant solution. Furthermore, OLP allows for industries to train robots and their programming/coding through software updates. Robotic Programming Platforms also offer different software solutions to generate these instructions.
It means there is no need for the actual physical robot to be present in any generation phase or testing the training program/code. Instead, all this happens within the simulation technology inside the robotic programming platform itself. The evolution of simulation technology is so far ahead that it can now accurately simulate almost any object or environment with all the characteristics and behaviors of the original real-world object or environment.
Simulation technologies today can simulate every robot’s functionalities, features, and operations. Various behavior, states, and phenomena of robots and their components can simulate without manually teaching robots. Simulations can accurately simulate the mechanical elements of different parts with different materials and their operation in different environments and conditions. Along with this, fluid dynamics for air and water is also possible to simulate. Collisions, movements, etc., are also potential. It is due to the ability of simulations to accurately simulate and imitate the real-life physics of materials and the environment.
In addition to this, simulations can also imitate electronic components and processes. For example, it can accurately simulate the processing of CPUs and progressing units or even network interfaces and data exchange. Along with this, simulations can even test technologies like Artificial Intelligence (AI) with Machine Learning (ML) and deep learning. All these possibilities allow simulations to simulate all behavior, state, and properties of a robot along with its features and functionalities effectively.
Robotic simulation software solutions are already available, and different industries and companies are already leveraging their benefits. These simulations make innovative technologies like OLP possible to exist and thrive, creating manually teaching robots irrelevant. With offline robot programming, companies need not go back to the old approach of using teaching pendants. Such an old approach is very time-consuming while also requiring enormous resources, workforce, and investment. In contrast, OLP provides companies with elegant future-proof solutions that are effective and efficient.
OLP successfully reduces downtimes from production due to its ability to upload programming instructions in robots that they are working on without taking them out of the output. They can also enable new roads to generation and testing robot programs far from the manual testing method and age of robot codes or instructions. Simulations make it very easy to try these codes, while AI automation enables self-diagnosis and real-time optimization of production lines.
OLP is often seen as a technology that is very complex and requires high skills to utilize. There is a huge misconception that only the sides with deep pockets can afford to use OLP solutions, and there won’t be any demand for manually teaching robots anymore. But that is not the case. OLP solutions are pleasing on paper and easy to integrate and adapt even in existing production. Companies like FS Studio are working hard to bring out innovative solutions and state-of-the-art R&D technologies, including robotic OLPs, to make this transition of using OLP solutions smoother. With decades of experience and collective knowledge of various skillful people, FS Studio brings out solutions like Robotic Simulation Services for multiple companies and industries.
With the increasing pace of the industry’s move towards Industry 4.0, every industry is eagerly shifting towards digital technology while replacing old technologies like Teach Pendants with newer, more elegant, and efficient solutions like Offline Robot Programming platforms. Offline robot programming opens the road to newer possibilities and opportunities, enabling rapid prototyping, testing, training, and superior research and development, saving you from manually teaching your robots. In addition, it will help companies bring out efficient production and help them maximize their efficiency with a proven feat of achieving higher Return of Investment (ROI) in production lines and product innovation. Furthermore, this will help industries and companies innovate and remain at the top of their game to surpass and outperform their competitors.