industry 4.0 - Robotic Simulation Services

Companies are swiftly adopting digital technology, with the whole industry moving towards the Fourth Industrial Revolution (FIR) or Industry 4.0. The ultimate end goal of almost all industries is to be self-sustainable, with automation at its core eventually like the Skyscraper Window Washing Robots. Subsequently, the industry has to adapt and integrate robotic technology in its operational process to reach this goal.

Robotics technology is rapidly evolving in both accessibility and usability. With this evolution, the technology is getting better and more usable, but the robotics market is also more valuable. Consequently, the robotics industry is currently one of the biggest markets of the technology paradigm.

In hindsight, the market also reflects this favorable shift of the industry towards robotics technology. As a result, researchers forecast that the global robotic industry market was more than 27 Billion US Dollars in 2020, with the other estimation that it will cross 74 Billion US Dollars by 2026. This increase in the market value represents an annual increase of more than 17%.

Furthermore, these figures will only increase in rate and estimation in the future post-COVID-19 pandemic era where work-from-home and remote technology is experiencing an enormous boost in development, accessibility, and adoption.

Robotics especially shines in industries where the work is either reparative or dangerous. Industries see this in retrospect in which various industries and production use robotic technology to achieve automation in repetitive and potentially dangerous tasks. For example, in the cleaning industry, skyscraper window cleaning is a hazardous task. With skyscrapers towering very high, the workers usually have to climb onto a platform that is hanging potentially even a hundred floors above with the support of a couple of wires.

Cleaning windows properly is just one of the problems when you are dangling hundreds of floors above the ground. With such high risk, the window cleaning industry rides on workers with steel nerves and a good cleaning capability. Although this business is lucrative, the lack of such workers and even companies that perform such risky jobs. The industry is also declining due to the same reason. With over 40 Billion US Dollars worth of market revenue every year, the window cleaning industry faces a lack of young talents to replace the old and trusty workers. The fact that above 74% of workers with training for such jobs are over 40 years old reflects this problem. Consequently, although a lucrative business, it's a dangerous job facing a severe lack of replacement workers.

One of the primary solutions to this problem is to remove workers from the task altogether. Therefore, replacing the window cleaning workers with robots is one of the possible solutions to eliminate human risk and increase efficiency and potential. Hence, window cleaning robots are growing in popularity in this business.

But to know how this all works, we first have to know about robots.

What is a Robot?

A robot is a programmable machine that can automatically perform specific tasks or take particular actions without requiring human assistance.

People usually imagine robots as machines with humanoid shapes with high intelligence, at least that is the depiction of robots in media and science fiction. But unlike robots in popular media and science fiction cultures, robots come in different forms, sizes, and uses. Furthermore, a robot is any machine with some level of processing power and can perform specific tasks without needing human intervention.

For instance, the disk-shaped machine/device that cleans the floor automatically while moving on its own and avoiding obstacles is a robot. Similarly, various toy robots and robotic kits are already available in the consumer market. Drones are also a type of robot that can fly autonomously, balance themselves and follow directions from human operators. Apart from the consumer market, robots are also widely in use in industrial settings. The most widespread use of robotic technology and robots is seen in industries and production sites.

A robot is not a singular device or a machine; instead, it combines various components, systems, and incoherence to perform multiple tasks. These components include sensors, processors, storage systems, power supplies, mechanical parts like wheels, arms, chains, cameras, actuators, rotors, motors, etc. These components, devices, and systems work together efficiently to behave like a singular unit and perform various tasks with collaboration and communication.

With the advancement of technology, various systems, including sensors, processing power, battery power, storage systems, motors, actuator systems, and digital systems, are getting more modern and efficient. With the constant evolution of these components, they are increasingly getting complex. However, increasing complexity also increases the ease of use, efficiency, and capability of these components. The whole robotic engineering paradigm reflects this increase with robots getting smarter, more capable, and more efficient in performing various tasks and jobs with increasing levels of autonomy.

The Case of Skyscraper Window Washing Robots

Skyscrapers are, as their name reflects, very tall and usually stand over 150 meters high. On the other hand, mega-skyscrapers are well over 600 meters in height with more than hundreds of floors. These skyscrapers also require a vast amount of maintenance, including cleaning their windows. But these skyscrapers are so tall that regular cleaners cannot clean them. So they need professional window cleaners.

Professional window cleaners usually stand atop a platform hanging beside skyscrapers and are controllable by a crane. This crane can take them downwards or upwards and sideways across the building. Although the media onto which the workers stand to have railings for safety, it still hangs above hundreds of floors above where one small mistake or mishap can end horribly. Besides these factors, the weather is also a significant factor that can increase the risk of window washing, especially if it is a windy season. So it is a pretty risky job from every corner possible.

Moreover, besides the danger of hanging beside such tall buildings, window cleaning is also a challenging job, with few workers even willing to climb onto the platform that's dangling hundreds of meters above the ground. This same case is why this business is so lucrative in the first place. Unfortunately, this is also becoming why new recruitments are getting complicated. With over 74% of the trained professional window washers being over 40 decades old, the replacement rate with young blood is thin.

Even if one does not fear heights, the job has a significant risk of losing their life, making it unattractive to many. The risk factor is very unfavorable with humans on the scale.

How Robots Make Skyscraper Window Washing More Safe?

Right off the bat, when robots are the ones cleaning the skyscraper windows, we can eliminate the risks of having humans on platforms besides the skyscrapers. When robots are replacing almost every human labor, it is essential to look into this factor where the risk of losing life is more than human labor. It will significantly reduce the risks along with having massive leverage if something does go wrong. Thus, we can remove the heavyweight of having potential dangers for humans.

With robots, maintenance along with cleaning is straightforward to perform. With the advancement in remote technology or even autonomous technology, window cleaning robots can leverage this by being controllable by humans or even independent at their tasks. With robots, workers can permanently bolt or fix the robots onto the lift mechanisms, significantly reducing the time consumption that would otherwise be used in checking harnesses or straps for human workers. It will reduce the turnaround times between jobs and save time significantly.

Not only will window cleaning become safer, but it will also become more efficient and fast while consuming fewer resources. Another significant advantage of using window cleaning robots is the economic benefit. These robots can work at almost any condition without stopping and even multiple robots for faster turnaround times between different jobs. As a result, it will undoubtedly bring more returns from the investment.

It will increase the work capacity of window cleaning companies and make the whole gig more economical for consumers. It will also be fascinating for the skyscraper owner to see the robot cleaning the window rather than being guilty of risking human life. Meaning it will attract more consumers and even less time between the cleaning cycles. It will increase the market value and revenue of the whole industry altogether.

FS Studio, therefore, provides robotic services like Offline Robotic Programming or even robot training and software development that can cater to the window cleaning business. FS Studio’s collective experience and knowledge from decades of research and development with solutions like Robotic Simulation Services alongside emerging technologies like AR and VR.

With expertise in Artificial Intelligence and technologies like Machine Learning (ML) and Big Data, FS Studio provides intuitive solutions for product development and innovative R&D technologies. FS Studio offers cutting-edge solutions for present problems and issues. It also empowers its clients with solid solutions that will also help them solve and tackle future challenges.

Skyscraper window washing robots are a massive step for window washing companies. They are safer, efficient, and cost-effective on top of enabling new opportunities and possibilities not only in end jobs but also on business fronts. With the Industry 4.0 approach, industries are transforming themselves towards digital technology to strive for automation. This goal relies heavily on robotic technology that enables intuitive solutions like skyscraper window washing robots.

The industry swiftly moves towards the Future Of Industrial Robotics, i.e., the Fourth Industrial Revolution (FIR). With this, industries and production plants are moving towards digital technology and probably reaching an efficient automation solution. To pursue this goal, industries are marching to develop their enterprises and production sites with robotic technology.

Robotic technology is increasing in sophistication and complexities. It is also going through a vast evolution of its use case and efficiency. In earlier times, where robots were much slower, inefficient, and less capable. While with modern technology, robotics now progresses much faster, with more efficient and competent robots. The robotic market is blooming with the advancement of sensors, communications technology, processing technology, storage systems, battery technology, and electronic components’ general efficiency and power.

This boom of the robotic market is not only for the industrial robotic paradigm, but even the common consumer market is experiencing this boom, its in pair with the increasing availability, accessibility, and ease of use of robotic technology at all sides. Consequently, today robots are not only available for industries and production plants but also in the general consumer space. Hence, the robotic industry itself is rising as a capacity market.

The robotic industry is growing at an unprecedented rate. With demands soaring through the sky, the robotic industry swiftly rises as one of the biggest markets. One of the most significant demands of robotic technology and robots is the industrial market with various industries and production sites. And since several types of industries currently “run” the world and robotic technology are at the forefront of these industries, it's one of the essential cornerstones of our future world.

With various robotic companies researching and developing innovative solutions and technologies within robotics, they are also propelling numerous industries towards success, efficiency, and even the future of the industrial robotics market, Industry 4.0. Furthermore, with robots simplifying and increasing the capabilities of industries, the robotic industry is also experiencing rapid growth. Consequently, researchers expect that the industrial robotic services alone will cross 4 Billion US Dollars in market value.

FS Studio is an innovative company that provides various state-of-the-art digital technology services like Robotic Simulation Services, Offline Programming, AI, AR, and VR. It also monitors the industry closely to prepare itself and its solutions to excel more in the future and essentially be future-proof. Reports from this monitoring help our clients and partners to identify various companies and opportunities lying within them. Furthermore, it will help them plan out different strategies regarding the robotic services they are planning to get and optimize their market position and plans.

deep learning boosts robot picking flexibility

Following are the ten companies that will dominate the industrial market in robotics.

Mitsubishi Electric

With its establishment of robotic systems in 1980, Mitsubishi Electric has possibly been the leader in industrial robotics with automation since then. The company provides its services with a wide range of robotic systems and automation solutions that help to improve productivity and efficiency around the industry. It also specializes in high-speed and precision performance systems in the industry. Mitsubishi Electric provides RH-CH compact Selective Compliance Assembly Robot Arm (SCARA) and articulated arm robotic systems and provides delta style robots from leader innovator or pick and place robots, Codian Robotics. Mitsubishi Electric generally provides lightweight and value-for-money robot systems with reasonable costs and a warranty of about three years in a robot purchase.

(ABB) ASEA Brown Bover

ABB, or ASEA Brown Bover, is a robotic company with an international reach in over 100 countries. With its establishment in 1883, ABB remains to be a leader in robotic technology innovation. ABB also holds the prestige to be a company to pioneer the first electric microprocessor-controlled robot and be the world’s first company to produce an industrial paint robot. It has sold over 300 thousand robot units worldwide by 2019 and remains a multinational robot company with expertise in the automation and motion department. Some of its essential products include FlexPainter robots (IRB 5500-22), Pre-machining robots (IRB 6660), Press tending robots (IRB 6660), Dual-arm robot YuMi (IRB 14000), and SCARA robots (IRB 910SC).

B+M Surface Systems GmbH

In 1992, B+M Surface Systems had a high reputation for automation systems and remained the leader in high-quality painting plants with automation and different surface application systems. As its name implies, it's a world-leading robotic company in surface design and painting, all from design and installation to maintenance and support. They help their customers in all fronts of robot technology usage with high customization for their customers. It is a leader in surface painting robots with products like Painting Robots with its T1 X5 Series robots and Adhesive Dosing Systems with its T2 X5 series robots.

Yaskawa Electric

In 1915, Yaskawa led its journey towards the robotic industry by releasing the all-electric industrial robot, Motoman, in 1977. Since its release, Yaskawa has sold over 300 thousand units of Motoman, which is an all-electric industrial robot. Yaskawa remains the leader in applications like welding, packaging, assembly and material removal, material cutting, and dispensing. It has sold vast numbers of products, including over 18 million inverters and 10 million servos. Its essential products include Arc Welding Robot with VA1400, Assembly Robots with HP20F, Pick and Pack robot with its G series robots, and Spot Welding with MH255.

Omron Adept Technologies

In 1948, Omron Adept Technologies was the leader in guidance systems with computer vision systems. It excels in designing and manufacturing these robots. It is also the largest robotics company that is based out of the USA. It usually provides cost-effective robotic solutions with the integration of various use-cases and automation.

Omron Adept Technologies also includes application software solutions with automation systems/equipment and mobile robots. Some of the critical robot products from Omron include Hornet, Cobra, eCobra, and Delta robot systems.

FANUC Robotics

FANUC is a leader in integrating Artificial Intelligence systems in robots and providing a wide range of industrial applications with robots of over 100 different models. It works on dynamic and smart solutions with AI integration and maintains its competitive edge with great flexibility. The FANUC robots are generally easy to operate, smart, and provide dynamic solutions. Some of the best FANUC robotic solutions include articulated robots of M-20B/25 series, collaborative robots with FANUC CR series, robots of R2000iC series, SCARA robots, and delta-style robots with M-1/2/3 series.

Kuka

Kuka is a German company that leads the robotic industry with its automated range of fully customizable software solutions with integrated robots with control technology and embedded automation systems. With its foundation going back to 1898, its focus and dedication to automation with robotics began in 2004 when the company either sold or closed other non-core departments to shift its primary focus towards automation and robotics. Some of the critical robotic systems of Kuka include Press-to-Press robots, Palletizing robots with its QUANTEC robots, some shelf-mounted robots, AGILUS robot system, which is a hygiene machine variant, and its KR AGILUS series, including KR 30 and 60 F series robots.

Epson Robots

EPSON is probably prominently known for its printing solutions in small printers. But the company was initially known for its automation systems and later became a major company dealing with various manufacturing sites with its different machinery solutions. Robotic technology from Epson excels in automation with several compact SCARA robots, PC-based and controlled robots. Its main products include G-series robots, SCARA with T-Series robots, and LS and RS series robots.

Kawasaki

In 1896, Kawasaki became a leading robotic technology company with over 160 thousand robot systems sold and installed. Kawasaki was thought to be the future of industrial robotics in Japan as it was the first company to commercialize industrial robots in Japan. It also pioneered and highly contributed to industry robot popularity and integration of various labor-saving systems and solutions. One of the most prominent products of Kawasaki has been its SCARA robot, duAro, which is a dual-arm robot with human collaboration capabilities. Some of its critical robotic products include Painting solutions with its K Series robots, Pick-and-Place robotic solutions with its Y-series robots, B-series robots for Spot welding, M series robots for medical and pharmaceutical solutions, and duAro SCARA robots.

Staubli

Though with a wide range of solutions, Staubli excels in Robots, Textiles, and Connectors. From its inception in 1892 in Switzerland with the textile business, Staubli began its industrial robotic journey devoted to quality engineering and factory floor solutions. Currently, Staubli also provides connector solutions with its expertise in both fluid and electrical connectors. With its accession of Unimation, Staubli is firm in its position towards being a most innovative industrial robotic solution provider company. It also provides various software solutions and various collaborative robots. Some of the significant products of Staubli include its RX series robots, TX2 series robots, CS series robots, TS80 robots, and TP90 robots. Various industries and production facilities are looking to invest in robotic technology. The whole industry is marching towards automation and its digital transformation to prepare itself for the future of industrial robotics with Industry 4.0. The robotic industry sets the path for these industries with its innovative robotic solutions and automation solutions. And these companies will undoubtedly be at the forefront when the industry sets its foot into this new landscape of Industry 4.0.

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.

Robot programming software is a software solution that helps program or code a robot for its use or operation. Offline Robot Programming Software is also the same.

With the advancement of technology, Industry 4.0 is inching swiftly closer towards us faster than ever. Industry 4.0, also known as the Fourth Industrial Revolution, is the age of digitization where every industry has digital technology at its core. Consequently, digital technology is continuously evolving. Today, it almost seems inevitable for industries to adopt digital technology instead of relying on the traditional approach to industry, manufacturing, and product innovation.

Robotic technology is also continuously evolving, with robots today more capable than ever in various fields and fronts, even unseen in the last decade. Moreover, with the complexity and sophistication of the robots increasing, they are constantly getting more and more complex to program, code, and even develop.

However, with increasing complexity in technology, it is also getting more and more adaptable, usable, accessible, and easy to use. It’s because newer bleeding-edge technological solutions help keep these complex problems and technology operable and functional with great ease of use and access. One of the similar problems regarding the increasing complexity is currently running alongside the robotic industry.

The Robotics industry is far more complex, risky, and resource-hungry than most technological undertakings out there. Due to the growing industry use cases for robot and their ability to fulfill these use cases. The nature of robotic technology is that numerous parts and systems converge together to form a single system unit that can perform various tasks and operations using these parts and systems. Due to this nature, alongside the already complex building blocks of robots, i.e., the components and different systems, integrating these building blocks to work in an efficient cohesion with each other is a huge undertaking.

For easing the difficulty of integrating different parts and systems, many state-of-the-art industries and companies are starting to use robotic computer simulations. Simulations are a great innovation of digital technology that can help develop robotics through research, design, development, and production. Moreover, even after production, robotic software can now help robot operations, maintenance, and programming with different robot programming software solutions.

What is Offline Robot Programming Software?

Offline Robot Programming software is an “offline” approach to programming or coding a robot. This “offline” approach takes the usual method of programming a robot, i.e., teaching pendants away while doing the “teaching” part through the software remotely. However, this remote programming of the robot takes away the need of taking the physical robot out of production; instead can program and code robots virtually through software.

Teach pendants the most common interface to program an industrial robot. The device helps control an industrial robot remotely and teaches them to move or act in a certain way. For example, these devices can program or code the robots to follow a specific path or perform a certain action in a particular manner. These devices also allow the operator to control and work with these robots without being physically present or in tether connection with the robot. It means robot programmers or operators get to control the robots and “teach” them remotely. Technicians usually use these devices for testing or programming, or coding of industrial robots. Hence, teaching pendants are a crucial part of industrial robotics.

Offline Robot Programming Software replaces this teaching pendant with a more elegant and efficient solution with the power of software and simulation technology. Due to the control over robots with software since robotic OLP or Robotic Offline Programming allows for uploading programs and codes through software updates. Furthermore, software developers and robot operators can generate these programs and codes through robotic simulation software in a PC rather than using the robot physically. OLP is, therefore, a more elegant, efficient, and more modern way to program industrial robots.

Why is Offline Robot Programming Software Important?

Even though these pendants are helpful and crucial to industrial robotic operations, they remain one of the bottlenecks of industrial robotics. Right off the bat, these devices are very slow and time-consuming. It's also very resource-consuming and requires personal at all times to operate. Furthermore, pendants also require the presence of the actual robot. They need the robot to be physically active in the teaching mode rather than doing other work during the teaching process, which is usually very long.

Hence, during teaching, the robot cannot be in production or be doing other functional tasks teaching process is very lengthy and tediously for the more complex robots with various joints or movement points and axes. The robot programmer has to program multiple joints and parts to code the robot manually, which is very time-consuming. The programmer will also have to take out the production robot during and until the teaching process. It will surely hamper the production line, and hence downtimes become longer.

In any industrial setup, the production line is the most vital part of it. So much so that the whole manufacturing or production plant usually is based around it. Holding such importance, the optimization of production lines is a very crucial task in any industry. Downtimes, irregularities, or faults in the production lines and components around it means it directly hampers the sector. Moreover, machines like robots, especially the ones with automation, are very crucial in production lines. Hence, production lines must not stop nor deter it due to the robots.

However, with robotic OLP, industries can remove and eliminate all these disadvantages and bottlenecks from production. Instead of teaching these industrial robots online, offline programming eliminates the downtime for programming these robots completely. With this power in their hands, production lines can now completely get rid of time for programming. Instead, industries can use all these times in the actual production and get better returns.

With OLP, automation comes one step closer in production setups. Offline Robot Programming software enables rapid prototyping to test programs and codes before uploading them to the robots through simulation software. Furthermore, simulations are now very technologically smart such that they can simulate all robot parts, mechanics, systems, and movements. With such capability in hand, robot programming and even robot development and the building will become very easy. Due to this, testing, training, and evaluating robots virtually become very easy through OLP. Furthermore, it allows for error detection and verification of programs and robot capability to perform tasks and operations even before they are physically present.

Apart from this, Offline Robot Programming software also increases the productivity of production lines and robot operators and developers. Furthermore, OLP also provides greater profitability and has a better Return On Investment (ROI). Moreover, with OLP, one can test and prove new and better project or concept ideas in their quotation phase without investing in physical resources.

OLP allows for not only training and testing but also helps in maintenance and repairs too. OLP can help to track down potential faults and errors even before they occur or after they occur. It further makes the production efficiency and without any downtimes possibly in future too.

Not only is OLP advantageous and beneficial for regular industrial robots, but it's also essential and can be a boon for some industries that involve high risk. For example, industries like aviation, nuclear, automotive are very high-risk industries. Testing robots in these industries is a sensitive matter. Hence OLP is a requirement in these industries to train and test robots efficiently. Furthermore, without, OLP it is likely not even possible and feasible for industries like the space industry able to undertake projects and accomplish them.

Offline Robot Programming software is generally seen as a technology with high complexity and requiring very skillful personals. But that is not the case. Various companies like FS Studio provide solutions when it comes to offline robot programming. Companies like these can help industries get started with OLP and thrive on enabling substantial new possibilities and opportunities. With decades of experience and expertise in fields like Artificial Intelligence (AI), Virtual Reality (VR), Augmented Reality (AR), and Simulation technology, FS Studio, can provide companies with proper and efficient OLP solutions to propel their industries with more efficient, safe and effective production lines. With the advent of Industry 4.0 upon us, companies and industries now must look for better alternatives and modern approaches to the industry. Digitization of industries is the future where digital technology will be at the core of all industries with efficient and smart solutions. OLP with simulation technology enables rapid prototyping, testing, development, and superior research and development (R&D) along with faster and efficient programming or coding of industrial robots. Furthermore, industries can collaborate with different OLP providers to determine the best solution for their particular industry and production and help them integrate their existing robots and production for a more smooth transition towards Offline Robot Programming Software.

The advent of next-generation technologies like Simulations, AR, VR, and AI continues to grow rapidly. With continuous evolution in their advancement and increasing accessibility, they can exponentially add value to manufacturers. Hence, influencing industries across the globe to adopt these technologies at an increasing rate. For example, artificial intelligence with immersive technologies like AR and VR swiftly transforms manufacturing processes and product development. But, on the other hand, robotic technology redefines the possibilities and opportunities in various fields and industries.

The increasing sophistication of robotic technology is visible due to giant leaps in the capabilities of current robotic systems. With technology evolving swiftly, the industry is also adopting newer technologies in its manufacturing and product development processes. One of these newer technologies the industry is moving towards is simulation technology.

With the dawn of Industry 4.0 upon us, industries undoubtedly need to advance towards digital transformation. In this advancement, simulation technology is a boon for manufacturers. Although simulation technology is not new due to its rapid evolution in recent years, it is expanding its horizon of possibilities and opportunities. Robotic technology is one of the unknown frontiers of simulation tech.

Simulation software has the power to enable rapid prototyping, testing, and development of product development processes and R&D technology. Computer simulation is one of the vital tools for industries like robotic development and manufacturing. With the crucial role of robots in the manufacturing industry, the development and advancement of robotic technology are significant for the whole manufacturing industry.

Why Simulation Softwares in Robot Development?

Robot research and development, along with its design and production, is very complex. It is not just because of the sophistication of the technologies in a robot. But also because of economic reasons and risks in robotic development. They also have to add value to the manufacturers as well.

Robots are usually expensive pieces of machinery. Industrial and manufacturing robots are costly due to the niche application following the niche research and development requirement. Moreover, even general robot design and development require massive resources, cost, time, and multidisciplinary skills. Furthermore, prototyping robots for testing, evaluation, and assessment need equally, if not more, resources, time, cost, and abilities. Add this with risks present in the real world, and robotic development truly becomes a huge undertaking.

Computer simulations for robotic development can solve all these problems. Computer simulations offer efficient and elegant solutions that are more cost-effective and less time-consuming. Any computer simulation software usually provides a 3D digital space to test and develop a product. Similarly, robot simulation software offers different environments and tools in a digital 3D area to test, run, research, evaluate and develop a robot.

Real robots in the real world consist of parts like motors, batteries, joints, arms, sensors, actuators, controllers, and other mechanical parts. Furthermore, robots also consist of networking, processing, and data handling components to analyze data and communicate. Apart from this, some robots also need to be smart and capable of making various decisions in real-time to add value to manufacturers. Consequently, due to these causes, robots in the real world are very complex and expensive.

However, robotic simulation software provides all these tools, components, and parts in its digital space. Due to the high advancement of simulation software, today, simulation software can simulate all these parts and subsequently a fully functional robot that can run/operate in different conditions and environments. One just has to bring these parts and models together digitally. The simulation software also supports the design and development of these parts and models digitally. Hence, developing or putting together a robot in a simulation environment is very quickly relative to the real world.

Moreover, just like in the real world, robotic simulation software also allows for the testing and evaluation robots in different environments and conditions. Simulation software can simulate fluid and air dynamics, collisions, and many more physical, real-world phenomena with very accurate and modern physics that reflect real-world physics. All this happens similarly to the real world, except the simulations are fast and easy to develop and do not have to suffer huge risks and significant economic setbacks.

With computer simulations on hand, the risks and costs in association with robot development become redundant. It also ensures that the developers do not exhaust their time worrying about resources and cost but instead focus on the actual robot development. It also provides the developers with flexibility and space to develop the best robot for their requirements without compromising developmental risks and costs.

How they Add Value to Manufacturers

With the vast advantages of using simulation software in robotic research and development, manufacturers are beginning to realize the potential it carries. Furthermore, minimizing risk in robot development in manufacturing and factories also means developing robots with better design that suits the requirements to a far greater degree. As a result, companies or factories using robots in various product manufacturing processes can undoubtedly reap the benefits of better and cost-effective robotic solutions, which is possible due to robotic simulation software.

Proper simulation software can ensure the best systems for different applications and use cases. With rapid design and development in the card, even if a system is not up to the mark, companies can simply re-design it in the digital form with much lower costs and resources. In addition, with computing systems becoming cheaper and efficient, simulations can now help manufacturers build their robotic solutions to stay competitive in the market with new and better solutions.

There are numerous ways the robotic simulation software can add value to manufacturers, for example, cohesion with better designs, processes, and efficient investment.

With manufacturers expanding their product spectra to a wide range, robotic systems in use are not always general robots but tailored with specific needs and requirements in play. For instance, a car manufacturing company cannot automate the assembly line process without the same robots. Development of robots enters completion with niche use cases in mind. One robot installs engines while another robot paints the car; another robot detects flaws in the painting. Another installs wheels, another lifts machines before installation, and so on. Each different use case requires another robot.

Hence in this scenario, designing different robots for different use cases in the real world is very expensive as well as being time and resources consuming. However, creating robots for other use cases is much simpler, more accessible, faster, and cost-effective through simulation software. Consequently, robotic simulation software can also help manufacturers to customize and fine-tune robots according to their needs. Moreover, such systems can undergo design and development to seamlessly fit into their existing facilities and systems quickly relative to traditional methods.

Automation also becomes much simpler with the capability of simulation software to test automation and smart technologies in a full-blown manner even before the final design is ready. Furthermore, simulation consisting of accurate and minute details add value to manufacturers, helping them configure their automation system so that the resultant robotic systems can meet their goals. However, manufacturers usually have to take significant risks for proof of design and automation process verification without simulation systems.

Due to all these advantages, simulation systems can return great results on the manufacturer’s investment. Furthermore, simulation software capable of self-diagnosis and automatic error reporting ensures that the finished designs and products are free of errors and potential flaws. It also ensures that the robotic simulation systems function with precision with known efficiencies in different environments and conditions. Thus, it helps manufacturers get maximum returns on their investment.

Moreover, the investment also becomes largely more safe and secure relative to the investment in traditional approaches. Furthermore, with the successful design and development of robots or systems meeting all requirements and needs beforehand, manufacturers can ensure further lucrative benefits and returns. Eventually, the end goal of manufacturers is to get returns from the end product. It largely depends upon the manufacturing process, which depends on the systems and procedures, including robotic systems used for manufacturing.

Hence, ultimately a successful result is a massive win for manufacturers. Robotic simulation software ensures that this result is successful and that the manufacturers get there with much lower costs, resources, time, and skills.

Conclusion

Industry 4.0 or the Fourth Industrial Revolution (FIR) is all about the digital transformation of enterprises. With Industry 4.0 approaching more closely than ever before, industries and manufacturers must keep up with advancements in technologies like simulation and artificial intelligence, AR, and VR. While it may seem that the transition to digital technology and simulations for product innovation, R&D, and robotic development is complex, the result in-store has enormous benefits with lucrative returns.

Hence, companies like FS Studio are working hard in these innovative technologies to ensure that manufacturers can experience a smooth transition to Industry 4.0. For example, ZeroSim, a technology in development and service by FS Studio, is a robotic simulation software technology built on Unity3D, a game engine, and ROS (Robotics Operating System). It provides a multitude of tools for building robots and simulation environments in Unity to interface with ROS.

Technologies like these add value to manufacturers, making robotic simulations faster, easier, and hassle-free to use for manufacturers. It also ensures that manufacturers can easily leverage the lofty benefits of robotic simulation software to transition themselves towards the next industrial revolution.

Robotics technology is continuously changing and evolving. With the development of simulation technology, the current industry is rapidly moving towards digital solutions together. With industries on the verge of shifting towards Industry 4.0, digital technologies, simulation technology, AI, AR, and VR will be the most critical pivot points. Robotic technology in industries and manufacturing processes provides vast benefits and advantages. Robot integration in production, manufacturing and other industries gives them cost savings, lower time, and efficient resource usage. Together, it all can help us to explore offline robot programming software solutions.

The traditional robotic training, testing, and operations method pales in comparison to the influx of modern demand and supply. Consequently, various industries are looking to make their supply chain from production to distribution more efficient and cost-effective. So naturally, robots are the ultimate answer for automation and efficient completion of a process with precision.

Along with the advancement of technology, industries across different fields are now looking to integrate their operations with robotic technology. However, robotic development is not an easy feat. Due to the sheer complexity of robot development and research, some industries are hesitant to adopt robotic technology. Nevertheless, the cost-benefit analysis of the development and use of robotics is simply too lucrative to ignore.

However, with the traditional methods of robot development, testing, and training, various industries cannot move towards it. Furthermore, it brought several misconceptions in the industry that robotic programming is too complicated and too resource-heavy to use. With these misconceptions, the industry was hesitant to take on the challenge. Even though offline robot programming has come a long way from its inception, misconceptions still linger around the industry with false beliefs. Words go around that it cannot handle all the variables present in real-world development or complicate things compared to the traditional approach.

Robot Offline Programming is an “offline” approach to programming that takes the robot programming away from the traditional pendant/robot cell and physical robots in production. Instead, Offline Robot Programming allows users to generate robotic instructions or code from their computers and different software solutions instead of using a robot on or taking it out of production.

The idea is simple; remove the traditional method of generating robotic instructions and code, i.e., using teach pendants and replace them with computer software or simulation software. It was necessary because the conventional process of using teach pendants or robot cells for robotic programming code was too inefficient and time-consuming. Pair this with the fact that it constrains profitability and business growth. It then becomes a throne in the process of robotic research and development.

Teach Pendants are devices that robot developers/operators use to control an industrial robot remotely. Teach pendants to allow users to manage and work with robots without connecting the device with a terminal but instead works wirelessly, i.e., no tethering to a fixed terminal. Technicians use these devices to test a robot either for programming, i.e., robotic coding or repair, or for performing some maintenance. Due to this, teaching pendants are a crucial part of industrial robotic operations.

However, using pendants is time-consuming. It's prolonged and even resource-consuming. Hence, the replacement of these traditional devices with offline robot programming software is necessary. It will allow users to operate robots either for testing or repair or maintenance or even robotic code generation with much efficiency and simplicity. Furthermore, it enables robot developers to perform all these actions through their computers without even taking out the robot from production or if it is not fully ready to be operational. Thus, it radically maximizes productivity and even reduces cycle time and downtime of the production.

Offline Programming or OLP solutions are therefore sought after by industries looking to utilize robotic solutions. Due to the advancement of simulation technology and offline programming software, it's becoming faster, more reliable, and more efficient to use OLP solutions than the traditional approach. Simulations and offline programming may differ because simulations exist without offline programming, but offline programming cannot live without simulations. Although this might make simulation and OLP seem different, they go hand in hand and sometimes are used interchangeably.

Robotic OLP can exist because of robotic simulation technology, which is currently one of the most frequent use cases of simulation technology in industries. With simulations enabling 3D representation of a robot, i.e., its digital twin, it can also represent and reproduce robotic functions, movements, behaviors, and operations in different conditions and environments. Thus, It essentially enables Robotic OLP to exist.

Although simulations make it easy to generate any environment for any use case, knowing these requirements beforehand is necessary to see the type of service one requires regarding OLP solutions. Along with this, there are some other things one needs to consider when exploring Robotic OLP.

Some of the things to consider when exploring Offline Robot Programming Software solutions are given below:

Offline Robot Programming is a technology that enables rapid programming with efficient processes and even automation in the mix. It is advantageous and beneficial to perform robotic coding for robots with complex structures, numerous moving parts, and axes or programming complex paths. These complex programming tasks generally take a massive amount of time, resources, and hard labor with teaching pendants, while it's straightforward, efficient, and swift with OLP.

OLP and Simulation technology go hand in hand. Only through the utilization of robotic simulation software can Offline Robot Programming exist. A robotic OLP is a robotic simulation software with features and functions that tests and evaluates robots in different conditions and environments of different needs and requirements around a production environment.
OLP can efficiently train, test, and evaluate robots. Hence training technicians or users for OLP is relatively straightforward. It is also very advantageous since after learning an OLP solution, it becomes easier to understand others.
Robot Offline Programming Software solutions increase the user’s productivity and the profitability of the industry/business using it. It also has a greater return on investment (ROI) relative to traditional approaches.
OLP is very useful for potential projects ideas in their quotation phase to prove their profitability and efficacy.
OLP is very efficient in tracking down any errors or faults, and potential problems in a robot before uploading programs or the robots are in operation.
Due to the nature of OLP, i.e., allowing users to program robots remotely without the need of the actual robot, it opens new possibilities for existing robot operations. Operations such as in high-mix and low-volume can explore more opportunities.
Some industries like aviation, automotive, nuclear, and space need OLP as requirements due to the nature of these industries. OLP provides massive benefits to these industries where on-site robot programming is improbable and sometimes even impossible.
OLP allows for testing in simulations through the use of various engineering tools and utilities available. Hence, it will enable testing a solution or modification thoroughly before making any actual physical modifications.
Robotic Offline Programming is now industry standard with an image of a superior software tool allowing for better returns and efficient solutions. In addition, it will enable industries to use OLP to attract high-quality staff and employees with a high chance of retaining them longer.
Due to the nature of OLP being a software tool, configurations for machines can be saved and reused on different devices instead of starting from scratch. It is a huge plus for some manufacturers/companies who have to configure large amounts of robots. Instead of having to program each robot from the start, OLP is very useful since edits and re-configuration of programs for each robot are possible.
The use of OLP also attracts other prospects like Robotic Simulation Softwares for the design, research, and development of robots. It is a very efficient and beneficial solution that allows for rapid growth, testing, and prototyping of robots at lower costs, less resource usage, and better efficiency.
Offline robot programming is a huge win when put in comparison with traditional ways of robotic programming. Allowing for a far quicker robot deployment or installation, OLP allows for rapid testing, fine-tuning, and programming a robot in a virtual environment in just days when the traditional method may even take weeks.

Furthermore, with virtual environments to teach the robot, downtimes are no longer present when teaching the robot a new programming or operation path. OLP can even upload new programming in the robots when in a live production environment or when it is operating. Apart from these, safety, quicker cycle times between teaching the robots, or a straightforward approach to test a new configuration, all are easier to perform through OLP.

Various companies like FS Studio provide OLP solutions to make it easier for companies/industries/manufacturers to adopt OLP solutions in their existing production environment. FS Studio provides Robotic Simulation Solutions crucial for OLP solutions with a decade of collective knowledge, experience, and skills in store. It helps the production team to focus on the actual product rather than shift their resources in offline robot programming implementation and adaptation. Nevertheless, OLP is a technological innovation that will help productions reach new levels of innovation with more possibilities and opportunities to explore.

Building intelligent infrastructure with digital twins has helped several companies to collect, extract, and analyze data. Digital twin technology or virtual twin is overgrowing with increasing accessibility and adaptability. As Industry 4.0 comes closer, technologies surrounding digital twins are also maturing and continue to develop. With the incorporation of technologies like the Internet of Things (IoT), data analysis, and Artificial Intelligence (AI), digital twins enhance R&D innovation with intelligent services like automation, self-monitoring, and real-time optimization. It enables rapid design & development and smart solutions in production, sales, logistics, and overall supply chain.

With the ability to enhance current manufacturing & product development, industries worldwide are incorporating digital twin technology. We can already see this accelerating adoption of digital twins across the industry. Although the global twin market was currently at 5.4 billion US Dollars in 2020, much of its slump is due to the worldwide pandemic. In addition, several industries shut down due to lockdowns and social distancing being the new norm during 2020 because of COVID-19. Nevertheless, the digital twin market is slowly rising again, with a tremendous rise expected after 2021. As a result, the global digital twin market will likely reach 63 billion US Dollars by 2027 due to a high growth rate of 42.7% annually.

What is Digital Twin?

While the idea of building intelligent infrastructure with digital twins is not entirely a new concept, due to its current exponential rise and growth, digital twins are undoubtedly growing more and more prominent. Along with the advancement in IT and digital technology infrastructure, digital twins are also evolving rapidly. In general, the concept of digital twinning represents a physical object or environment in a digital form that possesses its accurate characteristics and behavior. While 3D models and simulations also can describe an object or environment, twins systems do more than that.

A digital twin generally represents a physical object or environment not just in a static manner but in a dynamic form. A digital twin represents every phase of the lifecycle of a physical object or environment. A digital twin represents a physical object or environment from its design phase to manufacturing and maintenance and changes due to re-resign, iteration, and refining the object.

Hence, a digital twin is less of a 3D model rather more like an information model. Unlike traditional 3D models, building intelligent infrastructure with digital twins needs a more dynamic and adaptive approach. They can evolve and change over time concerning changes and enhancement in information and data. Digital twins can communicate, update and even learn similarly to their physical counterparts through data exchange with Artificial Intelligence at its core.

Artificial Intelligence with technologies like Machine Learning and Deep Learning enables a digital twin to behave as accurately as possible in contrast with its physical counterpart. Due to this dynamic nature of digital twins, they are in use to explore solutions, detect and prevent problems even before they happen and essentially plan for the future. Armed with these intelligent and smart solutions, companies and organizations worldwide rapidly adopt these technologies in their operations and global supply chain.

Building Intelligent Infrastructure with Digital Twins

Digital twins have five levels of sophistication. Ranging from a level 1 twin that can describe and visualize the product to a level 5 twin model that can operate autonomously, different levels of digital twin require different levels of infrastructure. For instance, a level 1 twin does not require advanced Artificial Intelligence or Machine Learning systems, but a level 5 twin does need them. Level 2 digital twin is an informative twin that needs to incorporate additional operational and sensory data. Furthermore, level 3 is a predictive twin that can use these different data to infer and make predictions. On the other hand, the Level 4 digital twin is a comprehensive twin that can consider and simulate future scenarios to predict and learn from them.

Building digital twin technology includes converging technologies like IoT, data analysis, design & development of the twin either in 2D or 3D, and incorporating AI and technologies like machine learning and deep learning. The digital twin infrastructure is not only in a digital form but also in physical form. This is because a digital twin simulation model resides in a digital format and connects the physical world alongside it. This connection is the representation of both digital models and physical models such that they represent and replicate each other. Every change in the digital or physical model must be synchronized, and both should also respond to each other’s differences.

The actual connection is made through digital models. We can link the physical world with the virtual world by twins modeling and simulating the physical world to map and represent it in digital form. On the other hand, we can connect the virtual world with the physical one by replicating any changes and updates made in the virtual world in the physical world itself. It will ensure that neither the digital form nor the physical form is not synchronized.

In digital twin technology, synchronization must be in real-time when building intelligent infrastructure with digital twins. Real-time synchronization and simulation of the product is the following infrastructure for digital twins. Whenever a product is in the developmental phase of production, the status of the digital twin must also reflect that. The changes occurring in the digital twin must also be replicated in the physical product. Therefore, the changes in materials, processes, environmental, and every other change must be synchronized across physical and digital forms.

Apart from this, the digital twin infrastructure also requires data analysis for deep learning and intelligent systems. Artificial Intelligence generally powers these intelligent systems along with Machine Learning and Deep Learning capabilities. This is necessary for smart analytics and prediction. ML and deep learning systems must be capable of analyzing substantial amounts of data. This data must be representing the actual physical product in real-world environments. Such data are generated and collected by sensors placed in the physical world and physical development.

The data collection is a crucial metric for a system to detect anomalies or errors through analysis in the digital twins platform. Usually, ML systems process these data types and perform pattern recognition to make predictions or suggestions. Thus, these systems enable self-monitoring, predictive maintenance and diagnosis, alert systems for possible future errors, and detection of abnormalities or inconsistencies in the product.

Due to this, the data must be accurate and representative of the actual physical product and environment with great precision. These types of data also are helpful for the corporations or organizations for their product analysis and study.

These infrastructures together enable all the digital twin advantages. The convergence of these technologies is a complex task. Nevertheless, the resultant solution offers an intelligent system that can track past system analytics to predict future solutions and real-time product optimization. Companies are rapidly advancing towards implementing digital twin technologies in their platforms and systems to leverage such benefits.

Building the Infrastructures

Building digital twin infrastructures is a very complicated and complex process. Since digital twins incorporate various technologies together, it is tough to integrate these technologies to work together flawlessly. Only with such integration can one enable proper digital twin technology and can leverage its benefits.

Since the technologies part of the model twins infrastructures are different, companies must be willing to take on R&D for every technology when building intelligent infrastructure with digital twins. Moreover, if not for flawless integration, the technologies must at least be working together, which is a challenging task. However, technology is rapidly growing, and so is its accessibility and ease of use. Hence, integrating these technologies is increasingly easier to enable the tech stack for digital twins.

With the power of the cloud, technology today is dependent mainly upon real-time computing. With the help of the cloud, companies can leverage virtually endless amounts of computing to enable various services, including digital twins. Furthermore, cloud computing allows companies to build intelligent systems that are ideal for integrating multiple infrastructures of the digital twin technology.

One of the most prevalent uses of cloud computing is Artificial Intelligence. Due to the nature of Machine Learning and deep learning, immense computing power is necessary to develop these systems. Cloud computing shines brightly in this field due to its vast pre-built infrastructure and network of computer systems. In cloud computing, these computer systems are connected through an extensive network of servers and processing systems. Cloud computing service providers serve this network of different systems as a single system with enormous computing power.

Alongside this, a system for efficient and accurate modeling of the physical world with high-performance systems for real-time optimization and synchronization is mainly necessary. Moreover, deep learning and data analytics with intelligent AI systems to enable smart solutions with automation at its core is also imperative. Furthermore, a unified system integrating all these technologies is crucial while building an infrastructure for digital twins.

Companies like FS Studio pioneer product innovation and transformative R&D technology through already established and proven digital infrastructure. Since deploying and building intelligent infrastructure with digital twins is very complex and challenging for companies and organizations, FS Studio provides innovative and smart solutions for these problems. Consequently, companies can focus on their primary product innovation rather than shifting their resources towards building a digital infrastructure.

Computer Simulation of Human Robots Collaboration in the industries is closer than we think. The current industry is moving towards the Fourth Industrial Revolution (FIR). FIR or Industry 4.0 is the digital transformation of the existing industries to enable new ways of manufacturing & production with automation at its core. The digital world will effectively meet the real world at this stage, integrating them on a level never seen before. Human Robots collaboration is one of the significant parts of this integration. With transformative technologies like computer simulations, AR, VR, and digital twins, cooperation among humans and robots is an absolute path that the next generation of technology will take.

Computer simulation is a very crucial tool for industries like robotic research and engineering. With the increasing adoption of computer simulation in various industries, simulations are rapidly becoming a vital part of product innovation and R&D technology. It is especially true for the robotic industry since collaboration between humans and robots is an essential part of the human robot paradigm.

Where Does Computer Simulation Come into Play?

Some factors influence the possibility for robots and humans to work together and collaborate efficiently. One of the top priorities or factors that affect this collaboration is human safety. During the operation, development, or testing of this concept of computer simulation of human robots collaboration, human safety is a top priority and should never be compromised. For this, various safeguards or failsafe mechanisms, power limiting restrictions, tools to monitor for possible errors, and proper fallback plans can be helpful.

Alongside this, robots that are in use must be aware of their surroundings and environment. At the very least, the use case of the robot must reflect its awareness and capabilities. Furthermore, robots also must control and change their actions as per real-time feedback and happenings in their surroundings. Thus, it presents the robot research and development industry with another challenge of autonomy and the ability of robots to perceive their surroundings or environments efficiently.

Conversely, bidirectional communication among robots and humans may open the door to fulfilling all the requirements necessary for a safe and effective human robot collaboration. But achieving such a feat is also not possible without proper testing and massive investments of time, resources, and money.

Computer Simulations can solve all these problems and complexities with efficient and elegant solutions. Computer simulation technology provides a modeling system to visualize any complex system, even 3D digital space. For example, a robot consists of joints, motors, arms, actuators, sensors, links, controllers, and other mechanical and electronic components like a battery, processing unit, and networking interfaces. All these components and elements can be costly when they reach the level of sophistication a robot requires. Alongside this, integrating these components into a complete robotic system in which these components work together efficiently as a whole system is also a very complex and expensive task to accomplish. Nevertheless, this is where computer simulations come into play.

The advancement in computer simulation technology now allows for the simulation of all these components and elements in a fully functional robot. Alongside this, computer simulation software can also simulate various environments and conditions under which a robot may operate. Much like a natural environment, a simulation environment allows for multiple experiments, tests, and evaluation of a robot, except it, is without all the costs and risks present when testing the robot in the real world. Computer simulations also enable monitoring and assessing robots with a very high level of sophistication in virtually any environment or condition possible.

Why is Computer Simulation of Human Robots Collaboration Important?

The human robot collaboration is essential for the factories of the future and all the possibilities that follow. In a space where robots and humans can work together efficiently to complete different tasks, endless opportunities emerge. For example, robots allow us to perform precarious and dangerous jobs that require massive strength or skill, along with repetitive or requiring extra precision. Meanwhile, some jobs require human intervention due to either being too expensive or complex to automate and jobs that require critical thinking and human intelligence. Thus, it constructively allows industries to utilize the best of both worlds efficiently.

For instance, risky jobs like mining, exploration of unknown borders and areas, repetitive assignments, lifting heavy loads, etc., have more practical industry use cases for robot in the field, but they also require human intervention. Similarly, jobs that require extra precision, like in surgery, may be more suited for robots. Still, due to a lack of intelligence and critical thinking, it is currently unable to do so. Likewise, human intervention is essential in search and rescue operations, but it also requires scanning large and potentially unsafe environments that are more suited for robots or drones. Alongside this, all factories and manufacturing industries cannot generally use robots due to either being too expensive to automate the job or too complex for robots to perform. Hence, human resources are used in various factories and manufacturing sites, albeit the factory and manufacturing sites are dangerous and unsafe.

These difficulties are easily removable if computer simulation of human robots collaboration becomes very efficient and easy to realize. Moreover, if such cooperation becomes possible to achieve, one can reap potential benefits from both worlds. For instance, robot developers in health care organizations can utilize the precision of a robot and the critical thinking of a surgeon to develop a surgical robot to perform complex surgeries on patients.

Consequently, a collaboration between humans and robots that enables an open environment where humans and robots can work together to complete works with integration of benefits from both worlds is a very lucrative goal to achieve. Computer simulation opens the door to such a goal. Due to the numerous advantages computer simulations possess, various industries develop human robot collaboration systems.

Generally, robot development in computer simulation software starts with designing and prototyping the robot. It requires a massive amount of resources, cost, time, and multidisciplinary skills in the real world. Then, each prototype comes to its testing, assessment, and redesign of the system according to the evaluations and results. It also requires equally if not more massive amounts of resources, cost, time, and skills in the real world. For a complete robot consisting of all its features and functionalities and compliance with all the factors discussed above, this process of prototyping, redesign, and testing has to be repeated numerous times until the evaluation and results are entirely within acceptable terms.

However, with the help of computer simulations, all these processes become redundant. When robot development with computer simulations occurs, developers/manufacturers get a digital platform to perform rapid prototyping with testing, modeling, redesigning, and programming all within the simulation. With the help of the computer simulation, developers can design a robot with all the parts and components right from the start to get a robot model. This model can go through various experiments, evaluations, and assessments to ensure formal requirements compliance. If not, developers can make changes or even redesign the robot entirely without much effort since it's in a digital form.

Not only this enables rapid prototyping and development, it ensures that developers do not exhaust all their time worrying about resources or costs but utilize that time for better ideas and models. It also opens the door for creative minds to flourish and experiment with various designs and configurations of robots. Furthermore, since the initial design process starts with a digital model, developers can tweak, organize and play with different formats. Finally, it will ensure that the design phase outputs the team's accurate designs with an efficient and agile developmental process.

Moreover, testing and evaluation of robots in different environments is also possible with error reporting and monitoring systems working together to gather essential data. It ensures that all unexpected problems or errors that the developers may encounter during the physical build of the robot are taken care of and solved. Testing with trajectory planning, verifying algorithm operation and efficiency, verifying the integrity of the design, and overall working of the robot can all be done in simulations. Testing various fluid mechanisms, aerodynamics, mechanical integrity, and kinetic forces with realistic physics engines is also possible.

One of the most vital computer simulation of human robots collaboration is human safety. Simulations enable testing for human safety and protection in numerous conditions and environments. We can quickly test and examine communications, control, and safety mechanics inside computer simulations without ever having to put a human at risk. With technologies like Augmented Reality (AR), Virtual Reality (VR), and intelligent AI systems, humans can test these robots with immersive experiences in realistic environments without taking risks.

It will rapidly evolve the development of human robot collaboration with the power of rapid prototyping, innovative product development systems, and efficient R&D technology. Furthermore, with Industry 4.0 gradually moving from embedded systems towards the digital transformation of the industries, simulations can open the door to new ways of development and enhance the much sought-perfect cyber-physical system (CPS).

With the advent of computer simulations, robot development and research is moving away from machines with no or low-level intelligence towards a more autonomous, adaptable, flexible, and re-configurable system that can work efficiently with humans. With computer simulations, human collaboration with intelligent robots will be possible across various industries where the whole collaborative system will be efficient, sustainable, effective, and safe. And our approach of creating the computer simulation of human robots collaboration will be completed.

Challenges of creating digital twins are increasing exponentially, especially with the advancement of technologies like simulation, modeling, and data analysis, digital twins of objects and environments are increasingly becoming more accessible and adaptable across various industries. Furthermore, with the integration of Artificial Intelligence with Machine Learning & Deep Learning, digital twins will transform industries across different spectrums, including the manufacturing industry.

The Fourth Industrial Revolution, or FIR or Industry 4.0 in short, is the automation of traditional manufacturing, production & other related industries with the digital transformation of traditional practices through modern technologies. Thus, industry 4.0 will be the age of digital technologies. Machine to Machine communication (M2M) and the Internet of Things (IoT) will work together to enable automation, self-monitoring, real-time optimization, and the production industry’s revolution.

Digital twins will be at the forefront of Industry 4.0. With its power of rapid designing & development, iteration & optimization in almost every engineering process & practice, digital twins will enable new opportunities and possibilities. In addition, digital twins will transform various manufacturing & production processes, drastically reduce time & costs, optimize maintenance and reduce downtime.

While digital twin technology is not entirely new, its growth and adoption are skyrocketing across various industries in recent years, while the challenges of creating digital twins are also rising. As a result, the valuation of the global digital twin market was sitting at 5.4 billion US Dollars in 2020. Furthermore, although its market was experiencing a slump in 2020 due to the COVID-19 pandemic, it will undoubtedly recover and experience exponential growth again. Consequently, researchers expect that the global digital twin market will reach 63 billion US Dollars by 2027 while rising at the growth rate of 42.7% annually.

Over the last decade, the evolution of the manufacturing and production industry has been mainly focusing on reducing costs, increasing quality, becoming flexible, and reaching customer needs across the supply chain. The manufacturing industry is adopting different modern technologies to achieve these goals. Millennium digital technologies have also been part of this technology stack due to the innovation and opportunities it brings to the table.

Different companies and organizations are using twin tech accordingly in different scales and nature. Due to this, the technology in use varies across the industry, such that some industries use the latest bleeding-edge systems while others use legacy and proven techniques. Companies generally use the latest tech when it becomes available to use the latest features and functionalities. On the other hand, proven legacy systems are in use due to their stability and ease of use.

Likewise, different uses of twinning sims in various industries possess other challenges. Apart from this, integration technologies like the Internet of Things (IoT), cloud, big data, and different approaches to digital twin integration will only increase the challenges for digital twins in terms of the sheer complexity of implementation. However, this also presents an enormous opportunity for industries to adopt and align these technologies to suit different needs to solve these complexities and challenges. Subsequently, companies like FS Studio solve the challenges of creating digital twins, providing a platform for the manufacturers or companies to work on without dealing with complexities.

Generally, the goal of any twin manufacturing is to create a twin or model of a real-world object in digital form. Furthermore, the aim is to make indistinguishable virtual digital twins from the actual physical object. Therefore, from the perspective of a manufacturer or a product development company, a digital twin technology will create an actual physical product experience in digital form. Hence, a digital twin for a product, object, or environment will consistently provide information and expertise throughout the whole product cycle.

A virtual twin can also serve companies for feedback collection alignment, useful for the product or the design team. Results from various tests may provide results that can be useful too. The design/engineering/manufacturing team can compile this information, feedback, and results for multiple purposes from the digital twin model. Furthermore, this compilation can also provide additional insights into the product, which can be very useful to tweak, change or even redesign the product entirely. This digital approach will consume much fewer resources, effort, and costs than the traditional physical approach. Moreover, these changes will also be reflected on the twin's systems instantly as the teams make these changes. This will ultimately allow crews to perform true real-time optimization of a product or a manufacturing process.

It will drastically improve the efficiency of designing and developing a product or a process. In addition, digital twins also enable higher flexibility across the overall design and development process. Furthermore, this flexibility comes at a lower cost and additional agility in manufacturing or product development. Hence, digital twin technology becomes very appealing for manufacturers and product developers due to these advantages and benefits.

One of the main challenges of creating digital twins remains to be the convergence of existing data, processes, and products in the digital form to be easily accessible and usable for the current or future teams in involvement. Moreover, such convergence may also change a company’s complete organizational structure from their R&D technology and product innovation to sales and promotion. Furthermore, incorporating technologies like IoT, the actual development of 2D or 3D models & simulations, and data analysis for consistent process, quality & authentic experience of the product remains a very complex process.

Apart from this, the actual use of digital twins created is also another challenge. The infrastructure and platform needed to use such digital twins are also essential, albeit complex, things to build. For example, suppose a team can create a car’s digital twin for a car manufacturer company. But problems with digital twins are that there is no actual use of the digital twin except for visualizing the vehicle. Even for proper visualization of the car across teams, different platforms and tools are necessary to often serve niche use cases of the company.

For instance, a car company needs a motor, brake, acceleration, air dynamics, and other niche simulations for the digital twin of their car. The technology stack should be able to perform various maneuvers a vehicle performs on the road. Aerodynamics and gravity simulation is a massive deal for car manufacturers. Integrating these simulations is also a monumental task.

Along with this, for the actual process of testing and developing products, the platform has to simulate various objects, environments, and conditions necessary for such functions. Alongside this, the platform should also be able to report errors & statistical data on simulations running while constantly monitoring and diagnosing the product during its testing or development. Collaboration between team members on the platform is also necessary for a large-scale company. Integration of Artificial Intelligence and technologies like Machine Learning and Deep Learning is also a very challenging task to accomplish.

Digital twin technology is also often associating itself with complementary technologies like Virtual Reality (VR) and Augmented Reality (AR). The use of VR and AR in a digital twin platform will upgrade the realism and accuracy of the product experience. With realistic simulations and modeling in VR and AR’s capability to enhance a product experience, the 4.0 industry will incorporate these technologies at the forefront with digital twin technology, increasing the challenges of creating digital twins. Alongside this, integrating the digital twin with the actual physical manufacturing process is also a huge challenge.

Although companies will have to adopt this new industrial revolution 4.0 with digital twin-driven smart manufacturing, the overall process will not be that complex. The hard part is the convergence of different technologies to enable a platform for generating this digital twin and integrating it with the actual physical process in product development or manufacturing. However, since the digital twin simulation accurately represents the actual physical product, the product/manufacturing team will have almost no difficulty incorporating this digital twin tech in their physical process.

Therefore, companies like FS Studio help product developers and manufacturers to focus only on product development and design rather than the process of adoption of the digital twin. While different industries are transitioning towards Industry 4.0 technologies, various platforms and solutions establish themselves as leaders in cutting-edge technologies like the digital twin model with AR VR to eliminate the complexities present while the transition happens. It will help the companies and organizations focus on their primary and core goals instead of shifting their resources and concentrate on their growth to the next industrial revolution.

Realization of challenges for the convergence of technologies like IoT, design, and generation of 2D or 3D models & simulation and analysis of existing data remains. With this, the incorporation of Artificial Intelligence, Machine Learning, and data analysis also pose challenges regarding automation, self-monitoring, and real-time optimization. Subsequently, corporations and manufacturers moving towards Industry 4.0 must place digital twin technology at its core.

It will help companies and organizations transition smoothly towards the industry 4.0 revolution, which incorporates product development and digital transformation. With the power of rapid design and development, new production and R&D innovation will take over the industry, reducing the challenges of creating digital twins in the transition to industry 4.0. Subsequently, with digital twin technology, industries across the spectrum will be growing exponentially in their move towards the next industrial revolution.

IoT and Digital Twins can reduce the costs in the manufacturing industry, minimizing unexpected downtime. These emerging technologies also help to perform complex simulations, offer deep insights and suggest equipment improvement. IoT technology also safeguards the interest of the manufacturer adding speed and flexibility in every situation.

What is a Digital Twin in simple words? Or, for that matter, IoT?

Digital Twin is the virtual twin or copy of the actual product. The digital twin connects the physical and digital worlds.

On the other hand, IoT, or the Internet of Things, is a physical "things" network. IoT platform is the medium for connecting and exchanging data between material objects. Generally speaking, we embed the sensors and software into physical objects over the internet.

As we live during the industrial revolution 4.0 (Industrie 4.0), manufacturers and industries embrace emerging tech to automate traditional systems. They are using emerging technology like AI, Robotics simulation, Biometrics to speed up the industry systems.

Emerging tech like IoT and Digital Twins are also reducing costs in astonishing ways.

IoT & Digital Twins Case Studies:

The evolution of IoT has made data transfer hassle-free by connecting sensors to the cloud and other "things." Apart from this, IoT is also serving as an effective tool for predictive maintenance.

Conversely, Digital twins leverage IoT to aid organizations in monitoring assets or processes virtually. Unfortunately, these are assets that are hard to check due to their distant location or a hazardous environment.

IoT and Digital Twins have unimaginable use in reality. For instance, power grids breakdowns create hindrance in every life, causing delays in businesses and services.

We can now tackle unwanted interruptions in power distribution thanks to IoT predictive maintenance.

Finland's electrical substation is the exemplary model of the predictive maintenance case study. In 2018, the electrical sub-station used Haltian's Thingsee wireless sensors for the first time. But, unfortunately, these sensors require manual checks from the human side.

The electrical sub-station used the sensors to collect temperature components, including humidity, air pressure, and distance.

This IoT-based predictive maintenance helped to increase efficiency in the electrical sub-stations while eliminating equipment failures. In addition, predictive maintenance helped to detect flopping assets and understand the factors leading to abnormal operations and disrupting schedule maintenance activities.

Finland's electrical sub-station isn't the only example of successful IoT in industrial applications.

Ericsson Panda manufacturing plant in China is another IoT case study we need to discuss.

The Ericsson Panda plant in Nanjing used Cellular IoT and connected 1000 devices to form a gigantic branch. In addition, the system had embedded IoT modules to send and receive data in real-time.

The IoT modules are said to transmit about 100 bytes of data per 8 hours from recent usage. Later, Ericsson Panda used the data in a cloud solution for analysis. The IoT solution costs just $20 per unit, will cut 50% maintenance work, saving USD 10,000 annually, and achieving breakeven for Ericsson Panda in 2 years.

The Ericsson Panda manufacturing plant is the first cellular IoT –based smart factory, and its immense success has contributed to the expansion of IoT worldwide.

Today, IoT technology has become a key element in the global supply chain already.

Since the beginnings of the industrial revolution, companies were eager to measure the temperature of the transported goods using the low-cost solution. IoT-based predictive maintenance and analysis applications in refrigeration systems help to understand when the system may fail. Therefore, it helped to avoid wastage of valuable agricultural goods and medicines and save money and time.

Similarly, companies have managed to keep the maintenance costs of factory equipment under control by 40%. IoT -based predictive maintenance has also helped to reduce equipment downtime by 50%. It reduced equipment capital investment by 3% to 5%. It saved the overall capital investment by 3% to 5% by extending the life of machinery.

Digital Twins can save money by predicting future failures. So, companies can repair defects at their earliest at a much lesser cost. It also recommends best strategies to improve the product development cycle, maximizing profitability. In this way, companies using Digital Twin can maintain a good relationship with their consumers.

As we can see, emerging technologies can help industries in the most remarkable ways. However, the expansion of Digital Twin and IoT isn't just limited to electrical sub-stations, supply chains, or manufacturing plants.

IoT and Digital Twin have expanded to other utility industries like healthcare, rail transportation, and oil and gas.

Oil and gas industries are adopting Digital Twins faster to minimize the costs of assets and productions. These industries have costly investments and handle them very carefully. Thus, it's no surprise that they aggressively adopt digital twins for modeling operations such as oil rigs, pipelines, and processing facilities.

Oil and gas companies have digitalized their systems to cut off weeks of unplanned downtime while reducing production costs. In addition, these industries have adopted predictive maintenance and IoT analytics to review historical data to detect failures in major components located at their offshore oil platform.

Digital Twins have transformed the transport industry as well. Today, the transport industry applies high-value rolling stock, such as locomotives, to maximize fuel efficiency and optimize maintenance.

The transport industry is willing to achieve the highest fuel efficiency possible to save hundreds of dollars to buy fuel. The rail transportation industry had reported saving about 10% on maintenance costs when they switched to condition-based preventive maintenance of rolling stock.

The digital twin is making remarkable contributions in the healthcare industry as well.

Q-Bios can be a great example to discuss. Q-Bios is the first clinical digital twin platform that harnessed the ability of digital twins to replicate anything indifferently.

Q Bios Gemini Digital Twin platform has built Mark-I, a computational biophysics model to scan the whole body. The company reported that Mark- I will examine the human body in 15 minutes and doesn't require radiation or breathe of the actual person.

Q Bios Gemini has claimed that Mark- I can work 10X better than the traditional MRI scanners for many critical diagnoses. In addition, Mark-I, the computational model, can eliminate bias or hallucination risk from AI and machine learning.

Another most significant advantage of the Mark-I is that it shields the patients from exposure to radiation, protecting them from running into the risks of developing cancer cells in the future.

Q Bios Gemini has received over $80 million from Andreessen Horowitz and Kaiser Foundation Hospitals to develop and expand its breakthrough whole-body scanning technology. In the future, the full-body scanning tech from Q Bios Gemini will provide data-driven and affordable care for all.

Medical and software companies are collaborating on digital twinning projects to create exact replicates of human body organs like the heart and the brain. The aim is to minimize risks in critical surgeries and aid organ donations.

Sim&Cure, a medical technology company, has built a digital twin called Sim&Size. This digital twin simulation will make brain surgery safer for Aneurysms patients as they will need less invasive surgery using catheters to install implants.

In another instance, Dassault Systèmes SE, a French software company, developed a Digital Twin heart using MRI images and ECG measurements. This digital twin model of the heart replicates the structure and some functions of the human heart. Now, heart surgeons can feed the patient data into the Digital Twin heart to determine whether the surgery will be successful.

Dassault Systèmes SE has launched the Living Heart Project in collaboration with academic and industrial members like Medtronic, Philips, and Boston. All the Living Heart Project members are working together to build safer and effective cardiac devices for patients.

Conclusion:

All the major industries are gaining massive value from IoT and Digital Twins. In other words, they are saving and making money simultaneously.

According to the predictions of McKinsey & Co, IoT technology would reach $11.1 trillion in economic impact by 2025. In addition, Cisco reported that data derived from IoT devices would surpass 800 Zettabytes by the end of 2021. There's no doubt that industries using IoT devices are experiencing explosive growth.

These industries are witnessing such massive growth because they managed to cut off shocking downtimes with Industry 4.0 technologies and build the ability to predict future failures and make necessary repairs using a digital twin.

Sadly, many companies have no idea about unplanned downtime's costs, root causes, and consequences. According to Service Max, 82% of companies reported that they had experienced unplanned downtime for three consecutive years. In addition, these companies experienced an average outage duration of 4hours every day with a median cost of $2 million.

Service Max also concluded that 70% of companies have no idea when their production machines will need maintenance or upgrades.

So, we can say that companies adopting IoT and digital twins are increasingly performing better than those avoiding emerging technologies. It happens because IoT and digital twins improved situational awareness and aided industry leaders in making faster business decisions.