Pedro Wightman, Lorena Garcia, Augusto Salazar, Fernando Landazury
©SHUTTERSTOCK.COM/BEEBRIGHT
Digital transformation has been a very popular topic in the last decade. Every major technology provider and consultancy firm worldwide has its definition for it; however, for many, it has become a buzzword that has been used and abused to sell every possible service or gadget, without helping companies build a clear path for successful adoption that will turn the new technology into an asset and not a dead weight.
When this process is taken seriously and with a real purpose, its impact on companies is real. If the results of this process can be translated into new products, services, or improvements on the business model that generate a tangible benefit to the company, it is called innovation (as defined by the OECD).
One of the technologies that is a star of the digital transformation process is extended reality (XR). This work presents a quick overview of the historical path that drove the birth and current state of XR, an exploration of some of its applications in industry, and an innovation process implemented by an important oil and gas company in Colombia, where XR is being adopted as a key technology for many areas.
Since the popularization of commercial computers in the 1970s and the PC in the 1980s, the world has seen a constant process of the adoption of technologies by companies to improve their internal operation; optimize resources; and expand communication capabilities within company departments as well as with clients, providers, government, etc. This is digital transformation at its best, even though it was not called that back then. The main difference between now and then is that, 40 years ago, it was just a desired advantage but today is an obligation. If a company has not adopted any of these technologies, it will most likely disappear in the very short term.
Of course, hardware development alone was not enough. The 2000s witnessed the birth of the modern digital ecosystem. First came appearance of the back-then mysterious Internet, which has progressed to the current monster that is constantly growing in terms of content, availability, and speed; the market of web-based applications; and the availability of flexible as-a-service models for infrastructure, software, back-end platforms, etc. Then, Web 2.0 empowered individuals to contribute and actively participate in the global network, and it opened the way for social networks and media streaming services, which still reign today. Third, smartphones brought computing and communication to people in a ubiquitous manner and started displacing PCs to provide an agile mobile environment full of applications that are accessible, low cost, and very easy to develop. Finally, the open source movement made many of these technologies affordable for small and medium-sized companies, which now could participate in this new fertile digital ecosystem despite their available resources and could now integrate new technologies into their daily core activities.
Another term that has been haunting every CEO for the last few years has been the Fourth Industrial Revolution, or Industry 4.0. This term refers to a large transformation that industries are experiencing today due to the appearance of radically new digital technologies. In case you are asking what the previous three were, here is a little reminder, as in Fig. 1. The first Industrial Revolution happened in the mid-1800s, when steam power was discovered and steam machinery was designed and used in industry for fabric production, locomotive transportation, mining, etc. The second revolution happened in the first decades of the 1900s, when electricity started to power machines, light bulbs, telegraphs, radio, and telephones, and concepts like serial and mass production were widely adopted. The third revolution took place in the 1960s with the appearance of affordable electronics, automated control, and robotics, which started mainly in the automotive industry but extended into all manufacturing sectors.
Fig 1 A brief description of the industrial revolutions.
The fourth revolution is happening right now, as we speak, and it is based on the digitization of processes and the integration of several technologies: the Internet of Things (IoT); blockchain; big data and data analytics; artificial intelligence; XR; additive manufacturing or 3D printing; robotics; cloud computing; and others transversal technologies like cybersecurity, system integration, etc.
This concept is closely related to digital transformation in relation to the deep integration of digital systems into the production, operation, and commercialization activities of a company. Many industry sectors are trying to adopt these ideas to improve their internal processes—for example, in agriculture (Liu et al., 2021; Raza et al., 2023), oil and gas (Elijah et al., 2021), construction, utilities, manufacturing (Xian et al., 2023), etc.
Everyone thinking about doing a digital transformation today is probably considering at least one of those technologies; however, to implement them, it is almost a given that the company must be at a certain level of maturity on its technology infrastructure. For example, a company must have at least one information system, like enterprise resource planning (ERP), a customer relationship manager (CRM), a business process model (BPM), or other similar platforms to support its operation. In addition, it is expected that the company should have some computing and networking infrastructure, either local or on the cloud, and some level of automation in its manufacturing or service processes, which could allow monitoring, planning, and management. If a company does not have any of these, or if its maturity level is too low, then some first steps must be taken before looking at adopting advanced technologies. In addition, factors like the perception of ease of use, impact, etc. can be critical to ensure the adoption of these technologies, as shown by Cordero et al. (2023).
One of the technologies that is part of the Industry 4.0 package is XR. This concept comprises three main technologies: virtual reality (VR), augmented reality (AR), and mixed reality (MR).
VR offers the user a completely synthetic digital world, which could be immersive, depending on the available technology for visualization, and where the user can navigate, can interact with, and must obey the rules of this environment. It usually requires a powerful computing device to generate a 3D world space and objects as well as all of the events generated by the interaction in real time. This technology was conceived for the first time in the 1960s by Ivan Sutherland with his famous Ultimate Display (or the Sword of Damocles), as seen in Fig. 2, but it had to wait until the 1980s to be made into a commercial technology by Jaron Lanier, founder of VPL, as in Fig. 3. However, due to the limitations of computing and visualization technologies and the costs associated, this initiative did not become fruitful. It was not until the mid-2010s when Oculus (now owned by Meta) developed the Oculus Rift head-mounted display and started a movement that resulted in the creation of a large diversity of hardware and software vendors and developers, who are now able to develop realistic virtual scenarios from their laptops. Now, many other companies, like Apple, are developing these devices. The main goal in the near future is to provide users with a full-dive VR experience, where users feel themselves inside the world. This idea may need the stimulation of all of the other senses beyond visual, including surround sound, haptic devices, controlled mobility, etc.
Fig 2 Ivan Sutherland wearing the Sword of Damocles. (Source: Sutherland, 1968; used with permission.)
Fig 3 Jaron Lanier wearing a VR display from VPL. (Source: Dadich, 2016; used with permission.)
AR is a slightly different concept, where digital elements are added to the user’s reality with the help of a digital device. The main difference from VR is that users are still aware of their environment but receive information that is beyond plain sight. For example, in a plant, a company employee, can see information about a machine once the device recognizes it, or a person on the street can see where the points of interest he or she is looking for are. Usually, AR requires a trigger to start the process of data acquisition, which can be a QR code or a program that can identify the element via a wireless marker, GPS location, or a video or picture or an action of the user (like starting a game, such as Pokemon Go). One of the first commercial devices for AR was Google Glass, which was a portable visualization interface and depended on a cellphone for computing and connectivity. However, with other projects, like Google Cardboard, it was shown that smartphones had everything not only for AR but also for immersive VR, thanks to the large processing power; quality of the current screens in terms of the resolution and refresh rate; and fast Internet connectivity, available both via Wi-Fi and 3G/4G/5G cellular networks.
Finally, MR is an evolution of AR in terms of the close relationship of digital objects with the real environment. The device maps the user’s actual space and uses it as the base for experience, making the digital elements aware of the real world around them. For example, a person is playing a virtual game in the living room of her or his house, and the characters of the game use the surfaces of the table, sofas, and other elements to hide, jump, or have any other interactions. This idea was one of the main foundations of the Microsoft HoloLens in 2016, as in Fig. 4, and other devices, like the Magic Leap.
Fig 4 A demo of the Microsoft HoloLens. (Source: Microsoft, 2023; used with permission.)
It is very important to note that, even though two of the most common areas of application for XR technologies have been in entertainment (video games, marketing, etc.), there is a large variety of options for applying all of these technologies in “serious” applications for industry. Most of the following cases were identified through exploration processes, based on existing solutions and the needs of the company, to find more critical, pertinent, and feasible approaches for their context.
At most companies, especially those that require employees to operate machinery or vehicles or to work in risky environments with high temperature, vibration, noise, or altitude, the employees need to be effectively trained to reduce potential hazards. Traditional training consists of a classroom-like environment, with slides and some multimedia material (videos, animation, etc.), guided by an individual experienced in the procedures. After a certain number of hours of theoretical training comes the in-the-field training, when the trainee has contact with the real work environment. However, depending on the elements, the trainees may have to wait for their turn to interact with a device, may not be able to make a mistake (or the plant will go boom!), and will have just a few chances to learn by doing.
Imagine another scenario. The employees arrive at a computer room, where, next to each computer there is a VR headset. Each person puts on the visor and is transported to a virtual representation of the field. Now, this can be done in two ways. First, a passive tour in a 3D video allows the employees to experience and familiarize themselves with the field securely, maybe even with some AR inside the VR environment, where each person can get more information. Then, after a few hours of a guided tour and single or multiple reproductions of the procedures on the video (which could be even seen at home, if possible), the trainees will be able to assess their learning curve by interacting in a synthetic computer-generated environment, which simulates the activity—operating a machine, executing a certain protocol, or driving a vehicle in a certain condition—to perform a task. This can be repeated as many times as necessary, and the computer could save each user’s performance, keep track of the areas that still need improvement, and even adapt the scenarios to increase the difficulty and allow working on the skills that need attention. After the trainees finish the virtual training, they can go into the real world with a more structured knowledge of the process. One example of this type of learning environment can be seen in Fuertes et al. (2021).
Some industries have been doing this for years; for example, aviation companies have enormous immersive physical simulators for pilots to train in conditions that are as similar to reality as possible, but they are limited to one student at a time, and the cost is incredibly high (Cross et al., 2022). XR allows most industries to create limited virtual environments for specific tasks that could be reproduced in several visors, making it cost-efficient due to scalability.
Once all operators have been trained and started doing what they are supposed to do, they can still need help. On the field, some processes may be that and require a precise order of execution. For example, in a certain process, valves 1 and 5 may look very similar, but they need to be opened at different times. To reduce the possibility of human errors, the operator can have an AR or MR device that shows the process, step by step; recognizes each of the components involved in the step; and may even verify in the system the successful execution of the task, as in Fig. 5. Also, the device can raise an alarm when there is an unexpected change in a certain variable and the process needs to be reversed, probably with the steps in a different order. Also, the device can allow the operator to communicate with other actors to report malfunctions or problems in the infrastructure that need to be taken care of to prevent future failures, or to consult and perform a real-time intervention in a piece of equipment to solve a critical problem before the maintenance team can arrive (Fidalgo et al., 2023).
Fig 5 An example of the AR version of a process description for operators.
When a company has a new project, like planning a new building or creating a new product, it requires the participation of a team of individuals, usually from different backgrounds, who need to collaborate in the design of that element. Traditionally, the participants must have a physical representation of the element being built, and every change will need to be implemented, which takes time. It could be a digital model on a CAD software platform, but it will depend on the perspective of the person with the mouse. Imagine that all of these people put on a visor, which could be VR or MR, and they start seeing the same model on the same table. They walk around, zoom in or out, expand the model, inspect each aspect, and then mention to everyone that they can go to that specific section or take control and share the view. Another person can propose a change, do it, and show it to everyone. Also, if a simulation engine is plugged into the system, it can evaluate the performance of the change in real time. Now, the advantage of these technologies is that the team does not even have to be in the same room; either a fully virtual room or an MR interface with digital 3D avatars that represent the other team members is also plausible to allow remote collaboration (Gong et al., 2021).
One application that is not usually considered a common scenario is the use of XR in management activities, but it is feasible. CEOs, VPs and those in other directing roles need to be able to access information fast and effectively, and most of the decisions need the participation of several units: engineering, finance, operations, etc. Similar to what happens in design teams, the management team members need to collaborate, looking at all of the different dimensions of a company. Spreadsheets, charts, and dashboards, despite the current efforts in user experience (UX) and interfaces, usually are flat and thought of as a 2D experience (Skowronek et al., 2022).
Imagine a group of high-level directors exploring a map of an existing plant; looking at a heatmap of maintenance costs in the infrastructure; inspecting the historical register of each machine on demand; and discussing the projection of future costs, or the possibility of updating, by contrasting the expenses with the current production levels and the expected income. Again, this experience can be done with each of them being seated in their office, their house, or even an airport if it is an urgent matter.
Companies, like any big system, resist change. It is a characteristic that comes from reaching stability and trying to protect it. Big changes usually imply a big risk for an organization. Not only XR but most of the technologies of Industry 4.0 require a change inside the company to not only know the potential of a technology but to recognize it in an almost intimate manner, appropriate the concept, and become an advocate for its application.
Employees in technical roles may know this, but, sometimes, they cannot transmit it clearly to the CEO, or one of the directors may see the potential of a technology but does not know where to start and cannot justify a large investment without even knowing if the company is ready to start that appropriation. On the other hand, many technology providers try to sell the “perfect” solution to which the company needs to adapt and that may not solve the actual needs of the organization; these are very likely to end up as “white elephants” that nobody uses because they solve no problem. This relationship between technology and administration processes and the definition of strategies have been addressed by Laubengaier et al. (2022).
A good innovation cycle can be key for successful digital transformation processes. Innovation can be defined as the process that takes research findings to final products that go into production and/or reach the market, positively impacting the company’s performance. While working with a big company that wanted to adopt XR, a simple innovation cycle called design, concept, prototype, and implementation (DCPI) was built by the team. It is composed of four moments that, based on experience, could work as a guide for a slow and steady innovation process. Fig. 6 presents the four steps. The times for each of the steps are rough estimates that depend on the complexity of the project but can illustrate the time proportions between the stages.
Fig 6 The definition of the design, concept, prototype, and implementation (DCPI) innovation cycle. UI: user interface; UX: user experience.
At this stage, the company is ready to explore the idea but has very few resources to risk and needs results fast. The main objective is to explore the company’s needs and current infrastructure as well as the state of the art in the desired technologies. Both elements are integrated into a single design, where the proposal is tailored to the needs, resources, and expectations of the company. Also, the result must show at least a low-resolution demo of the solution, something that will explore basic elements of user interface and UX that can inspire and make the directors imagine scenarios where the new technology can be applied.
For XR projects, you could implement an almost tutorial-based experience in a visor, which you could borrow from a university or a colleague, to let the decision makers feel the experience. Find videos on the Internet that illustrate your idea in a more direct manner and a good set of slides about the other technical content.
Finally, a route for the implementation of a proof of concept, in the short term, should be defined. This process could take between three and five months, depending on the complexity of the company, the technology, and the process being addressed.
Once a design is defined, the company will want to see something working, not only a wireframe model of how it is supposed to work. At this stage, it is critical to develop a demo with the available technology, even if not all functionalities are developed. The demo must illustrate the real challenges for future implementation: reduced computing capabilities, harsh policies for data and infrastructure protections, lack of training in personnel, internal protocols and standards, etc. as well as the feasibility of integrating several technologies into the company’s systems.
At this point, you should have included the company’s personnel, both from the infrastructure and potential users; found their requirements, their expectations, and their dreams; and tried to put them together. Your job is to find a good balance between what the bosses imagine and what the final user will feel is useful. The first will fund the project, and the other will use it and make it successful in their daily activities. Do not oversell or undersell the capabilities of the technology because the project could be crushed if high expectations were not met, but at the same time people should be inspired from the beginning to come to the table with curiosity and excitement.
The result of the proof of concept is a working piece of software plus hardware that proves that the main functionality can be done as well as a characterization of how a future version should be implemented, the problems that may appear, and how to solve them. It does not matter if this version is put together with duct tape and WD-40; the project can show that it works, despite its limitations. This is the message that the managers must receive so that the process continues. Now, if this version does not work, it confirms that the idea was not feasible due to the technological or the company’s capabilities; therefore, it needs to go back to the drawing board. This process could take anywhere from four to eight months.
If the proof of concept has shown the feasibility of implementation, is time to go back to the drawing board. At this stage, there should not be shortcuts of any kind, spaghetti code, shady variables, or showing wires. Pretty much everything from the proof of concept needs to be erased and redone well. Spend a good portion of the time on documentation and repeat all of the processes, one by one, based on the lessons learned from the proof of concept. Pay attention to details because, this time, the prototype should be tested in production. This does not mean that it is the final version that will be used by the company for the next 10 years, but it needs to iron out all of the pending issues from the proof of concept and will set the foundation for the final implementation of the solution. For XR projects, at this point of the process, the company must have its own gear and some people with at least partial dedication to the project.
Based on this solution, a thorough evaluation of the general performance of the solution must be done: technical indicators, UX, costs of implementation and usage, management resources, security issues, etc. The results of this evaluation will be presented to the top managers of the company and should summarize if the solution will, in fact, be an asset for the company, generating advantages or revenues, or if it is just a nice experiment that went well but will not benefit the company enough. This process could take anywhere from six to 12 months.
If everything went well with the prototype, the managers will be happy, inspired, and willing to invest in the full implementation of the new technology. All of the top and middle-management directors should know about the initiative and probably have ideas about how to integrate the technology with their areas. This is the moment of truth when the company will start experiencing the transformation. Most likely, it—especially if it is a big company—will look for large tech providers to implement the final version of the technology. Do not feel bad if that happens. You now know more than everyone about the way it should be implemented, the problems, and the potential. If this is the case, try to find a role as a company’s partner to guide and support the implementation as a consultant. Now, if you are in charge of the full implementation, build a good team, plan and prioritize the escalation of the prototype based on the requirements of all the other areas that are interested in adopting the technology, document carefully, and do the job. As in any project, prepare to keep connected to the project for a long time—updates, patches, maintenance, etc.—and, most importantly, define a route for the next projects (and repeat the cycle)!
Sometimes the innovation process is not as smooth as expected. Truthfulness in the process is key to recognizing when things are not going well and that a revision is necessary. If the problems are small enough, then just going back one or two stages may be all it takes to rethink and restart.
However, if a more serious situation is identified, like 1) a lack of technological maturity in the company; 2) a lack of interest from the customers in adopting the new technology; 3) a lack of trained personnel to implement, use, and maintain the solution; 4) low return on investment; 5) a foreseen technology that will make the current one obsolete in a matter of months or years; or 6) financial situations, both internal or external, then the process may need to be archived until the conditions are favorable for its implementation or just used for future consultation.
These decisions can be taken at any stage of the process, and, even if some investment, time, and other resources were invested already, it is always going to be cheaper to stop early than to implement a failed solution.
This innovation process has been used by the team for the last five years, and the following results can be enumerated:
Some of these projects have applied for and obtained external funding from government and international organizations, which can also be a great incentive to invest in applied research and innovation.
Not all companies are a good fit for all of these new technologies. A slow-paced process of discovering what the real problems are, how the technology could fit the problem, and if the company is ready and willing to invest in a deep transformation are questions that need to be answered before the big bill arrives to the CEO’s desk. Do your best to deeply learn the company’s problem before you propose a solution.
In terms of XR, it is very easy to think that it will be the solution to everything. Do not think that, in a few months, the company will be in the metaverse and that, just because of that, people will stream toward the technology and use it. One of the risks of XR is that it can be very gimmicky and attract attention rapidly, but, if it does not solve a real problem or makes a process more complicated by adding extra steps, requiring expensive equipment, time, and a heavy learning curve. In these cases, the solution will not stick. An unsuccessful experience may drive the company to stop believing in innovation in this area for a few years, so make sure that the job is systematic, disciplined, and well done.
Digital transformation is a way to implement new technologies to improve a company’s internal structure and processes, and it will continue to be something very critical in the foreseeable future, thanks to the accelerated rate of technological advances with the potential to offer new solutions to existing and future problems. All professionals in technology, engineering, science, math, and computer science should be capable of actively contributing to or leading this type of innovation process, given their intrinsic knowledge of the technical issues involved.
The fact that we are right in the middle of the Fourth Industrial Revolution is a unique opportunity to participate in defining the way companies will function from now on. What you will discover, design, and implement from these disruptive technologies can become the standard of tomorrow. XR technologies have the potential to change the way we interact with each other and with reality, from the metaverse to small, tailored training environments for companies, just as the Internet and smartphones have done. The digital ecosystem for XR is constantly growing, with new players coming every day, offering new tools to create better, faster, and cheaper solutions, and there is no way back. Do not be disappointed that the ideas of VR and the metaverse appear to be collapsing. Trends go over the hype by shedding all the bad ideas away so that the good ideas—like maybe yours—can be the ones that will be adopted, not too far in the future, to solve real problems. One of the next hot areas to work in is digital twins, which is very intertwined with XR, so try to get involved quickly.
The innovation process does not create new things for the sake of novelty, but it has an ingrained goal of putting those results to good use for the organization. This means that a successful process must answer an actual need, which sometimes is not too easy to identify. The DCPI innovation cycle can become a useful tool to plan the steps for a collaborative exercise with industry that can bring great results.
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Pedro Wightman (pedro.wightman@urosario.edu.co) earned his B.Sc. degree in systems engineering from the Universidad del Norte in 2004 and his doctorate degree in computer science and engineering from the University of South Florida in 2010. He is a principal professor at the School of Engineering, Science, and Technology of the Universidad del Rosario, Bogota 111711, Colombia. His research interests include location-based services, especially focused on location data privacy, blockchain, medical information systems, communication infrastructure for the IoT, and Industry 4.0. He is the author of three technical books and several publications in indexed journals and international events. He is a Senior Member of IEEE and senior researcher of the Ministry of Science.
Lorena Garcia (lgarciap9@ucentral.edu.co) earned her B.S. degree in electronics engineering from Universidad del Norte in 2006 and her M.Sc. degree in electronic and computer engineering from Universidad de los Andes in 2008. She has more than 16 years of experience in academic administration, teaching, and research in important institutions. Currently, she is an assistant professor at the School of Engineering and Basic Sciences of Universidad Central, Bogota 110311, Colombia. She is a Senior Member of IEEE and a member of the IEEE Educational Activities Board.
Augusto Salazar (augustosalazar@uninorte.edu.co) earned his B.S. degree in systems engineering from Universidad del Norte, Barranquilla, Colombia, in 2003 and his M.S. degree in computer science from National Chiao Tung University, Hsinchu, Taiwan, in 2012. He worked in the area of embedded systems for nine years at companies like Ericsson LMF (FI), Hitron Technologies (TW), and Proscend Communications (TW). Since 2012, he has been an assistant professor with the Department of Systems Engineering, Universidad del Norte, Barranquilla 081007, Colombia. His research interests include embedded systems, mobile application development, and game analytics.
Fernando Landazury (fernando.landazury@promigas.com) earned his B.S. degree in industrial engineering from the University of Atlantico in 2014 and his M.Sc. degree in industrial engineering from Universidad del Norte in 2017. He has worked in research and project management and as a professor in academia. Fernando is currently in charge of Innovation Promotions and Digital Solutions at Promigas S.A. E.S.P., Barranquilla 080002, Colombia, where he has led many technology innovation initiatives.
Digital Object Identifier 10.1109/MPOT.2023.3283107