Industry 5.0: Revolution or revision

Currently, the industrial society exists within the fourth industrial revolution, known as Industry 4.0. This period is defined by the use of Cyber-Physical Systems and Internet of Things technology. Industry 4.0 and industrial revolutions of the past have proven to be beneficial to the bevel gear industry. While Industry 4.0 is still relatively new, many technologists are beginning to speculate upon what is to come with the next industrial revolution, Industry 5.0, and how we may learn from the present. Industry 5.0 counters the current-state with mass personalization, an observation that the consumer values individuality and that the manufacturers must preserve the human-touch to provide it best. It also proposes the use of collaborative robots, known as cobots, that will work side-by-side with human workers. Cobots will serve to augment the human worker, increasing efficiency and capability. The bevel gear industry could benefit from Industry 5.0 as greatly as it has with the revolutions of the past. However, it must consider how it will adapt to the driving forces that work to change the course of the technological development of the past several decades and how it will adapt to the requirements for individuality that are predicted to come with Industry 5.0.

1 Introduction and revolutions past

Industrial production has been hallmarked using phase categorizations by technologists, sociologists, and historians since the first industrial revolution that occurred in the 19th century. Prior to this, people primarily lived in smaller, agrarian societies. The invention of steam power led people to rapidly urbanize and take on factory manufacturing positions, as it readily replaced human and animal powered work [1].

The second industrial revolution, sometimes known as the technological revolution, came about shortly after the first and is set apart by the introduction of electricity. The invention of the Bessemer process paired with ideas such as the assembly line concept and mass production allowed for an unprecedented rapid advancement of technology during the onset of this period [2]. Machines also began to be controlled by compressed air in addition to electric motors.

Manufacturing technology would not be significantly advanced until the third industrial revolution around the 1970s. The application of computer technology allowed for parts to be precisely made with a machine operated by a computer — instead of human — and was called computer numeric control (CNC). This gave way to new types of jobs for manufacturers, either programming processes for parts manufacturing or operating CNC machines. CNC technology was further enabled by computer-aided drafting (CAD) technology. Now designers could use CAD programs to quickly develop and revise complex part designs. The end result could be generated into a system of points, which is then fed into a CNC machine using G-Code. The CNC then follows the G-Code commands to produce the end product. CNC machines brought about the beginning of automation that defined the third industrial revolution. A chronology of the industrial revolutions can be seen in Figure 1.

1.1 Industrial Revolutions Past and The Bevel Gear Industry

Gear technology was not only a driving force of the early industrial revolutions, it was driven by them as well. While the involute profile had been recommended by Euler about a century prior to the first industrial revolution and advanced applications of gears existed — such as the famous Antikythera Mechanism — far prior as well, the need for precise gears was not commonplace until the proliferation of steam power. Factories had need of speed reductions from engines and for precise time-keeping. The first industrial revolution saw the invention of both a gear-hobbing machine that was capable of generating spur and helical gears by Herman Pfauter of the Pfauter company (currently Gleason-Pfauter) and the invention of the bevel gear planar by William Gleason of the Gleason Works [4]. This time period would also see the creation of several other large bevel-gear companies that exist presently such as Oerlikon-Buehrle (currently Oerlikon Geartec, owned by Klingelnberg), which created bevel gears through templates, and Klingelnberg Söhne, which drove many advancements in bevel-gear technology [4]. The inventions of all of these companies would prove invaluable to further enabling the first industrial revolution.

By the time the second industrial revolution came, the automobile industry was beginning to take off. The bevel-gear industry quickly rose to meet the power transmission demands that were becoming more common with the invention of the hypoid gear drive by Ernst Wildhaber of the Gleason Works. Klingelnberg developed the Palloid Method, which could be used for spiral bevel and hypoid gears around this time as well. Electricity allowed for smaller machines that could have a motor onboard across the whole gear-manufacturing industry. Increased need for gear technology during the second industrial revolution brought significant advancement to the gearing world.

The advent of computers with the third industrial revolution would also prove to be fortuitous to gear manufacturers. The design of gear train systems can be a complex task. As many in the gear industry were already experts on gear-train design, they naturally rose to create software that could design gears and powertrains. This was taken a step further in the creation of computerized gear-analysis methods such as tooth contact analysis developed by Theodore J. Krenzer of the Gleason Works, allowing for rapid, optimal design [5].

CNC bevel-gear generation machines came about during the late ’80s [6]. These early CNC machines removed the long setup time traditionally required for generating gear profiles. CNC gear generation also allowed for the manufacturer to use a single machine for both single indexing and continuous generation, which was entirely unprecedented. Precision was also increased due to repeatable computer accuracy. Additionally, new machines were brought about that changed the bevel-gear industry, such as the coordinate measurement machine (CMM). This machine allowed for precise measurements of complex surfaces, such as bevel gear teeth. In general, all of the technological advancements of the previous industrial revolutions allowed for the bevel-gear industry to rise in import and necessity.

2 Industry 4.0 – The present

Currently, many technologists believe us to be within the fourth industrial revolution, Industry 4.0. Industry 4.0 originated as a high-tech strategy that was announced at the Hannover Fair in order to promote computerization, efficiency gains through automation, and all-around technological advancement [7]. It was quickly adopted by industry leaders throughout the world. This revolution contains several key elements to promote manufacturing efficiency.

The first and foremost element is the widespread implementation of cyber-physical systems (CPS) within manufacturing. A CPS itself is vaguely defined and in general can be thought of as a system made of physical machines and computers that are capable of exchanging information and influencing each’s actions [8]. Examples of a CPS can be seen through something as small as a pacemaker to as large as a national power grid [9]. This is readily applied to the world of manufacturing, as computer-controlled devices had already started spreading throughout the industry since the previous industrial revolution [10]. Some examples of this technology applied to the world of manufacturing can be seen in Figure 2.

Another key strategy of Industry 4.0 is the inclusion of Internet of Things technology (IoT). In general, IoT can be thought of as a networked connection of objects [11]. As applied to the manufacturing industry, CNC machines, measurement tools, instrumentation, and robotic assembly lines could all be thought of as potential IoT devices. Though in practice, the widespread implementation of IoT on all of these devices can be problematic due to the incredible variety seen even across machines with the same function; the rewards of IoT have already been seen by original equipment manufacturers (OEMs) and small-medium enterprises (SMEs) [12]. The value of IoT is realized when it is paired with the concept of Big Data. Devices that can be considered for IoT typically consist of at least one CPS, if not more. The architecture of a CPS relies upon sensors to observe the physical world for providing the virtual system with feedback for control [13]. Collecting and compiling all of that data enables further benefits of Industry 4.0.

One of the primary benefits of the aforementioned strategies that can be realized is the application of predictive and prescriptive maintenance to manufacturing machines. SMEs are particularly sensitive to manufacturing downtime [9]. One such downtime that previously had been considered as unavoidable was downtime due to regular maintenance of machines. The alternative of a machine crashing or instrumentation failing can be far more expensive, but excessively maintaining machines can also lead to significant profit loss [13]. By feeding the data collected from a machine as it degrades into a statistical, predictive model, downtime for maintenance can be minimized since a machine will only be serviced as required [14, 15]. Artificial intelligence (AI) can also be applied to such a model and the worker then notified of how to best fix the machine [13]. A comparison and description of maintenance paradigms throughout all of the industrial periods can be seen in Figure 3.

Another benefit of the compilation and analysis of Big Data from factory IoT devices is the possibility for robotic process automation (RPA) and automated report generation. RPA is a technology that uses software scripting to mimic human interaction through various computer applications or computer-based processes [16]. Given the constant stream of data that comes from IoT devices, RPA is a natural choice for data handling. This can be readily applied to automate regular production rate analytics, providing supervisors with a method for quantitively monitoring efficiency [17]. This technology is further realized for OEMs since they often consider a “family of parts” where only several design parameters vary across parts that share a family. In this case, the manufacturer can go so far as to automate the process from part design, manufacturing methods creation, manufacturing, shipping, all the way to corrective measures from manufacturing data [18].

All of these facets of Industry 4.0 can be combined with other tenets of the strategy to form a goal of lights-out manufacturing. Lights-out manufacturing attempts to recreate an automatic factory, where products are handled from raw material to end-state entirely by unsupervised robots [19]. The idea of this came about from a fictional short story that described an automatic factory in the 1950s and resulted in a large industrial push throughout the late ’70s and ’80s [20]. While accomplishing this was only a dream throughout the third industrial revolution, it was brought into a reality with the technology from Industry 4.0. One well-known example can be seen through a Fanuc factory in Japan [21]. These factories can manufacture products 24 hours a day, seven days a week. Such a feat of automation can be seen as a factory that is one large CPS.

2.1 Industry 4.0 and the Bevel-Gear Industry

As with the industrial revolutions of the past, the present has proven to be fortuitous to the bevel-gear industry. Due to the high-tech nature of the parts being manufactured, the large number of sensors required for IoT and CPS technologies were already present on many modern machines. Additionally, many bevel-gear manufacturing machines also had on-board computers capable of more than just the interpolation methods required of typical CNC machines prior to Industry 4.0 [4]. Because of this, there have been several concepts of Industry 4.0 that have been uniquely extended in addition to the tenets of the revolution mentioned prior.

One concept of Industry 4.0 that has been easily advanced within the bevel-gear industry is that of the digital twin. A digital twin is a realistic model of the current state of a physical system that is used for autonomous decision making [22]. A key component of the digital twin in the manufacturing process is the state of the part being manufactured. Since the geometry of a gear is well defined throughout the manufacturing process, its theoretical state can be compared with the actual state at all points, providing an autonomous model the ability to adjust plans or maintain the original manufacturing method accordingly. Digital-twin models also aid in more precise noise and stress analysis, both of which have become a subject of particular interest to the automotive industry recently [23].

Some companies have taken the application of CPS, IoT, and digital twin technologies a step further in creating closed loop manufacturing (CLM) [24]. Spiral bevel and hypoid gears are known for complex geometries that are not easily generated.

The tooth profile of such a gear is cut in either a single-indexing or a continuous fashion, heat-treated, then either ground or lapped depending on the cutting method, and finally inspected. If necessary and possible, corrective manufacturing methods are applied. Gears that are ground have a superior degree of control and thus can have corrective methods applied. The Gleason Works and Zeiss introduced the first CLM model in 1985 [26]. Tooth surface data would be generated at the Gleason Works and sent to users. This ideal data would be compared with real measurement data using the Gleason Automated Gear Evaluation (G-AGE) software. At the time of initial release, corrections would still have to be manually input at the machine. The application of Industry 4.0 technologies allowed machines to communicate any necessary adjustments without human interference and bring a previously scrapped part into finished tolerances [26]. The G-AGE model of closed loop manufacturing can be seen in Figure 4.

Although upgrading to the newest, latest, and greatest technology may prove prohibitively expensive for many bevel-gear manufacturers, this is particularly true for SMEs who work on contracts often from the automotive and aerospace industry. As such, there has also been focus on adapting machines from the third industrial revolution to the capabilities of Industry 4.0 [27]. Retrofitting sensors is one of many ways being considered to modernize older factories and provide SMEs a method of adapting to the future without having to consider the large, initial investment of a new machine [3].

Many advancements have also been made with the introduction of manufacturing expert system software. Such software manages the design, cutting, heat treatment, finishing, and testing of bevel gears. The Gleason Works released the G-LAB manufacturing system in 1995 to do precisely that [26]. This system also featured several groundbreaking technologies such as the ability to predict warpage from heat treatment and correct for such deviations. This resulted in a reduction in grinding time and a decrease in part scrapping. The G-LAB system was released before the wide-spread proliferation of computer network technology in manufacturing facilities, though. Due to a lack of infrastructure, the G-LAB system was discontinued in 2005. The adoption of IOT, however, has made the necessary technology affordable and readily available for many OEMs and SMEs. Just recently, the new Gleason Expert Manufacturing system (GEMS) was released by the Gleason Works. This new software system combines gear design and optimization with network connections to manufacturing machines and CMMs and creates correction loops for an automated production.

Many modern manufacturing facilities have adopted to a cellular layout to promote lean manufacturing. In this layout, a facility consists of many “cells” that are specialized to accomplish a specific task. Bevel-gear manufacturing is particularly well suited to this, as cells can be specialized for pinion and gear operations, inspection, and finishing. Cellular facilities are also very well suited to automation and Kanban-style production boards. Adopting to these new manufacturing strategies has helped increase the productivity of facilities.

As can be seen, the bevel-gear industry has not only benefited from the technologies of Industry 4.0, it often drove them. Furthermore, with several advancements, the bevel-gear industry was years ahead of its time. Many exciting advancements are still being made today.

3 Industry 5.0: A response to Industry 4.0

Industry 4.0 provided manufacturers with a plan for further automation, digitization, and cost of service reduction. While many benefits have been already realized, some technologists have pointed out the drawbacks that are even now starting to become apparent. One of particular note is that, while Industry 4.0 is incredibly optimized to large-scale mass production, it is not well-suited to the issue of customized products and low-run manufacturing [28]. Another concern with Industry 4.0 is that the ethical and social ramifications of such a large-scale automation are not often considered [29, 30]. Several technologists have also been quick to point out that complete automation does not necessarily entail maximum efficiency and introduces a new means of critical failure for a factory [1, 31].

Industry 5.0 was first introduced as a conceptual counter to all of these downsides via a LinkedIn article written by Michael Rada [32]. This article pointed out that the capability of total automation presented by Industry 4.0 must be controlled, otherwise the technology will eventually only serve a select few instead of advancing all of humanity. While still in its infancy, Industry 5.0 already has several different aspects and serves to provide a plan for the further advancement of technology that does not leave humans behind.

As briefly mentioned earlier, mass production often prohibits low-run and customized products since it is best suited to producing many similar parts. Industry 5.0 counters this concept by introducing the critical idea of mass personalization [33]. While it is certainly not the case with every product that a consumer will buy, mass personalization asserts that customers are concerned with standing out and are willing to be more involved in the manufacturing process for that uniqueness.

Furthermore, according to consumer involvement theory, involvement in the development process can add value beyond the specialized end product [34]. Mass customization also addresses low-run products since it is expected that all things produced will vary to an extent. SMEs are particularly well suited to adopt to this principle since full-scale automation is often infeasible to them due to the variety of parts typically produced. Several OEMs have adopted this principle already through things such as color personalization and laser engravement [33].

Despite this observation, regressing to a non-automated manufacturing state makes little sense to both OEMs and SMEs, as doing so would discard the work of over a full century of advancement. One common recommendation for allowing customization while maintaining some automation is introducing collaborative robots (cobots) into factories [35]. The idea behind this is that the feasibility of robots performing all tasks within a factory is typically low for all but a few manufacturers. Any sort of customization practically prohibits it. What is far more feasible, though, is that a robot could work in sync with a human. Typically, consumers do not mind if some sort of automation technology was used during the manufacturing process, so long as the end product is personalized [33-36]. Because of this, cobots are particularly ideal for use throughout the manufacturing industry because they can fulfill the underlying consistency requirements, prevent workers from having to engage in dangerous tasks, generate accurate process quality data, have a relatively uniform cost throughout the world, and free up workers to focus on final customization [36].

One of the more understudied facets of Industry 4.0 is how it can be ethically implemented [32, 34]. Additionally, there are concerns on an overly-pervasive IoT and AI technological world. Some argue it could easily degrade the human workforce or it could develop into an authoritarian or oligarchical power structure [31, 37]. While it may not be the intention, automation is at the crux of many aspects of Industry 4.0. Automation itself is far from the vague definition of bad when used appropriately. In fact, automation could provide partial relief to the anticipated skills gap concern within the manufacturing industry [35]. But, when taken to extremes, such as the case of automatic factories, one must consider ethical implications. Profit margins for a company may be increased, but a large number of workers – humans – are eliminated from the equation. While this is a rare, hyperbolized case, it can be used to extrapolate the importance of ethical considerations within the framework of automation. Many within the technological world have already begun to note the need for some sort of guidance at this pivotal point in advancement [38].

Industry 5.0 seeks to solve this by stressing the importance of a human touch for mass personalization and using cobots instead of full-automation. Using technology in this way is more in line with the intention of an invention, something that is meant to serve people. For this reason, Industry 5.0 is sometimes being preemptively referred to as the Age of Augmentation [30]. Currently, AI models used for automated robotic operations must be trained on how to perform every aspect of a complex task and how to mitigate unanticipated problems — something that a statistical model is poorly equipped to do. Instead, the cobot’s AI model could be trained to anticipate the human worker’s next action, which is far more feasible for the general factory setting [29]. In this way, robotic technology exists to increase human productivity, not replace it. As Industry 5.0 is still in its very early stages of development, there is still plenty of room for improvement on this plan, though. In fact, an online survey of 150 employees in Romania found there was a notable amount of trepidation in accepting cobots into the workplace [39]. Some of the results from such a survey can be seen in Figure 5. As the sample is limited to one specific region of the world, though, it would be prudent to conduct a similar survey throughout the rest of the world. The employees of manufacturing facilities are some of the most critical stakeholders in technological advancement; their perspectives cannot be overlooked.

Another critical point of Industry 5.0 is the observation that the pursuit of maximum profits does not necessarily result in maximum manufacturing efficiency, which can be valued higher by the customer [29, 34]. Despite significant advancements with robotic technology, artificial intelligence, and deep learning within the last two decades, these technologies are often not as well-suited to complex tasks as a skilled worker would be, particularly in a dynamic, poorly predictable environment. So, while a robot may perform a task cheaply, increasing the profits, it can take more time and have a higher capacity for failure. Ultimately, the goal for a production facility should be to make a product as efficiently as possible. Chasing profits may result in gains for executives, but it misses the true object of satisfying a customer’s needs. Industry 5.0 attempts to revise this by using robotic, AI, and deep learning technologies more appropriately.

Relying so heavily upon automated technology also introduces a new critical failure point for a production facility. Since autonomous systems rely on internet technologies to communicate and perform tasks, they are reliant upon networking systems to manufacture a product. Similar to a factory’s reliance upon electricity, a factory must now rely upon another external provider and expect possible network failures. Another point of failure for an internet system is introduced in this case, though, when considering the possibility that a computer network can be hacked [40]. Data breaches, ransomware, and cyber-attacks have already been seen in several, vital industrial facilities despite how new Industry 4.0 is [41]. Such a failure could easily cripple a largely automated factory. Because of this, the importance of cybersecurity has grown significantly with the implementation of Industry 4.0. This would be far from rendered irrelevant under the current paradigm of Industry 5.0. However, the prevalence of human workers provides damage mitigation in the event of a cyberattack or network failure. The temporary loss of cobots and internet-based communications systems may hinder facility productivity, but productivity will not come to a complete standstill because the workers can still operate without internet technology.

Industry 5.0 is still in its very early phases of development and has only recently started to gain note within the technological society. That said, it attempts to solve some of the problems already being noticed within Industry 4.0 with several novel ideas.

3.1 Industry 5.0 and Predictions for the Bevel-Gear Industry

As with the industrial revolutions of the past and present, Industry 5.0 has the opportunity to be a great boon for the bevel-gear industry. However, as the concept of the next industrial revolution is still developing, the means of advancement is not yet clear cut. The foundational aspect of Industry 5.0 is perhaps the idea of mass personalization, as it is the large part of the driving logic for cobots. One could argue that mass personalization is almost entirely irrelevant to the bevel-gear industry since an end-user is not concerned with the appearance of a gear within their mechanism. This is not truly the case, though. For example, most car owners do not care what the hypoid pair in their differential looks like, but, they do care about the driving performance. A bevel or hypoid pair can be customized by considering the specific consumer’s preferences. In this way, a consumer could select a car optimized for efficiency, overload, or quietness. The consumer could potentially even “design” a car to fall somewhere between these three optimizations.

Moreover, there is still need for human skill level within the industry for the operations that have not been considered easily or potentially well automated. In this way, it can be seen how the bevel industry itself stands to benefit from the ideas for Industry 5.0. Many of the production operations will always require a human to handle complex decision-making, but that worker’s ability can be augmented with cobot technology.

Much of the bevel-gear industry is currently very well optimized to serve the needs of its largest consumers, which include the aerospace, automotive, and construction industries. As mentioned prior, the requirements of these industries are the ability to produce many of the same gears or gear-like products as efficiently as possible. A manufacturing facility may also produce a low-quantity run several times throughout the course of a year. In that sort of manufacturing facility, it is not common to produce a unique gear pair outside its new product development and research and development departments. Yet, there are also quite a few bevel-gear manufacturing companies that are well optimized to be individually focused. These companies particularly stand to benefit from the embracement of mass personalization.

General technological trends predict the proliferation of robotic technology, whether it comes as intended by Industry 4.0 or as proposed by Industry 5.0. Unlike the aforementioned industries, the robotic industry has a much higher likelihood for more individualized gearbox requirements as the needs of each consumer will differ. As changing axes of rotation and high precision are often functionally required for robotic arm design, bevel gears are a natural fit. This individualization can be thought of as a conceptual mirror to mass personalization in that it appears to go against many of the established benefits of mass production. Currently the design and manufacturing process associated with bevel gear technology is not as optimized to individualization as it is a gear that will be made many times.

Fully adapting to the needs of individualization while maintaining the established optimizations for mass manufacturing may prove difficult for some within the bevel-gear industry, but that is certainly not to say it is infeasible.  Furthermore, improving upon the capability of individualized design may even go to aid the industries that traditionally rely upon the mass manufacturing of a standard gear set — the aerospace, automotive, and construction industries — since it can greatly expedite the new product-development process. Doing so may aid in the creation of many new technologies within each of those respective fields since transmission design can be a time-consuming and recursive process.

The first of these new optimizations can come from the design process itself. Quite a few software applications exist to allow for a relatively quick design of powertrain systems. If a more complex bevel-gear geometry, such as a hypoid gear, is to be considered, though, the designer must have a very high degree of skill and knowledge on the topic. Even though much of the math behind the design process is already automated, making this process more universal would greatly improve upon the feasibility of a rapid, unique design for an application engineer. One way of doing so could be by providing design recommendations. Something along the lines of, “If you increase the hypoid offset by X amount, you will decrease the volume by Y% while only increasing the thrust load by Z%” could prove invaluable to new designers as that sort of intuition is typically acquired through years of specialized work. Since there are many aspects involved in the design of these gears, there are many different possibilities to optimize against. These recommendations could perhaps come about by considering several “typical optimizations” and performing gradient descent methods for each categorization. Alternatively, a deep learning model may even be appropriate. Fuzzy logic could be used to identify “similar” designs and aid in such optimizations.

Another simple method of expediting the design process could come from considering a library of “base gear” pairs. The designer could work from this library and alter appropriate parameters to suit their design. While this may sound quite simple, it could easily prove to be quite the undertaking since the generation of hypoid profiles is accomplished by considering machine parameters, which have the potential to vary greatly across minor design adjustments.

The development process can be further improved upon by considering the addition of additive manufacturing. This technology has not significantly proliferated into the bevel-gear industry for a number of reasons. Several of which include: the precision entailed still mandates finishing operations, the layering process that is commonly used in plastics-based additive manufacturing results in non-uniform bending and fatigue failure modes, and that 3D point cloud generation of complex gears like hypoids is not possible within many common CAD platforms. Although additive manufacturing has become a common method of rapid prototype development, 3D-printed bevel gears are a long way from replacing those that were traditionally manufactured. But they could readily be used as a placeholder during the prototyping process for initial testing. Once the designer is satisfied, the gear can be replaced with one that is meant for long-term use.

Another adjustment for individualized design could be realized within the machines that generate bevel-gear profiles. These machines are typically large and expensive. Because they go to factories that will use them frequently, the period of return on investment (ROI) is appropriate. Additionally, new machines are typically smaller than their predecessors so the size is no problem to factories that already had machines for the production of bevel gears. However, the size requirements for gears within the robotics industry has the potential to greatly differ from what is normally considered within the aerospace, automotive, and construction industries. A robotic arm requiring a joint with a bevel gear about the size of what is in a differential would be quite large.

While existing machines can produce the smaller gears, the bevel-gear industry could also create small gear CNC machines. These machines would be reminiscent to the tabletop CNC systems that have started gaining popularity within the last decade and would stand opposite to what is typically considered for gear-machine design. They do not need many of the bells and whistles considered within the machines that mass produce bevel gears. The only functional requirement is to produce bevel gears that are on the relatively smaller side, perhaps smaller than 200 millimeters. The prioritization of machine design would be that it is affordable with a small footprint. These considerations could help to reduce the ROI that had prohibited the consideration of developing a bevel-gear-based power transmission system. Furthermore, it is possible to consider an embedded design system where a gear designer can design a whole system and then send the design directly to these small gear CNC machines for manufacturing and prototyping. This would serve to further close the gap between manufacturing and design and could fit quite well within a new product development lab.

These are only several predictions for how the bevel gear industry may react and drive the upcoming industrial revolution. It certainly has some considerations for the future to weigh and decide upon. As with the past, bevel-gear technology could prove to be a driving force for the technological future.

4 Final remarks on Industry 5.0

Industry 5.0 points out several flaws with Industry 4.0. Some of which, such as the creation of a new critical point of failure and the lack of stakeholder consideration, are glaring oversights. Despite being still relatively new, technologists have already developed several ideas and started to formulate a plan on how they can be implemented in such a way as to benefit all stakeholders as much as possible. Impressively, several technologists and researchers have already begun conducting surveys, collecting data, and robustly determining feasibility for all of these plans. Even so, the authors take a slightly critical view on Industry 5.0, as there is still room for development.

One of the core principles behind Industry 5.0 lies with mass personalization. While the concept mass personalization applied to manufacturing is novel, its founding concept of a consumer valuing individuality is not new. As many technologists will point out, several OEMs and SMEs have been providing new and innovative means for personalization far before any sort of formalization of the idea. So, mass personalization standing as a pivotal aspect of Industry 5.0 really only serves as a reminder that mass production prohibits mass personalization. That said, this is, of course, a very important reminder to manufacturers that may be driven only to mass production.

Mass personalization may not seem immediately applicable to most industries, but its indirect application is incredibly significant to many industries. Indeed, there will be a few manufacturing industries that have no application of such an idea. However, any product interfacing with people has the potential to be individualized. For example, one could view a cellphone case as an example of mass personalization. The reader would be hard pressed to find a consumer that cares about how a processor chip — or any internal component for that matter — looks inside their smart phone. What the user does care about, though, is performance and cost. Giving the user the ability to adjust this balance could prove invaluable to OEMs.

As can be extrapolated, mass personalization has the potential to affect many manufacturing industries. The application of cobots could indeed be valuable to these industries since mass personalization makes total automation difficult. Even manufacturers that do not see an application of mass personalization could stand to benefit from the introduction of cobots as there is still the observation that maximum profit does not necessarily result in the most optimized output.

If one considers only output against profit, though, there needs to be concrete research that quantifies just how valuable this efficiency is and a comparison with typical worker efficiency and total automation efficiency. Such a study is hard to perform whereas total automation can be considered with something as trivial as an ROI calculation. Mass personalization and cobots are good ideas, but there must be more, and speculation should not bear significant weight within the world of engineering.

As the reader may have noticed, despite this work focusing upon Industry 5.0, a great deal of attention was paid to the advancements of Industry 4.0, the present. This is because it is the authors’ opinion that Industry 5.0 is not currently unique enough to be considered an industrial revolution in the same way as the past and present. Those periods all represent times of social change and are made possible by some new, emerging technology. While Industry 5.0 presents many important social arguments — arguments that had occasionally been entirely ignored during the “advent of Industry 4.0” — there is currently no new emerging technology at the crux of Industry 5.0. Some may argue the use of cobots for worker augmentation is a foundational concept of Industry 5.0 and is emerging. This technology is not new, though. The same technology that goes into present-state Industry 4.0 robotics can be applied to cobots. Cobots themselves can really be viewed as just another application of Industry 4.0 technology.

None of this is necessarily a bad thing. This is all to say that if Industry 5.0 is still in its infancy, Industry 4.0 is simply an older sibling. Development may be presently rapid, but without any champion for Industry 5.0, the underlying concepts could be viewed as a revision of Industry 4.0 just as well. Industry 4.0 and 5.0 provide a good means to drive technological advancement in a specific direction. In this way, the proposition of Industry 5.0 is similar to a bend along a trail.

5 Conclusion

The future of the manufacturing and bevel gear industry is Industry 5.0. Several critical ideas are behind the revolution of the future such as mass personalization and cobots. While it is still young, more development is needed. The ideas of Industry 5.0 could stand to be greatly beneficial to manufacturers and the bevel-gear industry.

Acknowledgements

The authors wish to thank Dr. Hermann Stadtfeld of the Gleason Works, Dr. Haris Ligata of the Gleason Works, Markus Bolze of the Gleason Works, and Dr. Alfonso Fuentes of the Rochester Institute of Technology for patiently answering countless questions on bevel-gear technology. 

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