1. Introduction
Modernization and industrialization are terms that have been used interchangeably to describe the profound transformations in society since the First Industrial Revolution, which was driven by steam technology [
1]. Industrial modernization, driven by the progressive incorporation of new technologies, has transformed how tasks are performed and products are manufactured. Currently, technologies that are leading the change are those based on digitalization, the Internet, and, more recently, artificial intelligence. Some authors consider that we are currently on the brink of a Third [
2], Fourth [
3], or even Fifth Industrial Revolution [
4].
The advancement of process modernization in a given geographical area can occur naturally as a consequence of technology integration into production systems. However, this progress has also resulted from concrete government policies. At the governmental level, several countries have actively developed productive modernization policies. These initiatives have focused on incentives such as subsidies or tax reductions to promote modernization. One example of such initiatives is Industrie/Industry 4.0 (I4.0), the name given to a German government effort to incorporate new technologies into manufacturing in 2011 [
5]. In this framework, the new Industry 5.0 concept has recently emerged at a level beyond Industry 4.0, which the European Commission defines as a value-driven, collaborative, human-centric, resilient, and sustainable industrial development stage [
6,
7,
8,
9,
10,
11]. The concept of Industry 5.0 extends beyond purely technological advancements, particularly those related to sustainability, which were not considered in previous industrial levels. Industry 5.0 emphasizes environmental responsibility, ethical considerations, and human-centric approaches in industrial processes.
Measuring the progress of modernization in production processes allows for a clearer demonstration of the impact of modernization projects implemented within them. In fact, some authors consider this a critical component [
12], particularly because it enables the evaluation of the effectiveness and impact of private or publicly funded modernization projects, which continue to be awarded at both national and international levels as part of public policies aimed at industrial development across various countries. However, describing the level of modernization in a process is not trivial; the countless available technologies, their different domains, and their varying effects on the process make standardization in measurement difficult [
13]. These difficulties are found even if the aim is to measure only the digital aspects of modernization [
14]. Several research studies and initiatives have attempted to describe modernization in industries and specific production processes. The Secretariat of the Organization for Economic Cooperation and Development (OECD) has attempted to solve the problem of classifying the technological level of certain industries [
15], but the efforts have undergone revisions and improvements to reflect the new technological changes, such as the recent new digital technologies. Other examples have focused on leveraging the conceptual foundation of the Industry 4.0 initiative, which began as a German government effort but has evolved into a globally recognized concept. The term Industry 4.0 is now widely used to describe modernized processes resulting from the incorporation of specific technologies such as the Internet of Things (IoT), smart automation, big data analysis, and connectivity, aiming to create highly efficient, flexible, and interconnected production and manufacturing environments [
5]. Some studies have explored the use of the concept of Industry 4.0 and the transition from previous industry levels to Industry 4.0 as a way to report processes or application areas as containing the most recent digital technologies [
16]. Based on the Industry 4.0 concept and the narrative of industrial modernization in stages, some authors have tried to define Industry 1.0, 2.0, 3.0, and 5.0 to associate a process with a specific technological level of the industry.
A brief literature review reveals that the current Industry 4.0 literature on process modernization typically follows two main approaches: (i) a general overview of enabling technologies, associated opportunities, and anticipated outcomes driven by an imminent technological revolution; or (ii) a classic transition model, where a baseline scenario is upgraded through the incorporation of new technologies, thus reclassifying the process within the new industrial stage [
17,
18,
19,
20]. However, more complex situations may arise where interpretation becomes ambiguous in practice. This occurs, for example, when technologies are not fully implemented on a large scale but instead integrated partially or as individual components. Such cases make it difficult, for example, to distinguish between an advanced Industry 3.0 level and an Industry 4.0 classification. Based on our literature review, we hypothesize that there is a gap in the literature regarding how to answer simple questions regarding how to describe simple modernization cases of process modernization within the conceptual framework regarding the Third, Fourth, and Fifth Industrial Revolutions, as well as Industry 3.0, Industry 4.0, and Industry 5.0. This gap could limit the applicability of existing theories in describing modernization, making it challenging to apply them to actual cases when measuring the initial and final modernization levels, as well as the changes introduced, is necessary. This research aims to analyze cases in which current theoretical limitations become evident. Analyzing these cases could help determine the aspects where existing theories may or may not provide adequate answers and highlight areas where the theoretical framework could be strengthened.
In
Section 2, the materials and methods of this research are presented. In
Section 3, the results are shown.
Section 4 expands on the discussion of the research. Finally,
Section 5 presents the conclusion of this research.
2. Materials and Methods
This research is based on the cases found when executing project “ANID Fondef VIU23P0092 Automated Brew”, which focused on applying Industry 4.0 technologies in breweries. The project was developed and executed between 2023 and 2025, specifically in Temuco, Chile, with funding from the Chilean Ministry of Science and Technology. The objective of the project was to design and validate a system integrating hardware and software to modernize beer production, incorporating IoT devices, cloud computing, and artificial intelligence. The system developed introduced a web platform that could detect variations in controlled variables, classify them, and estimate, through algorithms, the effect of the variation on the product. This web platform was accessed using computers and smartphones and allows for obtaining a brief report about the process. During the execution of the project, an evaluation tool was required to assess process modernization before and after the implementation of new technologies, using the Industry 4.0 framework. While measuring the improvements in modernization, simple yet fundamental questions emerged, which ultimately proved difficult to answer using Industry 4.0-related concepts.
From the initial context provided by the experience within the project, a modernization case with initial and final conditions was characterized, followed by the identification of a set of general questions related to the initial and final cases. Then, a literature review was performed to identify potential answers to questions regarding modernization in the context of Industry 4.0. The general structure of the methodology is presented in
Figure 1.
2.1. Characterization of the Proposed Context and Emerging Questions
The following section presents the case to be analyzed in this study, starting from an initial condition that has been modernized through the addition of an Industry 4.0 system and exploring different possible final scenarios.
Initial Industrial Case: A beer-related industrial process is considered, utilizing automatic temperature control provided by a programmable logic controller (PLC). The industrial process is modernized, obtaining various final cases depending on the exact addition. Final Industrial Case 1: The process is modernized through a project that incorporates a computer with a soft sensor (equipment designed to infer the state of the process using digital data) based on a neural network (NN) and connected to the Internet. Final Industrial Case 2: In this variation, the initial process is further modernized by adding three soft sensors and three computers, with Internet, to the industrial process instead of one. Final Industrial Case 3: This variation replicates Industrial Modernization Case 2, but after one week, the operators chose not to use or sometimes use the soft sensor.
Question 1: Based on the present case, how would each of the proposed scenarios be classified when using the concepts of the Third and Fourth Industrial Revolutions and of Industry 3.0 and 4.0, and what distinguishes each concept from the others?
Justification: These concepts are widely used in the scientific literature to describe technological transitions in concrete processes. Understanding how they apply to specific cases and how they differ from one another is essential to assess their consistency, practical utility, and reproducibility, key aspects that this study seeks to evaluate critically.
Question 2: What defines a 4.0 system in such a way that its incorporation is sufficient for a process to be classified as Industry 4.0, and what is the minimum technological addition required for reaching that level?
Justification: The literature often assumes that integrating certain technologies automatically qualifies a process as Industry 4.0. This question critically examines that assumption by analyzing whether a clear and reproducible definition of a 4.0 system exists, one that enables consistent classification of modernization levels. Identifying the minimum addition required is essential for evaluating modernization strategies and for supporting investment, policy, and assessment decisions based on measurable and operational criteria.
Question 3: In the context of the present case, how should the classification of a process as Industry 4.0 be affected when multiple qualifying systems are incorporated but remain unused or only partially used? Justification: This question seeks to evaluate whether the classification of a process as Industry 4.0 should remain the same when multiple systems are implemented, or if these systems, once implemented, end up being unused or only partially used. This is particularly relevant in cases where technologies are installed but not adopted in practice, since all such scenarios would a priori be classified in the same Industry 4.0 level. The question contributes to assessing whether current classification approaches are adequate for capturing the real state of modernization in industrial processes.
In this study, the concepts of the Industry 3.0 to 4.0 scale were considered for use, along with the framework of industrial revolutions, since these concepts have been regarded in the literature as valid and useful for describing technological transitions in concrete processes. This is supported by the widespread use of the concept in scientific literature. Several studies suggest that when a system with Industry 4.0 technologies is added to an existing process, the process as a whole can be classified as 4.0. This methodological choice allowed us to evaluate whether that assumption holds true in a real case by systematically comparing scenarios with and without such technologies.
2.2. Methodology for Literature Review
This work introduces the Sequential Industry Framework concept to maintain concise language when referring to the conceptual framework of the First, Second, Third, Fourth, and Fifth Industrial Revolutions, as well as Industry 1.0, Industry 2.0, Industry 3.0, Industry 4.0, and Industry 5.0.
In order to attempt to answer the emerging questions, three different literature searches were performed. The first aimed to find the origin of the concepts Third Industrial Revolution, Fourth Industrial Revolution, Industry 4.0, and Industry 3.0 to establish clear differences. This search was performed using Google and Google Scholar, searching for previous usages of the terms in the search of their original intended usage. Then, a second literature search was aimed at identifying the defining characteristic that would allow the identification of a 4.0 system and its minimum concrete expression. For this search, influential works from the Sequential Industry Framework were used based on a persistent citation of the works over time. For this purpose, manuscripts and/or books that had, on average, at least 100 citations per year since their publication were selected. The number of years was calculated as 2025 minus the year of publication plus one. The literature search was conducted using Google Scholar, where 150 articles were retrieved for each of the following concepts: Industry 4.0, Industry 5.0, Third Industrial Revolution, Fourth Industrial Revolution, and Fifth Industrial Revolution. Finally, a third specific search was conducted to determine whether the core literature addressed transitions between industry levels, particularly from Industry 3.0 to Industry 4.0. This search focused on cases involving the incorporation of varying quantities of modern systems or instances where systems ultimately remained unused. If this situation was not covered in the core literature, an additional search was carried out to identify less cited works that specifically explored this issue. A comprehensive representation of the case, questions, and direction of the literature searched is provided in
Figure 2, which expands the initial three-stage methodology presented in
Figure 1, following the same color for each stage, with stage 1, blue, for the characterization of the modernization case, stage 2, yellow, for the identification of the emerging questions, and stage 3, green, for the literature search.
3. Results
A review of the literature and the distinguishing criteria between each industrial revolution or industry level raises the question of where the term “Third Industrial Revolution” originally emerged, as tracing its origins could reveal relevant insights. A retrospective review of the literature highlights the work of Jeremy Rifkin, who, in both a book and a newspaper column, noted that he collaborated with leaders of the European Parliament in 2006 on an economic development plan centered around the concept of the Third Industrial Revolution [
2,
21]. Furthermore, the search reveals that Jeremy Rifkin had already introduced the idea of a Third Industrial Revolution in his earlier book,
The End of Work (1995), where he referred to an electronic revolution that began after World War II [
22]. In
The End of Work, Rifkin attributes the concept of the Third Industrial Revolution to an electronic revolution, which he suggests was implicitly mentioned in a 1949 article.
When reviewed in Spanish, an explicit and exact reference to the “Tercera Revolución Industrial” consistent with the current understanding of the Third Industrial Revolution was found. The search leads to the article here translated as “The Third Industrial Revolution: Social, Economic, Cultural, and Ethical Consequences”, published in 1994 by Vega Cantor from Colombia [
23]. In this work, the author identifies a series of technological changes, including microelectronics, information technology, telecommunications, biotechnology, new materials, and alternative energies, while acknowledging the dominant role of oil in the Second Industrial Revolution, which, according to the author, was still ongoing at the time of publication (1994). Nevertheless, he also points to emerging possibilities enabled by new energy sources such as wind and solar power.
When reviewing sources in French, it was possible to identify the term “Troisième Révolution Industrielle”, Third Industrial Revolution, in the article “La troisième révolution industrielle et ses enjeux humains”, published in the
Revue européenne des sciences sociales, Volume XXIX, 1991 [
24]. This article discusses the human implications of the Third Industrial Revolution, characterizing it by technological and scientific advancements at the time of its writing.
In 1987, an explicit reference to the Third Industrial Revolution appeared in a recopilatory work published by UNESCO in France. This book presents the question of whether a new industrial revolution is starting. In this book, the new third industrial revolution is observed by the changes in energy and methods of communication, the introduction of computers, computer networks and information sciences, the transmission and retrieval of data, computer-aided design and manufacturing, and robotics, all tendencies that had an economic impact on the society at that time (1987) [
25].
No references to the Third Industrial Revolution were found before 1987 in English, French, Spanish, Russian, and Chinese. However, in German, the work
Die dritte industrielle Revolution, Wie die Mikroelektronik unser Leben verändert by Dieter Balkhausen and published in 1978, was found. This work describes the Third Industrial Revolution as being driven by the emergence and widespread use of microelectronic devices [
26].
Other no exact references that could be considered related to the Third Industrial Revolution include
The Third Wave, a book published by Alvin Toffler in 1980, in which he proposes the existence of a third wave in human progress: the first being the agricultural revolution, the second the industrial revolution, and the third, occurring in his time, based on information [
27]. Further earlier sources identified through English-language searches include “The Triple Revolution”, a U.S. governmental memorandum from 1964, which identified three technological megatrends, the rise in automation, the nuclear arms race, and advances in human rights, concepts that differ significantly from Rifkin’s framing of the Third Industrial Revolution [
28].
From a historical point of view, the terms that followed the appearance of the Third Industrial Revolution were both implicitly treated as synonymous: Industry 4.0 (Industrie 4.0) at the Hannover Fair in 2011 and “4. Industrielle Revolution” in a newspaper column published at that time, showing the potential of incorporating Internet, Internet of things, smart processes and products, and cyber–physical systems in German manufacturing [
29]. Then, both the term Industry 4.0 (Industrie 4.0) and the Fourth Industrial Revolution appeared in the recommendation written for the German manufacturing industries in 2013 [
5]. The Fourth Industrial Revolution then was popularized by Schwab with its book in 2016 [
3].
The term Industry 3.0 was proposed retroactively (2014), as the previous stage of Industry 4.0, Industrie 3.0 as a synonymous with the Third Industrial Revolution and related to digitalization and the introduction of programmable logic controllers that enabled digital programming of automation system technologies [
30].
Relevant works were searched in the areas of the Third, Fourth, and Fifth Industrial Revolutions and the related concepts of Industry 3.0, 4.0, and 5.0 based on the criterion of persistent citation defined as more than 100 citations per year since publication; the results are presented in
Table 1,
Table 2 and
Table 3.
Table 4 presents a summary of the articles and the range of publication years for each topic, indicating the range of bibliographic citations obtained for each category. In the concept column, the order of the search is presented.
When analyzing the concepts of the Third Industrial Revolution in the core literature with persistent citations, the first search looked for work that did not mention the Fourth Industrial Revolution. From the only work found, this source neither mentions the concepts of Industry 3.0, 4.0, or 5.0 [
2]. In the case of the Fourth Industrial Revolution, some authors do relate the concept to Industry 4.0 [
33], while others do not mention it [
3,
31,
32,
34]. In the literature on the Fifth Industrial Revolution, some authors do not relate it to Industry 5.0 [
35], while others do [
6,
36].
Regarding the concepts of industrial revolutions and industry levels, in the referenced work, some studies on Industry 4.0 consider the notation and concept of industry levels as equivalent to that of industrial revolutions [
6,
30,
38,
39,
40,
41,
42,
43,
44,
45,
46,
47,
48,
49,
50,
51,
52,
53,
54,
55,
56,
57,
58,
59,
61,
62,
64,
65], while others do not mention industrial revolutions in the body of the document [
63]. In the case of Industry 3.0, all the works consider the concept equivalent to that of an industrial revolution [
74,
75,
76], and for Industry 5.0, all the works consider the concepts either equivalent or strongly related [
36,
66,
67,
68,
69,
70,
71,
72] with only one work that does not mention it [
73].
Given that the literature on industry levels is more frequently linked to that of industrial revolutions, rather than industrial revolution literature referencing Industry 3.0/4.0/5.0, it can be concluded that the concept of Industry 3.0/4.0/5.0 is accepted as a derivation of the broader industrial revolution concept. However, most publications do not clearly define the distinction between these terms. One of the few studies that attempts to differentiate between Industry 4.0 and the Fourth Industrial Revolution points out that the study includes a comparison between Industry 4.0 and the Fourth Industrial Revolution, noting that industrial revolutions represent systemic transformations that affect society, governance structures, and personal identity, whereas Industry 4.0 primarily pertains to manufacturing within this broader revolution [
60]. The author argues that in Korea, the term “Fourth Industrial Revolution” is more appropriate than “Industry 4.0”, as it builds upon the digital revolution, incorporating greater connectivity, improved sensors, artificial intelligence, and machine learning [
60].
In the search for consensus within the literature, Industry 1.0 is marked by the introduction of mechanical machines moved by water and steam engines [
30,
39,
49,
52,
53,
58,
66,
67], with examples such as the mechanical loom [
49,
58] and the development of mechanical tools [
49].
Major innovations of Industry 2.0 were electricity [
39,
43,
52,
53,
54,
66,
67,
74,
76], which enabled the replacement of steam power [
52] and the replacement of steam by chemical energy sources [
52]. Other technologies include the conveyor belt [
53,
58]. Other authors include at this level additional technologies such as electronics, mechanical devices, and automobiles [
76].
In relation to Industry 3.0, the key technologies include electronics [
6,
39,
45,
49,
52,
53,
58,
66,
74], microelectronics [
39,
45], integrated circuits [
52], information technologies [
39,
49,
51,
52,
53,
58,
74], communication technologies [
39,
42,
52,
53], partial automation [
66], computer numerical control [
39], computer-aided manufacturing [
39,
42], use of PLCs [
6,
49], and industrial robots [
39].
The technologies of Industry 4.0 include cyber–physical systems, defined as a fusion between the physical and digital worlds, where machines and products acquire smart characteristics [
39,
42,
46,
49,
51,
52,
55,
64,
65] and where decentralized decision-making can be implemented [
46]. Another key technology is the Internet of Things, defined as an interconnected and integrated network of sensors, actuators, hardware, and software that enables data collection and exchange [
39,
40,
41,
42,
43,
46,
49,
51,
52,
59,
62,
64,
65]. Another technology is the Industrial Internet of Things, specifically adapted to industrial needs and requirements [
53,
62]. Internet of Services refers to systems that generate outcomes based on input data and can be located either within or outside the organization [
41,
46,
47,
64,
65]. Cloud computing enables the storage, processing, and use of applications for information and data processing, independently of the access location, through the Internet [
39,
40,
41,
44,
49,
51,
65,
74]. It also refers to the use of big data and data analytics tools to enable data-driven decision-making [
40,
44,
49,
51,
52,
62,
71,
74]. The incorporation and implementation of artificial intelligence as a tool that replicates human cognitive abilities [
41,
44,
50,
51,
59,
62,
71], machine learning [
54], additive manufacturing, such as 3D printing [
44,
47,
51,
59,
60,
62], industrial robots [
39,
41,
51,
59,
62], the use of simulation programs and software [
44,
49,
51,
62], augmented reality and virtual reality [
41,
44,
52], blockchain [
39,
44,
59,
62], RFID [
51,
62,
65,
74], cybersecurity [
51], digital twin [
71], mobile devices, and applications [
44,
51] are also part of Industry 4.0.
The possibility of using the dates in the Sequential Industry Framework as a basis for classifying technologies and processes was examined. The findings show a general consensus in identifying the beginning of Industry 4.0 in the year 2011, as this marks the presentation of the Industrie 4.0 concept at the Hanover Fair. Despite this, there are significant divergences in the reported dates for the different industrial revolutions. For example, the beginning of the First Industrial Revolution was placed anywhere between the 18th and 19th centuries, and its end was placed between the 1840s and early 1900s. The Second Industrial Revolution is said to begin between 1870 and the 20th century, and its end is reported to be between 1930 and 2008. The Third Industrial Revolution is considered to start as early as 1950 or as late as 2007, with its end ranging from 2000 to the present day. The beginning of the Fourth Industrial Revolution is reported as being between 2000 and 2020, while the Fifth Industrial Revolution is dated from 2017 to a point in the future. These wide-ranging estimates for the start and end of each industrial revolution contrast sharply with the more defined timelines reported by other authors [
34] that point out that systems from the First Industrial Revolution remain in use today, which could also be interpreted as an ongoing outcome of that revolution. Based on the results, it becomes evident that there is a lack of clear definition and consensus regarding the dates and the concept of industrial revolution, as well as the notion of industry across its different levels (see
Table 5).
Finally, there are studies outside the core literature of the Sequential Industrial Modernization Framework which introduce the concept of Industry 3.5 as a hybrid approach between Industry 3.0 and Industry 4.0 [
77]. In Industry 3.5, five key characteristics are identified, including digital decision-making, smart supply chain, smart manufacturing, total resource management, and smart factory. Upon reviewing this literature, examples associated with this level include the implementation of evolutionary algorithms for task organization [
77,
78,
79,
80,
81,
82,
83], for smart supply chain [
84,
85], resource management [
86,
87], smart production and quality [
88,
89], computer vision [
90], and other cases of intelligent algorithm applications [
91,
92,
93]. All the previously reported works correspond to application cases of optimization algorithms that incorporate aspects related to evolutionary algorithms applied in various domains. Despite this, the 3.5 level does not, for instance, distinguish the number of algorithms or systems implemented but merely focuses on incorporating smart algorithms.
When reviewing the literature, information can be found on transitions from earlier levels to Industry 4.0, where technologies classified as 4.0 are described. However, these technologies are considered in a general or conceptual manner, without accounting for the number or scale of systems involved, nor for partial implementations. As a result, it can be concluded that the reviewed literature does not provide sufficient information to describe the exact minimum addition or the criteria needed to reach Industry 4.0.
A study was found in a specific literature search concerning progressive implementation in terms of quantities and frequency of use. The reported study tried to implement a measuring-like approach of a specific process in terms of Industry 1.0 to 5.0 [
39]. This work has classified industrial practices within the seafood processing industry according to industry levels from 1.0 to 5.0. These classifications address various levels of practice, adoption, and readiness; however, the classification presented some contradictory aspects in the methodology. Finally, another contradictory work in terms of the use of the levels of modernization related to agriculture was found [
94].
4. Discussion
4.1. What Distinguishes TIR, FIR, I3.0, and I4.0?
The term industry and its levels, from 1.0 to 5.0, have been widely used as synonymous with the concept of industrial revolutions. However, significant discrepancies emerge when analyzing the periods marking the beginning and end of each industrial revolution. In fact, as shown in
Table 5, there is no consensus regarding these revolution dates, except for specific cases, such as the year 2011, commonly cited as the beginning of Industry 4.0. This lack of agreement on dates reveals a concerning absence of scientific rigor. The disparity may be attributed to the lack of a clear and universally accepted definition within the industrial modernization research community. Given the inconsistencies in reported timelines, it is not feasible to define precise periods for each industrial level. As a result, classifying technologies or processes based on dates becomes unreliable, even when using objective indicators such as the year of publication, patent filing, the manufacturing date of a component, or the start-up date of a process. Furthermore, if it is assumed, as some authors suggest, that revolutions such as the First through Third have already concluded (see
Table 5), this raises the question of whether it is still possible to develop systems associated with these earlier revolutions today. In these cases, a deeper question arises: under what specific conditions should a system be classified as belonging to a past industrial revolution rather than the current one? This issue highlights a fundamental gap in the literature, where the absence of clear temporal criteria makes it difficult to determine the appropriate classification. Without an agreed-upon framework, the application of these concepts in scientific discourse becomes inconsistent and potentially misleading. Although the terms are widely used, the lack of consensus undermines their analytical value and calls into question the reliability of the criteria and their sources for comparative or evaluative purposes.
A retrospective review of the literature highlights the work of Jeremy Rifkin, noting that he collaborated with leaders of the European Parliament in 2006 on an economic development plan centered around the concept of the Third Industrial Revolution [
2,
21]. Based on this precedent, an obvious question arises: Why, in 2006, were international agencies satisfied with the term Third Industrial Revolution but, only a few years later, was there a push to define a Fourth Industrial Revolution, especially considering that at the same time, governments were actively developing initiatives based on the idea of the Third Industrial Revolution, often using similar concepts? Is Industrie 4.0 a hype, as some authors have questioned [
30]?
It is at this point that analyzing the untranslated German work
Die dritte industrielle Revolution helps explain why, in Germany, the country of origin of the concept Industrie 4.0, the idea of a Fourth Industrial Revolution may have seemed more reasonable rather than in English, where the notion persisted that the Third Revolution was still unfolding. Rifkin popularized the concept in English, whereas in other languages such as French and German, the idea of a third revolution based on electronics had already been recognized and disseminated through sources that were never translated [
24,
26,
95] or that lacked popularity [
25]. The 1978 German book, which framed the Third Industrial Revolution around the rise in electronics, offers a logical foundation for the later proposal of a Fourth Revolution focused on advanced computing and internet-based communications. This would show that hype or the popularity aspect of the concepts has played a major role in the defining characteristics of the concepts, which can also explain why a deeper analysis allows finding important inconsistencies.
It is noteworthy that the 1978 publication, which explicitly coined the term Third Industrial Revolution, has not been used as a reference point to define the beginning of the Third Industrial Revolution, unlike the case of the 2011 Hannover Fair, which is widely cited as the starting point of Industry 4.0. The first reference to the Third Industrial Revolution also lacks recognition as its citation score only reaches 48 on Google Scholar, again showing the importance of the popularity in the development of the concepts (last accessed on 23 April 2025).
It is therefore in the more distant works, the 1978 book and the Industrie 4.0 report from 2013, where the most significant differences between the two concepts, Industry 3.0 and Industry 4.0, can be observed. The former describes the profound changes brought about by the introduction of electronics through digital systems, while the latter, Industrie 4.0, extensively employs concepts related to data acquisition, processing, and transmission based on the computational technologies already available at that time.
4.2. What Defines a 4.0 Technology, and What Is the Minimum Addition for Reaching Industry 4.0?
The criterion of associating specific technologies with a particular industrial revolution appears to be a more practical approach to classifying systems. However, it must be noted that there is no consensus among authors on a definitive list of technologies. Furthermore, the technologies themselves are not always clearly defined.
As has been stated, “a cyberphysical system can be just about anything that has integrated computation, networking, and physical processes. A human operator is a cyber–physical system, and so is a smart factory” [
46]. For instance, when referring to cyber–physical systems, the concept does not necessarily imply internet use or require state-of-the-art computing devices. From a commercial perspective, no off-the-shelf products directly “add” a cyber–physical component; rather, it is an abstract representation of the interaction among multiple agents within a system. The lack of formal requirements makes it difficult to determine precisely when the cyber–physical threshold is met. Relying on the classification of technologies strictly according to those listed by authors in the core literature can also be limiting, especially for technologies not explicitly described in those sources. Determining whether such technologies belong to a specific industry level becomes a complex task in the absence of clearly defined criteria.
The same analytical difficulty applies to the Internet of Things (IoT), often defined as a paradigm in which devices communicate directly with each other without human intervention. However, such capabilities may or may not require the use of the Internet itself, as Internet protocols are just one of many ways to transmit data over a given medium. For instance, a local installation using digital communication protocols could still exhibit functional attributes similar to IoT systems without relying on internet connectivity.
Similarly, the concept of cloud computing, understood as performing computation on a remote server, also presents definitional challenges. Internet access is not strictly necessary to enable remote processing capabilities. Moreover, cloud computing as a functionality has existed since the early development of websites, particularly once users were able to upload their content. Web servers allow access to stored data from multiple locations and can perform processing tasks on the uploaded content.
Regarding big data, the challenge arises from a different angle: Internet connectivity is not necessarily required to process large volumes of data. Such processing can be performed locally, using on-premise computing resources, without the need for remote servers or cloud-based infrastructure. This raises an important question: At what point does data processing activity transition from being characteristic of Industry 3.0 to qualifying as Industry 4.0? Similarly, how frequently such processes must occur to justify the classification is also unclear, and these aspects are not addressed in the core literature reviewed.
A comparable situation is found with 3D printing. As a technology that adds material to build three-dimensional structures, 3D printing does not inherently require Internet connectivity or intelligent algorithms. In practice, 3D structures can be manufactured using preloaded design files stored in compressed formats directly on electronic chips, eliminating the need for external software during fabrication. Upon reviewing the compiled literature, no objective or reproducible justifications were found to explain why certain technologies are categorized under Industry 4.0 rather than 3.0. This lack of standardized criteria further complicates efforts to consistently classify technologies across industrial levels. There is a clear need for standardization of the defining characteristics of these technologies in order to establish concrete and precise definitions.
Following the questions presented in the methodology, specifically, what defines a 4.0 system and what is the minimum addition required to reach Industry 4.0? In this framework, the initial case consisting of an industrial process with temperature control implemented by a PLC would have the classic automation labeled by Industry 3.0 if industrial progress was to be considered from a historical perspective, as stated by others [
20]. For instance, if modernization into Industry 4.0 is wanted, a system based on 4.0 technologies could be purchased and installed to provide more complex insights and data analysis. If installed, the process would be evaluated as Industry 4.0, following an approach reported by others [
40]. However, there are difficulties with regard to the exact difference between Industry 3.0 and Industry 4.0 in industrial processes, considering that both levels have digital technologies, including computers, as stated by others [
16].
The difficulty distinguishing between levels 3.0 and 4.0 becomes clear when attempting to classify a neural network implementation as a potential 4.0 system. Neural networks are often considered intelligent systems and thus could be categorized as 4.0 technology. However, they were invented in the 20th century and can be implemented using entirely analog components, such as vacuum tubes, but also with digital systems, microcontrollers, and computers. This case illustrates the lack of a clear, reproducible, and objective classification procedure, not only for neural networks but for various other technologies as well. A hardware-based classification could emerge as a potential criterion for classification; however, this idea would require deep exploration.
4.3. How Should Multiple, Unused, or Partially Used Industry 4.0 Systems Be Accounted for?
While Industry 4.0 primarily emphasizes revolutionary advancements in industrial processes, modernization can also occur incrementally by gradually integrating systems within the same technological level, resulting in step-by-step improvements. The Industry 4.0 framework defines revolutionary changes through transitions from levels 1.0 to 4.0 but does not effectively address incremental or partial advancements within a single level. In the Industry 4.0 framework, if an initial Industry 4.0 process is modernized by incorporating various new Industry 4.0 technologies, it would still be classified as Industry 4.0 with the classic approach.
A reported study attempted to measure Industry 1.0 to 5.0 levels in seafood processing [
96]. However, the application of Industry 4.0 concepts reveals notable contradictions, grounded in the weaknesses of the base concepts pertaining to the Sequential Industrial Modernization Framework, that, in our opinion, end up making the efforts to measure partial and progressive implementation not useful. For example, manual tasks are categorized under Industry 1.0, even though manual labor is not representative of industrial production. Similarly, the replacement of manual labor by machines has been classified as part of Industry 2.0, despite mechanization being described in early sources as a defining feature of the first industrial revolution [
38,
97]. Oral communication is classified as Industry 1.0, even though its use predates the First Industrial Revolution, while written communication is associated with Industry 2.0, despite its historical significance in transitioning from prehistoric to historical times. Additionally, the use of electricity is attributed to Industry 3.0, although key contributions to electric machinery by Tesla and Edison predate the 20th century, and electricity is widely regarded as the driving force of the Second Industrial Revolution [
38,
97]. Human sensory methods are also classified under Industry 1.0, despite their lack of direct relevance to the First Industrial Revolution. On the other hand, technologies such as IoT, AI, and cloud-based solutions, which define Industry 4.0 [
97,
98], have been included in the classification of Industry 5.0 in smart food laboratories. While these inconsistencies and contradictions do not undermine the overall merit of aiming to classify different aspects within specific industry levels, they highlight the limitations of the frameworks based on industrial revolutions, including Industry 3.0/4.0/5.0 concepts, thus making the resulting efforts to describe increasing numbers of systems or partial implementation of the cited work not useful for practical application.
Although such examples may initially appear illustrative in terms of the contradictions found when applying the concepts pertaining to the Sequential Industrial Modernization Framework, a review of other sources reveals even deeper inconsistencies in the definition of industrial levels with a rather important amount of cites (930 in Google Scholar last accessed on 26 April 2025). For instance, in the agricultural domain, Industry 1.0 has been associated with practices involving manual labor or animal power, dating back over 10,000 years, clearly contradicting the notion of Industry 1.0 as linked to the First Industrial Revolution. Similarly, Agriculture 2.0 has been defined by the introduction of steam-powered machinery. These cases highlight that the literature on Industry 4.0 often lacks rigorous analysis of the preceding levels and applies these classifications without ensuring coherence with related historical and academic sources [
94]. Finally, the large number of citations reinforces the perceived validity of the original work, making it difficult to recognize conceptual errors. As the work becomes widely accepted and cited, critical analysis decreases, and even if inconsistencies are later acknowledged, the widespread dissemination of the original ideas makes correction unlikely.
4.4. Discussion with Experts
During the peer review process of this article, several insightful comments and questions were raised, contributing meaningfully to the ongoing discussion. Since these remarks may reflect broader concerns among experts in the field, they are presented and addressed here to clarify key aspects of the debate surrounding industry levels, the methodology, and the results of this study. Each comment and response are identified using a three-digit code, where the first digit refers to the reviewer, the second to the revision round, and the third to the specific comment within that round.
Comment 1.1.1: The results are based on a very soft evaluation of the application of I4.0 and 5.0 without having a solid benchmark to apply. A survey of the users would have been a good validation of the findings, which would have allowed for additional statistical analysis of the results. Overall, it is a nice step towards defining the intentions of I4.0/5.0.
Response to Comment 1.1.1: This study analyzes a theoretical yet concrete and well-defined problem related to the application of the Industry 4.0 concept to describe modernization in specific cases. A series of modernization examples was established, and an exercise was proposed in which the initial and final cases were evaluated as if they were part of a test on Industry 4.0. In most of the analyzed cases, the problem that arises is that the Industry 4.0 concept does not allow for the description of incremental improvements or that the classification of the same process may vary according to different authors, some of whom contradict each other. This demonstrates that defining Industry 4.0 based solely on new opinions will not resolve the existing conceptual confusion. This paper argues that the lack of precision in the conceptualization of Industry 4.0 prevents the adequate resolution of simple cases. Recognizing these weaknesses is, in our view, a valuable contribution, as it represents the first step toward addressing this gap. The solution to these problems should come from more precise and structured theoretical definitions, given that expert consultation has been a recurring approach in the literature that has failed to provide precise answers. In fact, despite numerous conferences on Industry 4.0, fundamental issues, such as the distinction between Industry 3.0 and Industry 4.0, remain unresolved to date. More than 10 years after its initial conceptualization, discussions on a new Industry 5.0 have already begun, yet this concept, in our opinion, also lacks a clear definition for scientific use.
Comment 2.2.1: In the introduction and later on, the authors repeat that there is no clear and commonly accepted distinction between “Industry 3.0” and “Industry 4.0” in the literature. Nevertheless, the authors use several questions to make this distinction, only to conclude that their questions could not be answered.
Response to comment 2.2.1: Regarding the affirmation that there is no clear distinction between Industry 3.0 and Industry 4.0, this has to be clarified. It is true that there is no universal consensus on the concepts, which can be initially found in a quick literature search and comparison, but there are different levels of disagreement, which are very important to discuss as these have not been previously addressed in the literature. This was analyzed in this work. The first distinction concerns the concepts of the Third Industrial Revolution and Fourth Industrial Revolution. Some authors who support the concept of the Third Industrial Revolution have publicly criticized the definition of the Fourth Industrial Revolution, arguing that an industrial revolution should be understood as the societal impact of the convergence of technologies across three domains, which together form a new platform [
21]. These three domains are communication technologies for managing economic activity, new forms of energy to power production, and new modes of transportation. According to this perspective, the First Industrial Revolution combined the telegraph and steam press, coal, and locomotive; the Second Industrial Revolution included the telephone, electricity, cheap oil, and internal combustion vehicles. The Third, and what the author considers the current revolution, combines the Internet, renewable energy, and driverless transportation. From this viewpoint, digitalization is a defining feature of the Third Industrial Revolution. The author argues that these transformations are incremental and will take 30 to 40 years to fully unfold, and therefore, proposing the existence of a Fourth Industrial Revolution is a claim built on “shaky ground” [
2].
On the other hand, despite criticisms, the Fourth Industrial Revolution has emerged as a popular concept that has attracted significant interest in the literature and ultimately dominated the narrative. Moreover, this concept is often presented in association with Industry 4.0, and the two terms are frequently used interchangeably. This creates a conceptual problem: if the critiques of the Fourth Industrial Revolution are valid, particularly the claim that it refers to a revolution that has yet to begin fully, then this conceptual fragility extends to Industry 4.0 as well. The issue becomes more pronounced when Industry 4.0 is defined by retroactively labeling the previous revolutions as Industry 1.0, 2.0, and 3.0, reinforcing a Sequential Industrial Modernization Framework that lacks historical consistency. It is worth noting that, in our review, we identified one author who explicitly distinguishes between the Fourth Industrial Revolution and Industry 4.0. According to this view, Industry 4.0 refers specifically to transformations within the industrial domain, whereas the Fourth Industrial Revolution encompasses the broader societal changes brought about by the same set of technologies [
60].
Within the theoretical literature on Industry 4.0, a distinction is indeed made between Industry 3.0 and 4.0. However, it is also acknowledged that both share the foundational feature of digitalization. While there are elements that allow for the characterization of each industrial level, what remains unanswered is the core issue of how the transition from one level to the next actually occurs. This raises a key question: At what precise point in the industrial domain can we say the shift from Industry 3.0 to 4.0 takes place? This study addresses this question, which demands a clear answer, yet no such answer is found in the literature with sufficient rigor, as the concepts used for the transition into Industry 4.0 also lack clear definitions and concrete technical specifications.
Underscoring the importance of addressing this gap is the fact that many current government initiatives for Industry 4.0 modernization target SMEs. These companies often operate with limited investment capacity, yet the expectation is that, with modest upgrades, they can reach Industry 4.0 status. Therefore, a precise and operationalizable answer is necessary. It is important to reiterate that the initial aim of this study was not to propose definitive answers but rather to highlight the lack of clarity in current theorization. We argue that identifying and analyzing inconsistencies through a set of structured cases and questions provides a sufficiently deep approach.
Nonetheless, we consider that this area represents fertile ground for future research. Depending on how new conceptual frameworks are defined, the transition between levels could be interpreted in different ways. First, it could be interpreted as a disruptive shift, where the mere incorporation of a specific element is sufficient to reach a new level. Second, it is a gradual process requiring an accumulative set of technologies or functionalities. Third, as a non-exclusive transition, where the previous level is not abandoned but maintained through a model of modernization by addition.
Comment 3.1.2: In general, there is no solvable research problem.
Response to comment 3.1.2: The research problem examines whether the current Industry 4.0 theory fundamentally addresses modernization and can be used to solve basic and concrete modernization questions. The unexpected finding is that these questions cannot be adequately answered within the current Sequential Industrial Modernization Framework. However, this does not imply that such problems cannot be solved. On the contrary, this highlights an important research opportunity. By defining the abstract issues outlined in this study, new, more precise, and rigorous definitions may emerge, providing clear and reliable solutions to these problems. This approach would enable a shift from a vague concept to one that is both theoretically and useful in practice.
Comment 3.2.1: In my opinion, the authors are trying to discuss philosophical issues, but from a practical point of view, the primary issue is increasing production efficiency.
Response to comment 3.2.1: In this regard, one of the interesting aspects of this work is to show that depending on the way that the process modernization is considered, even if Industry 4.0 promises increases in efficiency and the introduction of new digital technologies, both of these aspects do not always concur. In this sense, not all cases of modernization into Industry 4.0 would have increases in production efficiency, especially in cases analyzed in this work, for example, if the technology is acquired but ends up being not used, or partially used, or used for a task that was already performed without technology without offering new value to the processes. These questions are related to how to measure efficiency in these cases and are worth discussing. As public and private funds are directed at modernization and potentially to the acquisition of Industry 4.0 systems, a correct assessment is important. Although the reviewer points out that the primary issue about production is efficiency, efficiency in itself is not enough; other critical attributes when measuring the modernization of the process are productivity, sustainability, and reliability. These aspects are not discussed in the related literature, which states that although some are obvious, they are not always taken into consideration. For example, not all processes that go from Industry 3.0 to Industry 4.0 would have increased efficiency, productivity, sustainability, and reliability.
Comment 3.3.2: The authors point out the inconsistency of defining the time boundaries of a particular revolution. At the same time, it is obvious that different countries or enterprises within one country can belong to different technological levels, thus the possibility of determining the time of the emergence of a new industrial revolution is possible only post factum and is of more historical and philosophical value than practical and technical.
Response to comment 3.3.2: The authors share the view of the reviewer. Indeed, companies and countries may operate at different technological levels. However, it is important to emphasize the origin of this work: the objective was to ground the concepts of Industry 4.0 by applying them to a specific case and evaluating their actual usefulness in classifying the level of modernization. Although some studies have attempted this task [
96], their results remain debatable. Our analysis highlights the need to develop better tools for measuring modernization in concrete, specific cases, moving beyond the limitations of broad and imprecise notions such as industrial revolutions or industry levels. Building better classifications that accurately describe how concrete processes improve or evolve is essential for guiding the modernization of companies with practical and technical criteria. Ultimately, this work shows that the issue remains unresolved, which is not immediately evident given that many widely cited publications have adopted the Sequential Modernization Framework to describe advanced levels of modernization in specific applications.
4.5. Addressing the Weaknesses in the Reviewed Literature
At the conclusion of the analysis carried out in this study, several weaknesses in the existing literature become evident. The historical criterion proves to be of limited use, and there is no consensus regarding the concepts of industrial revolution or industry levels. Moreover, it appears unlikely that such a consensus will be reached if the literature continues to develop along its current trajectory. Describing the transition between levels based on the partial incorporation of technologies remains particularly problematic. Additionally, using specific technologies to distinguish Industry 4.0 from Industry 3.0 also presents challenges, as these technologies are neither rigorously defined nor supported by shared technical definitions across the literature.
In response to these weaknesses, several approaches are proposed to help strengthen the core literature in this area of study. First, it is essential to acknowledge that there is no consensus regarding the foundational concepts pertaining to the Sequential Industry Framework. Therefore, when a study refers to industrial revolutions or industry levels, it should explicitly reference the definition proposed by a specific author, recognizing that this definition may differ from those used by others. This practice would allow for a more rigorous discussion of the concepts in relation to their stated definitions or their absence as presented by individual authors. This will allow for transparent comparison and critical discussion of conceptual variations.
On the other hand, it must be recognized that using a historical or date-based criterion to define the beginning or end of a particular industrial revolution or industry level is not feasible, as technological development depends on the geographic context and can vary significantly even at the local level among companies, industries, or communities. Including historical aspects in introductory sections does not provide objective information, and it is surprising that this evident weakness has not been previously addressed by the research community working in the field of Industry 4.0.
The technological criterion appears to be more useful for defining the different industry levels, but it is essential to recognize the need to propose specific technical criteria to define these technologies. Generic descriptions are not sufficient. General or vague descriptions should be replaced with measurable attributes or thresholds. Case studies should consider nontraditional or borderline systems and should address whether partial incorporation of technologies is sufficient to shift a system to a higher industrial level and under what conditions such classification is justified. The development of technical classification criteria for modernization could become a fertile field of research projects, contributing to a more concrete and rigorous foundation for this area of study.
For this reason, it is also essential to recognize that concepts, understood as models representing reality, must be much more rigorous and subject to critical analysis. They should not be accepted merely on the basis of apparent utility, the prestige or popularity of the authors who proposed them, or by the frequency of citation. Concepts must be subjected to scientific scrutiny and evaluated based on internal coherence, reproducibility, and applicability.
Despite this, and considering that the literature in this field is relatively consolidated, with numerous and widely cited works, and that the existing weaknesses are not broadly acknowledged within the area of study, it becomes evident that the problem of describing modernization remains unresolved. For this reason, it is both advisable and necessary to initiate efforts aimed at proposing new frameworks for understanding modernization from a broader perspective, with frameworks capable of providing better descriptions that compete with the existing conceptualizations.
5. Conclusions
In this study, we tried to use the concepts of the Third, Fourth, and Fifth Industrial Revolutions and Industry 3.0, 4.0, and 5.0, here considered part of the new term Sequential Industry Framework, to describe a simple modernization case in which a base situation is modernized by adding an Industry 4.0 technology and answer questions that could emerge when discussing the process. Core literature on the Sequential Industry Framework was identified using a 100-citations-per-year threshold, yielding one work on the Third Industrial Revolution, five on the Fourth Industrial Revolution, three on the Fifth Industrial Revolution, thirty-two on Industry 4.0, eleven on Industry 5.0, and four on Industry 3.0. Unexpectedly, our review showed that the core literature, although it describes the Sequential Industry Framework, does not resolve what constitutes Industry 4.0 technology, how Industry 3.0 differs from Industry 4.0, or the minimal exact technological addition needed to reach Industry 4.0. Also, the use of dates for defining each industrial revolution failed to find a clear consensus. The First Industrial Revolution ranges from the 18th and 19th century to between 1870 and early 1900s, with the Second starting between 1870 and the 20th century and ending between 1930 and 2008, the Third starting between 1950 and 2007 and ending from the year 2000 to the present days, and the fourth with a strong consensus on starting in 2011; however, others consider the year 2000, with the end date in 2020 or happening in the present day, and Industry 5.0 from the year 2017 or that it will start in the future.
The findings highlighted several critical issues: the concepts of the Sequential Industry Framework are excessively centered on the historical context of industrial revolutions, thereby complicating the assessment of contemporary processes; the technologies associated with each level are not rigorously defined, there is a lack of answers on how to account for improvements of more than one system being introduced or in cases of partial implementation, and finally there is a lack of reproducibility in the criteria of classification of industry levels or industrial revolutions.
These weaknesses become evident in the literature when, for example, manual tasks, oral communication, and human sensory methods are classified under Industry 1.0; written communication and the replacement of human labor by machines under Industry 2.0; electricity under Industry 3.0; and technologies such as IoT, AI, and cloud-based solutions under Industry 5.0. For instance, in the agricultural context, some sources have defined Industry 1.0 as practices involving manual labor or animal traction, with origins dating back more than 10,000 years, an interpretation that contradicts the conventional association of Industry 1.0 with the First Industrial Revolution. Likewise, Agriculture 2.0 has been linked to the adoption of steam-powered machinery. These examples illustrate that much of the Industry 4.0 literature lacks a rigorous examination of prior stages and applies industrial classifications without ensuring consistency with historical or scholarly frameworks.
Finally, we propose that more rigorous efforts are needed to better define the concepts related to the Sequential Industry Framework. These concepts must be subjected to scientific scrutiny to assess whether they meet the standards required for use in the scientific literature.