1. Introduction
The evolution of manufacturing has been marked by successive industrial revolutions, each bringing about profound transformations in production systems, economic structures, and societal dynamics. The advent of mechanized production, as exemplified by the First Industrial Revolution in the 18th century, signaled a transition from manual craftsmanship to large-scale manufacturing. While these advances catalyzed economic growth and urbanization, they also led to an increased demand for natural resources and significant environmental degradation. Concerns over resource depletion, pollution, and unsafe labor conditions gradually emerged, yet it was not until the late 20th century that sustainability became a central focus in industrial development [1,2].
A seminal moment in the evolution of this movement was the publication of the Brundtland Report in 1987. This report introduced the widely accepted definition of sustainable development as “meeting the needs of the present without compromising the ability of future generations to meet their own needs”. This definition led to an increasing emphasis on environmental responsibility within manufacturing, initially focused on reducing emissions, waste, and pollution. As time progressed, however, a shift occurred, with sustainability in manufacturing transitioning from a reactive approach—centered on damage mitigation—to a proactive strategy that integrates sustainable practices into the fundamental operations of industry [2].
During the 2010s, the forces of globalization and mounting consumer pressure compelled numerous corporations to adopt more sustainable practices. This shift was accompanied by the introduction of mandatory regulations and certifications, which served to impose more stringent oversight of corporate activities. Consequently, sustainability has evolved from a mere regulatory compliance strategy to a critical business model for enhancing operational efficiency by reducing resource and energy consumption. This paradigm shift has led to the adoption of a holistic approach to sustainability, encompassing its three dimensions: economic, environmental, and social [3].
The evolution of sustainable manufacturing has been marked by a growing integration of technology and approach, driven by the paradigm of Industry 4.0. This digital transformation and business model innovation has enabled companies to enhance their sustainability. Through this holistic integration and the implementation of concepts such as the circular economy, which aims to close the life cycle of products, sustainable manufacturing seeks to adopt a restorative approach for the future. The overarching objective of sustainable manufacturing is to restore planetary boundaries to safe levels and ensure the long-term viability of life on Earth [4,5].
The integration of Industry 4.0 technologies and circular economy principles signifies a paradigm shift in sustainable manufacturing. The foundational element of Industry 4.0 is the digital infrastructure, which encompasses the Internet of Things (IoT), cyber–physical systems (CPS), and cloud computing. This infrastructure enables real-time data exchange, process automation, and dynamic optimization across manufacturing networks. These capabilities are critical for supporting circular economy strategies, which aim to regenerate natural systems by closing material loops through reuse, remanufacturing, and recycling [5]. The alignment between Industry 4.0 and the circular economy is particularly evident in the manner in which digital technologies facilitate actions such as product life extension, resource efficiency, and value recovery, which are considered to be the core pillars of circular innovation. By facilitating traceability, monitoring, and intelligent decision-making, Industry 4.0 technologies enable the implementation of closed-loop systems and reverse logistics networks that would otherwise be too complex or costly to manage [5]. Consequently, the integration of Industry 4.0 and the circular economy enables manufacturing systems to transition from linear to circular, resilient, and resource-efficient configurations.
Research Objective and Contribution
This document provides an overview that analyzes the latest research trends in sustainable manufacturing over the past five years. A systematic search of the literature on the subject was carried out using PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) to contextualize the research, and, considering global sustainability goals and the impact of industry on sustainable development, the study will focus on research, analyses, and advancements in sustainable manufacturing at an industrial level.
The primary objective of this review is to explore and synthesize the current advances and intersections of sustainable manufacturing strategies within the context of Industry 4.0, circular economy frameworks, and emerging biotechnologies. Specifically, the objective of this paper is to identify and critically examine how technological innovations—such as AM, CPS, and bio-based materials—are converging to redefine sustainability across industrial systems. This integrative perspective is essential for guiding both academic discourse and practical implementation toward more resilient and resource-efficient production models.
This review makes a significant contribution to the extant literature by providing a comprehensive, interdisciplinary analysis that links technological enablers of Industry 4.0 with environmental and circular economic imperatives. Whereas extant studies address these themes in isolation, the present study proposes a unified framework that highlights operational, organizational, and ecological synergies. Furthermore, the study makes an empirical contribution through its mapping of emerging practices in industrial symbiosis and circular production loops. The integration of enabling technologies, such as the IoT, simulation tools, and reverse logistics, offers actionable insights for decision-makers seeking to optimize both environmental performance and economic viability. In summary, this paper provides a holistic and structured overview of sustainable manufacturing paradigms as they evolve under the influence of Industry 4.0. It offers a theoretical and empirical foundation for future research and practice, advocating for a transformation toward circular, bio-based, and intelligent production systems.
Notwithstanding the proliferation of studies on sustainable manufacturing, several crucial gaps persist, a subject this review aims to explicitly address. Firstly, the extant literature on this subject has a tendency to analyze Industry 4.0 technologies, circular economy models, and bio-based innovations separately, without exploring the complex synergies and trade-offs that arise at their intersection in depth. This review makes a significant contribution by addressing the issue of fragmentation through an integrative perspective that articulates technological, environmental, and organizational dimensions. Secondly, the extant literature has identified a paucity of attention towards the specific role of small- and medium-sized enterprises (SMEs), especially in terms of their capacity to adopt and implement these advanced technologies. The paucity of empirical studies exploring the particular barriers and opportunities faced by SMEs represents a significant gap that this work aims to address. Finally, although industrial symbiosis and circularity strategies have been extensively discussed at a conceptual level, there are still few studies that map their practical application and real impact in different industrial sectors and geographical contexts. Synthesizing scattered evidence and highlighting best practices, this review seeks to address these gaps, offering useful guidance for future research and supporting both professionals and policymakers in adopting more holistic and context-appropriate approaches to sustainable manufacturing.
2. Materials and Methods
As previously stated, the present document conducts a systematic review within the scope of the conceptual framework presented in the introduction, applying a PRISMA-based method of literature search that has been adjusted for the engineering field. This review follows the guidance provided by the PRISMA methodology in its latest 2020 revision. Moreover, the study by Blanco et al. in 2020 [6] is utilized as a point of reference, detailing the methodology to be employed to undertake systematic reviews with PRISMA. This includes an in-depth case study that focuses on the most recent trends in the utilization of magnesium, aluminum, and titanium in sectors such as the automotive and aeronautics sectors.
Although PRISMA is a strong basis for carrying out systematic reviews, it has certain inherent limitations. A salient drawback pertains to its reliance on the accessibility and caliber of the included papers, which can exhibit considerable variability based on factors such as database coverage or the precision of search terms. Furthermore, PRISMA does not assess the methodological soundness or relevance of the selected studies, leaving this crucial task to researchers. This delegation has the potential to introduce bias into the review process if not managed with rigor. Another notable limitation stems from the variability among the identified studies. These differences can arise in various aspects, including research methodologies, data collection approaches, and study types. This heterogeneity can impede the synthesis, analysis, and interpretation of results, thereby imposing an additional burden on researchers to ensure the coherence and reliability of their findings.
Consequently, the methodology employed in this study is built on a systematic approach that consists of several key steps. Initially, the research question was defined, with a focus on investigating the latest trends in sustainable manufacturing. Secondly, a reading quota of 15 articles was established, as it was expected that a substantial number of them would be found. The article seeks to identify the most relevant articles; therefore, the search could not be too specific. Following the PRISMA methodology, the articles with the most citations were selected as being the most relevant to the topic under investigation. Consequently, the inclusion and exclusion criteria were predetermined to screen the search results. These criteria were meticulously designed to encompass specific aspects, including publication mode and rigorous quality standards. Simultaneously, search criteria were established, consisting of carefully selected keywords and their synonyms, to ensure comprehensive coverage of the topic and to minimize bias in the search process. Once the initial set of articles was retrieved, a preliminary selection process of the 15 articles was conducted. This involved using database tools to apply filters based on the predefined criteria. The texts were then reviewed, and articles that did not align with the research scope or failed to meet the established quality standards were excluded. Consequently, in the event that 1 of the 15 articles identified was discarded, the subsequent article with the highest number of references was selected, and this process was repeated until the desired number of articles was obtained. The final selection of the literature was categorized and organized according to factors such as type, topics covered, and relevance, through detailed reading and statistical analysis supported by database tools. The process ensured a thorough analysis and facilitated the identification of valuable insights in the desired topic from the selected articles. Finally, the conclusions drawn from the analysis were synthesized in order to facilitate the development of the results and discussion sections of this article. The search and analysis strategies are shown in an outline in Figure 1.
2.1. Inclusion and Exclusion Criteria Used in the Search
The preliminary definition of inclusion and exclusion criteria provides a solid foundation for the research and ensures that the results are consistent with the intended objectives. These criteria function not only to delineate the study’s scope, but also to mitigate potential bias and ensure that the selected literature is both pertinent and representative for the subsequent analysis [6].
As stated earlier, this analysis focuses on studies published within the last five years to provide a thorough examination of recent trends in sustainable manufacturing techniques. The selection of studies was primarily focused on journal articles, as they are renowned for their meticulous methodologies and reliable findings. Additionally, review articles were included to offer a broad perspective on the current state of the field, highlighting key developments. Conference proceedings were also considered, given their significance in showcasing the latest advancements, innovations, and emerging trends. These sources are especially useful for identifying new approaches to sustainable manufacturing.
To refine the search within the defined topic, a set of carefully selected keywords and synonyms were structured into Boolean equations (see Figure 2). This methodological approach guaranteed extensive coverage, thereby minimizing the probability of overlooking pertinent studies.
Web of Science (WoS) was selected as the primary bibliographic resource for this review because of its vast collection of high-quality, peer-reviewed publications and its sophisticated search and analysis tools. WoS provides access to reputable studies from top-tier journals, which adds credibility to the review. Its advanced filtering and Boolean search capabilities facilitate both comprehensive and precise literature searches, while its bibliometric tools enable trend analysis and citation tracking. The choice of WoS is in line with PRISMA’s core principles of rigor and transparency, ensuring the validity of the review and the inclusion of influential studies on sustainable manufacturing.
The selection of publications was constrained to those of an open access nature, with the objective of ensuring global accessibility and thereby fostering collaboration in research. The application of strict quality criteria was a further essential element of the re-search process. The inclusion of articles was contingent upon their having undergone the process of peer review and having been published in journals that were ranked in the top quartiles (Q1 and Q2) of the journal impact factor and journal citation reports. This ensured a high standard of reliability and rigor across the analyzed texts. These criteria are summarized in Table 1.
2.2. Definition of Search Criteria
The aim of this literature review is to explore the most significant studies on sustainable manufacturing, tracing its evolution from its inception to the present, while also considering potential future developments. Following the previously outlined search methodology, the study uses Boolean equations with keywords and their synonyms to effectively conduct the literature search.
The terms used in the search process are shown in Figure 2. The first column specifies the type of documents to be retrieved, including reviews, research papers, and studies, based on the predefined selection criteria. The second column refines the search to focus on sustainable manufacturing, ensuring that only relevant articles within this area are considered. The third column highlights the industrial applications of sustainable manufacturing, emphasizing its importance in advancing production and research in the manufacturing sector. The next column clusters key concepts related to sustainable manufacturing, such as product life cycle, eco-design, and circular economy, to increase the precision of the results and filter out unrelated studies. Finally, the last column includes terms related to sustainability and energy efficiency to maintain a strong focus on minimizing environmental impact. Given the broad nature of this topic and the likelihood of retrieving a large number of irrelevant articles, the advanced ‘exact search’ feature of WoS is used to ensure that each selected document contains at least one term from each column.
The Boolean equations used in the search are as follows: TS = (review OR research OR investigation OR stud*) AND TS = (sustainable manufacturing) AND TS = (industry) AND TS = (life cycle OR eco design OR eco-design OR circular economy OR value creation OR Industry 4.0) AND TS = (carbon dioxide OR carbon emission * OR energy efficient OR fossil fuel OR fuel consumption OR fuel saving OR global warming OR environment OR green OR carbon footprint)
With ‘exact search’ enabled in more options, the results of the WoS search, when entered with these Boolean equations, yielded a total of 1305 documents.
2.3. Literature Selection
This section describes the final selection process of the documents obtained in the previous search. First, the search was filtered according to the inclusion and exclusion criteria listed in Table 1. This filter was applied using the WoS search tools, including only open access and English language documents, which resulted in the exclusion of 697 (53.4%) documents from the search. The publication date filter was then applied, which excluded 171 (13.1%) documents from the search. With the exclusion of an additional 4 articles that were not in the English language, the result was a list of 522 articles to read.
In order to optimize document selection and ensure that the analysis was based on the most influential contributions in the field, it was decided to focus the study on the 15 most cited articles from the resulting set. This number was deemed sufficiently representative to encapsulate the most recent and pertinent trends in sustainable manufacturing, while maintaining an analysis on a manageable scale that would facilitate in-depth discussion. Moreover, the prioritization of the most cited works ensured that the selected articles have demonstrated substantial academic impact and recognition by the scientific community. This strategy enabled the study to concentrate on pivotal publications that influence the discourse and evolution of sustainable manufacturing paradigms, thereby ensuring that the results are grounded in well-established and widely recognized scientific contributions.
Therefore, the top 15 most cited articles underwent an initial review to apply the remaining inclusion and exclusion criteria. As a result, only one article (6.7%) was excluded because it did not meet the established quality standards. Specifically, the article was classified within the third quartile (Q3) of the journal citation reports, thereby falling short of the quality threshold defined by the review protocol, which required inclusion of only Q1 and Q2 publications. To maintain the selection criteria, the next most cited article was added to the final list. The article in question did satisfy all pre-established criteria for quality and credibility. The following flow chart, shown in Figure 3, summarizes the selection process for the literature found.
2.4. Synthesis and Analysis of the Documents Included in the Literature Review
The 15 selected documents underwent an in-depth review, including a content analysis aimed at identifying methodologies, approaches, and findings. This process allowed for the identification of recurring patterns, key contributions to the field, and potential gaps in the existing research. To ensure a comprehensive understanding, the selected texts were thoroughly reviewed, resulting in the extraction of the data summarized in Table 2.
As illustrated in Figure 4, a total of 14 documents (93.3%) were classified in business and engineering, which is a significant increase compared to other subject areas. In addition, 13 documents (86.7%) were associated with materials science, while 8 documents (53.3%) were associated with computer science and science technology. These results highlight the diversity and variation in the data collected, reinforcing their connection to the disciplines of engineering and economics.
The years 2019 and 2020 represent the majority of the texts analyzed, as illustrated in Figure 5. The majority of citations are concentrated in these articles, attributed to the longevity of these publications, allowing for more citations to accumulate.
As mentioned above, the terms ‘review’, ‘research’, ‘investigation’, and ‘study*’ were included in the search criteria to identify articles on state-of-the-art advances, process optimization, and experimental design related to the topic. Of the analyzed texts, 1 (6.7%) focused on state-of-the-art assessments, 11 (73.3%) explored process optimization, and 4 (26.7%) involved experiments aimed at improving or providing an alternative perspective on machining processes.
In addition to the classification system outlined in Table 2, a further categorization of the selected articles was conducted based on their thematic content. This additional classification was performed with a particular emphasis on their contribution to the broader context of sustainable manufacturing and the emerging opportunities it offers for industrial, technological, and environmental progress. Accordingly, Table 3 below delineates the primary research themes that were identified across the articles that were analyzed. These themes represent the most prominent strategic frameworks that currently underpin the advancement of sustainable manufacturing.
A total of 10 articles (66.7%) concentrate on the implementation of Industry 4.0, with the objective of optimizing the adoption of sustainability measures in companies and organizations. This underscores the significance of Industry 4.0 in this domain, positioning it as a fundamental element for the effective development of the three dimensions of sustainability. The circular economy appears prominently in the reviewed literature, cited in 9 out of 15 articles (60%). It is presented as a key strategic framework that enables sustainable manufacturing by promoting material recirculation through reuse, remanufacturing, and recycling. Often integrated with Industry 4.0 technologies, the circular economy supports the transition from linear to closed-loop systems, enhancing both environmental performance and resource efficiency. Meanwhile, environmental impact assessment is addressed in 8 of the reviewed articles (53.3%), reflecting its importance as a methodological tool for assessing the environmental impact of manufacturing processes. Often linked to life cycle thinking, it provides a structured approach to quantifying emissions, resource use, and waste generation, thereby guiding more informed and sustainable decision-making in industrial contexts. Additive manufacturing (AM) is featured in 6 of the reviewed articles (40%) as a key enabler of sustainable production. Its integration with Industry 4.0 further enhances its potential within circular and low-impact manufacturing systems. A total of 7 of the 15 reviewed articles (46.7%) discuss sustainable materials, highlighting their role in reducing environmental impact through the use of bio-based, biodegradable, or recycled alternatives. These materials are frequently assessed via life cycle approaches and are regarded as pivotal components in promoting green manufacturing and attaining circularity in production systems. Therefore, Life Cycle Assessment (LCA) is employed in 5 out of the 15 examined (33.3%) articles as a core analytical instrument to quantify the environmental impacts of products and processes across their entire life cycle. The utilization of LCA fosters evidence-based decision-making and enhances the incorporation of sustainability criteria in material selection, process optimization, and product design. Finally, the reviewed articles address applications in SMEs in 6 articles (40%). These studies underscore the dualities of implementing sustainable manufacturing practices in settings characterized by resource constraints, accentuating the necessity for scalable technologies, financial support mechanisms, and targeted skill development to facilitate adoption.
3. Results and Discussion
As previously mentioned in the Introduction, the pursuit of sustainability has seen a marked increase in recent years. This endeavor, undertaken by companies, institutions, and organizations, has been propelled by the implementation of innovative technologies, various policies and regulations, and the adoption of sustainable practices and strategies, such as circular economy principles and the introduction of sustainable materials. A comprehensive analysis encompasses the three pillars of sustainability: economic, environmental, and social. The application of analytical methods and assessment approaches can serve to further strengthen these implementations.
The most frequently implemented approach in the analyzed articles was Industry 4.0, which appeared in 10 out of the 15 selected texts (66.67%). This prevalence is not surprising, as Industry 4.0 represents a significant transformation in companies and manufacturing operations, as well as in industrial production, through the integration of advanced technologies. This term was first introduced in Germany in 2011 to denote a contemporary era characterized by the convergence of digital, physical, and biological technologies. This paradigm encompasses a wide range of technological advances, including CPS, the IoT, big data analysis, artificial intelligence (AI), and cloud computing. This fluid communication between physical and digital components allows for the decentralization of decision-making processes and the development of highly efficient production environments. Consequently, Industry 4.0 not only transforms manufacturing operations, but also reshapes value creation processes and business strategies at a systemic level [5]. This paradigm shift establishes the foundation for novel production models and redefines industrial practices, underscoring the interconnection between technological innovation and sustainability.
The evolution of manufacturing systems within the Industry 4.0 paradigm necessitates a multidisciplinary theoretical framework to comprehend the interrelationships between technological innovation and sustainability. In this context, four key frameworks are of particular pertinence: environmental impact assessment, circular economy principles, AM, and sustainable materials science. Environmental impact assessment serves as the foundation for evaluating the sustainability of manufacturing processes and technologies. It encompasses the identification, quantification, and mitigation of environmental consequences related to resource consumption, energy use, emissions, and waste generation [5]. LCA, a widely utilized method for quantifying environmental impacts across the entire lifecycle of products and processes, further informs this evaluation [2]. Furthermore, the integration of real-time data analytics and embedded environmental indicators within Industry 4.0 systems provides novel capabilities to monitor and mitigate environmental impacts during production processes.
Concomitantly, the circular economy offers a systemic framework that redefines growth by decoupling economic activity from the consumption of finite resources. In contrast to the conventional “take–make–dispose” model, it advocates for the recirculation of materials through reuse, refurbishment, remanufacturing, and recycling strategies [1]. AM plays a critical role in this transition by enabling localized production, reducing energy use, minimizing material waste, and supporting mass customization. Furthermore, AM facilitates the use of recycled or renewable materials, aligning with circular economy and sustainable innovation principles [2]. Material sustainability has become pivotal in advancing green manufacturing. A mounting body of research underscores the imperative to substitute petroleum-based inputs with biodegradable, renewable, and low-impact alternatives. The selection of raw materials is guided by sustainable design principles, as addressed through LCA, circularity, and eco-innovation. These principles favor non-toxic constituents and encourage reuse and recycling strategies throughout the product’s lifespan.
The relationship between sustainability and Industry 4.0 is of paramount importance in advancing sustainable practices within companies and organizations. The advent of Industry 4.0 technologies has engendered substantial opportunities to curtail environmental impacts, minimize material waste, and enhance energy efficiency. For instance, Kumar et al. [1] investigated the role of Industry 4.0 in enhancing the performance of SMEs in India through sustainable business models aligned with corporate social responsibility principles. Their findings underscore the potential of Industry 4.0 technologies to enhance the efficiency and energy savings of manufacturing processes. However, the study also notes that implementing these technologies remains particularly challenging for SMEs in developing countries due to resource limitations, identifying fifteen critical challenges that must be addressed to ensure successful integration. In a complementary line of research, Machado et al. [4] conducted a systematic review exploring how Industry 4.0 contributes to sustainable manufacturing. Utilizing bibliometric, social, and network analyses, they have provided quantitative insights into the development of research in this domain. While the correlation between Industry 4.0 and sustainability is recognized, the authors underscore that its integration remains inadequate and advocate for additional research grounded in practical case applications.
Additionally, Panetto et al. [7] analyzed the role of CPS in Industry 4.0 and highlighted key challenges in the transition toward the “industry of the future.” The aforementioned framework encompasses the control of manufacturing plants via CPS, interoperability across systems of systems (SoS), interconnected networks, and data-driven decision-making processes. These systems contribute to sustainable manufacturing by integrating complementary technologies, such as collaborative robots (cobots) and augmented reality, thus improving production efficiency. Moreover, a number of studies have examined the practical applications of this phenomenon. For instance, Braccini et al. [8] examined the adoption of Industry 4.0 in a sanitary ceramics manufacturing company, noting the paucity of empirical research on the subject. The case study evaluated the implementation process by considering sustainability’s three dimensions and employment variability. Contrary to concerns about job losses, the findings suggest that Industry 4.0 creates new roles while enhancing productivity, product quality, and workplace safety through continuous process improvement. Consequently, the study strongly recommends the adoption of these technologies to support sustainable manufacturing.
Despite the significant benefits that Industry 4.0 technologies can bring to sustainability and operational efficiency, SMEs face numerous and multifaceted barriers in their adoption. Key challenges include limited financial resources, a shortage of skilled personnel, underdeveloped digital infrastructure, and organizational inertia when it comes to embracing disruptive technologies [5]. Additionally, the substantial capital expenditure demanded by the integration of CPS, IoT platforms, and advanced data analytics tools poses a considerable obstacle for SMEs, particularly in developing economies [5]. These constraints are often compounded by difficulties in accessing external funding and the absence of tailored implementation roadmaps for smaller firms. To overcome these barriers, targeted policy measures and adaptive business strategies are essential. Governments and institutions can support SMEs through fiscal incentives, innovation grants, and low-interest financing mechanisms aimed at de-risking technological investments. Concurrently, capacity-building initiatives, including vocational training programs, digital literacy workshops, and industry–academia partnerships, can facilitate the acquisition of knowledge and skills. From a business perspective, the adoption of modular, interoperable, and scalable digital solutions enables SMEs to implement Industry 4.0 technologies incrementally, aligning with their operational and financial constraints. Furthermore, engagement in collaborative ecosystems, such as industrial clusters or digital innovation hubs, can facilitate access to shared infrastructure, technical expertise, and best practices, thereby reducing the barriers to successful digital transformation [5].
As previously mentioned, some of the reviewed articles explore additional concepts that reinforce the sustainable approach when implementing Industry 4.0. The studies by Tseng et al. [9] and Varela et al. [10] examine the integration of Industry 4.0 with lean manufacturing from a sustainability perspective. Lean manufacturing is a time-based philosophy that belongs to the set of “lean” techniques, focusing on creating value for the end consumer by eliminating activities that generate waste. In the initial study [9], bibliometric analyses were conducted to examine sustainable industry by linking lean manufacturing and Industry 4.0. The study concludes that further practical analyses of these cases are needed to strengthen the understanding of their combined impact. In the subsequent study [10], a structural equation model was proposed to quantitatively measure the effects of lean manufacturing and Industry 4.0, both with a focus on sustainability. To this end, a survey was administered in Spain and Portugal to assess the influence of these philosophies, and the resulting data were then analyzed both independently and in relation to one another. The resulting equation model was based on six hypotheses; however, it did not fully meet all the proposed criteria. The study ultimately suggests that the assumed variables differ from those commonly addressed in the analyzed literature, highlighting the need for further refinement and investigation in this area.
Another pivotal concept highlighted in several of the aforementioned articles is the circular economy. In the study published by Dev et al. [5], a pathway toward a sustainable supply chain is presented through the joint implementation of Industry 4.0 principles and the circular economy approach. Additionally, a lean approach and the implementation of reverse logistics are introduced as essential factors for improving sustainability. The study proposes a structured plan for this integrated implementation, outlining a comprehensive system that interconnects these elements. The study introduces optimized reuse and recycling processes facilitated by reverse logistics, designs for sustainable environments, and highlights key advantages such as cleaner and more efficient production.
AM, a process of paramount importance to the enhancement of sustainability in corporate and organizational entities, can also be regarded as a constituent element of Industry 4.0. In the study presented by Mehrpouya et al. [2], an analysis is conducted on the implementation of AM as a sustainable production process. The study underscores its substantial potential for sustainability improvements, as it facilitates the utilization of sustainable and recyclable materials, with some materials even being reusable. The study introduces key practices, including mass customization, a growing production model that prioritizes customer-specific considerations. It also introduces other essential concepts, such as eco-design and LCA. Eco-design ensures that every design process minimizes environmental impact, while LCA is a tool commonly used alongside eco-design to evaluate a product’s environmental footprint throughout its entire life cycle, considering all stages of production, use, and disposal. The study concludes by emphasizing the potential of AM when combined with other Industry 4.0 technologies and its promising future in advancing sustainable manufacturing.
A critical complementary strategy to advance Industry 4.0 from a sustainability perspective involves the incorporation of sustainable materials to replace traditional, more polluting alternatives. This practice aligns closely with the principles of Industry 4.0, as it supports the integration of circular economy strategies aimed at reducing waste, extending product lifecycles, and enabling product designs that facilitate disassembly and recycling. The incorporation of bio-based, biodegradable, or recyclable materials within smart manufacturing environments signifies a systemic endeavor to mitigate environmental impact while preserving high efficiency and cultivating innovation. In this regard, Hynes et al. [11] examined the textile industry’s use of dyes and chemicals, proposing sustainable alternatives and highlighting the role of Industry 4.0 technologies, including the IoT and smart sensors, to enhance management systems and improve sustainability performance. Fabris et al. [12] explored the industrialization and application of algae as a sustainable material in combination with Industry 4.0 technologies. The study’s findings underscore the potential of algae-based solutions to provide cost-effective, technologically advanced alternatives that promote environmental responsibility in domains such as biomass generation and biotechnology. Notwithstanding the promising potential of algae, the authors note a paucity of extensive research concerning its industrial applications.
Concurrently, Jones et al. [3] investigated the potential of mycelium-based composites as substitutes for conventional thermal and acoustic insulation materials. These bio-fabricated composites exhibit reduced energy consumption during the manufacturing process and offer superior thermal, acoustic, and fire resistance properties. Despite the presence of certain limitations, the study emphasizes their substantial potential to propel the transition toward environmentally sustainable construction solutions. Additionally, RameshKumar et al. [13] have focused on the design of biodegradable polymers aimed at reducing plastic pollution by replacing conventional packaging materials. Their research addresses the balance between biodegradability and functionality, incorporating a LCA to evaluate the sustainable value chain of bioplastics. Finally, Shafey [14] examined biosynthesis processes for substituting metallic and metal oxide nanoparticles commonly used in cosmetics, pharmaceuticals, and personal care products. This study underscores the utilization of biodegradable polymers as a substitute for such nanoparticles, offering insights into fabrication techniques while maintaining a pronounced focus on sustainability and environmental responsibility.
It can be stated with complete certainty that the implementation of Industry 4.0 is a practice that enhances the sustainability of companies and organizations, providing improvements that extend beyond this domain. The integration of advanced technologies into business practices has been shown to enhance efficiency, reduce environmental impact, and develop products and services that are more sustainable. However, it is imperative to acknowledge the challenges that must be addressed, such as unemployment and data privacy, to ensure a just and advantageous transition across the three dimensions of sustainability: economic, environmental, and social.
The transition to a fully sustainable manufacturing paradigm is contingent upon the convergence of Industry 4.0 and the previously discussed pillars of sustainability. Of particular significance is the relationship between Industry 4.0 and the circular economy. The efficacy of circular economy strategies is significantly enhanced when supported by Industry 4.0 technologies, which facilitate the establishment of industrial ecosystems that enable the continuous repurposing of materials and components. This synergy not only mitigates environmental impact, but also enhances economic viability. AM further strengthens this connection by leveraging Industry 4.0 technologies to optimize design, production processes, and material efficiency. The application of AI-driven design has been demonstrated to play a complementary role in this regard, achieving a reduction in material usage while preserving structural integrity. This, in turn, has resulted in products that are lighter, stronger, and more sustainable. In this context, sustainable materials, such as biodegradable polymers, engineered mycelium composites, and recycled carbon fiber, are critical in bridging Industry 4.0-enabled manufacturing with circular economy objectives. These materials are instrumental in facilitating the development of resource-efficient, closed-loop production systems.
Smart factories, enabled by Industry 4.0 technologies, further reinforce this integration through the implementation of real-time monitoring systems that assess material properties and performance. This ensures that bio-based and recycled materials can be seamlessly incorporated into demanding applications without compromising quality. Concurrently, the implementation of predictive maintenance, driven by data analytics, has been shown to optimize AM processes, thereby extending the material’s usability and reducing waste. The combination of these elements gives rise to a system in which the whole surpasses the sum of its parts. The advent of Industry 4.0 signifies more than merely a digital transformation instrument; it is the technological facilitator that enhances and integrates circular economy principles, additive manufacturing innovations, and sustainable material development. This integration is further advanced by real-time data.
On the other hand, despite the numerous advantages offered by the implementation of Industry 4.0, it is not a mandatory requirement for improving sustainable manufacturing in companies and organizations. In the study by Nana O. [15], the end-of-life applications of electric vehicle batteries are examined within a low-carbon circular economy. This research presents a sustainability approach aligned with the circular economy concept discussed earlier, but without considering Industry 4.0. The study, conducted in the United Kingdom, aims to reshape industrial systems. Initially, semi-structured surveys were carried out with various local companies, proposing closed-loop solutions, identifying challenges, and suggesting necessary actions. One key issue identified was the isolated implementation of closed-loop solutions, which should instead be applied collaboratively. The study also introduces the ReLiB Project, which aims to achieve nearly 100% battery mineral recycling. It is estimated that, through the implementation of regulatory measures such as these, a complete transition could be achieved by 2050 under a circular economy framework. Similarly, the study by Neves et al. [16] explores the implementation of industrial symbiosis, which enables different entities and companies—traditionally operating separately—to collaborate with one another. This article maps research trends in industrial symbiosis from a sustainability perspective, emphasizing how closing material cycles can significantly reduce previously generated waste. The study employs a case analysis method, gathering and qualitatively analyzing data to enhance understanding of existing cases. The findings highlight resource savings and economic benefits as the primary advantages of this approach.
A sustainability impact assessment was conducted to further elucidate the findings presented in the preceding sections. This assessment synthesizes the environmental, economic, and social contributions of the key technologies and strategies identified in the reviewed literature. The objective of this assessment is to provide a multifaceted perspective on the alignment of these innovations with the principles of sustainable manufacturing, which extends beyond their technical descriptions or conceptual functions. The resulting Table 4 classifies each element according to its systemic contributions and is based on the empirical evidence gathered from the selected studies included in this review.
As illustrated in Table 4, the reviewed literature elucidates the multifaceted contributions of each strategy and technology. The central enabling role of Industry 4.0 is evidenced by its integration of real-time data analytics, automation, and smart systems. Collectively, these technologies enhance energy efficiency, reduce waste, and support agile decision-making. Its economic relevance is particularly pronounced in the areas of operational optimization and cost reduction. On a social level, it demands a restructuring of workforce skills and digital literacy [4,7]. The circular economy has emerged as a system-level paradigm facilitating the continuous flow of materials through reuse, remanufacturing, and recycling. Its integration with digital tools enhances traceability and efficiency, while economically enabling new value creation models based on resource regeneration rather than extraction [1,5]. AM offers unique benefits by enabling localized, on-demand production with significantly reduced material waste. It facilitates customization, lightweight design, and reduced supply chain emissions. However, concerns regarding material recyclability and energy consumption during production underscore the need for future improvements [2]. The utilization of sustainable materials is imperative in the pursuit of decoupling manufacturing from its fossil-based inputs. These materials offer substantial environmental benefits but are still transitioning from niche applications to broader industrial scalability due to cost and durability constraints [3,13]. LCA serves as a methodological foundation for objectively evaluating sustainability outcomes across the entire lifespan of products [2]. Industrial symbiosis, on the other hand, is a strategic approach to enhancing resource efficiency at the system and product life cycle levels. It facilitates cross-sectoral material exchanges, thereby reducing collective waste [5,16]. The collective findings of the sustainability impact assessment underscore that technologies delivering the greatest sustainability gains are those that operate across multiple dimensions simultaneously—technological, environmental, economic, and social. This underscores the necessity of adopting holistic approaches when assessing the viability and strategic value of innovations within sustainable manufacturing systems.
Concurrently with technological and environmental innovations, global economic landscapes are undergoing profound transformations that are reshaping pathways toward sustainable manufacturing. In advanced economies, particularly in Western Europe and North America, there is a marked shift toward service-oriented and resource-regenerative business models. These regions are increasingly incorporating circular economy principles through the integration of advanced digital tools, Industry 4.0 technologies, and policy-driven incentives, including European directives and industrial symbiosis networks. Initiatives of this nature facilitate the establishment of closed-loop systems, real-time monitoring, digital twins, and collaborative platforms where firms exchange materials, energy, and information to optimize efficiency and minimize waste. This transition is facilitated by the presence of robust digital infrastructures and stringent environmental regulations, which have led to the development of sophisticated applications of sustainable manufacturing across various sectors [5,16].
Conversely, emerging and developing economies—particularly in Asia, Latin America, and select regions of Africa—are undergoing rapid industrialization, accompanied by increasing access to digital infrastructure and integration into global supply chains. In this context, the strategic implementation of Industry 4.0 technologies, reverse logistics, and AM is driven not solely by the pursuit of competitiveness, but also by the imperative to decouple economic growth from resource consumption. The aforementioned nations have advanced this agenda through the implementation of industrial symbiosis frameworks in eco-industrial parks. The promotion of shared use of materials, energy, and infrastructure is intended to achieve emissions reductions and cost savings. Moreover, additive manufacturing plays a pivotal role in the decentralization of production and the mitigation of transportation-related emissions, while facilitating the utilization of bio-based and biodegradable materials for mass customization [12,16].
However, considerable disparities persist in these regions due to varying levels of industrial maturity, regulatory support, and technological capabilities. The implementation of smart manufacturing remains uneven, particularly among SMEs, which face financial and technical challenges. Furthermore, while industrial symbiosis in advanced economies is often institutionalized and policy-driven, in developing contexts, it frequently emerges through informal or community-based initiatives influenced by resource scarcity and local socio-economic conditions [2,16].
When considered collectively, these region-specific trajectories indicate that sustainable manufacturing is not uniform. While global trends increasingly align around circularity, resilience, and digitalization, the operationalization of these concepts must be adapted to the unique economic, infrastructural, and regulatory realities of each region [2]. This underscores the necessity for context-sensitive strategies that ensure technological solutions are not only environmentally and socially beneficial, but also economically viable and locally relevant. Sustainable manufacturing, therefore, is best understood as a globally interconnected, yet regionally nuanced, transformation [13]. Nevertheless, significant disparities persist in these regions due to varying levels of industrial maturity, regulatory support, and technological capabilities. The implementation of smart manufacturing remains uneven, particularly among SMEs. These enterprises face financial and technical challenges. Furthermore, while industrial symbiosis in advanced economies is often institutionalized and policy-driven, in developing contexts, it frequently emerges through informal or community-based initiatives influenced by resource scarcity and local socio-economic conditions [1,2,16].
In light of these considerations, recent findings indicate that the future evolution of sustainable manufacturing will be influenced not only by regional adaptation and policy alignment, but also by the strategic incorporation of emerging technologies, bio-based innovations, and system-level circularity. A notable shift in manufacturing paradigms is evident, with a transition toward hybrid models that integrate digital intelligence with ecological functionality. For instance, the integration of Industry 4.0 tools—such as the IoT, real-time monitoring, digital twin simulations, and AI-driven decision-making—with bioengineered systems demonstrates a significant synergy between technological efficiency and biological regeneration [3,12]. These bio-digital systems possess the capacity to transform waste into value through decentralized, low-energy, and scalable processes that reduce environmental impact while enhancing material circularity. Concurrently with these innovations, the emergence of green nanotechnologies has opened new avenues for environmentally benign functional materials applicable in sectors ranging from electronics to water treatment [14]. Concurrently, systemic approaches, such as industrial symbiosis, are undergoing a transformation through the integration of advanced data infrastructures and supply chain analytics, thereby establishing interconnected networks for material and energy exchange. These digitally supported symbioses have the potential to enhance operational efficiency and to generate new business models grounded in eco-innovation and shared value creation [5,16]. These developments signify a fundamental shift in sustainable manufacturing, transitioning from isolated technological upgrades to comprehensive, interdisciplinary ecosystems capable of responding dynamically to local and global sustainability challenges. This paradigm shift underscores the imperative of integrating adaptability, resilience, and biological compatibility into the very fabric of industrial innovation strategies [12,14,16].
4. Conclusions and Future Research Directions
A thorough review of extant literature reveals that the integration of sustainable manufacturing processes within the industry engenders multiple advantages. These include the reduction in environmental impact and operational costs, while concomitantly enhancing production efficiency and overall machining performance. The following conclusions can be derived from this review: The advent of Industry 4.0 technologies has profoundly impacted the realm of sustainable manufacturing. These technologies serve as the foundational framework for real-time monitoring, predictive analytics, and resource optimization. By leveraging the capabilities of the IoT, AI, and blockchain, enterprises can enhance material traceability, reduce waste, and augment production efficiency. However, the widespread adoption of these technologies is impeded by several challenges. These include the high implementation costs, concerns regarding cybersecurity, and the necessity of technical expertise, particularly for SMEs. The circular economy is significantly enhanced through Industry 4.0 innovations, as digital systems facilitate closed-loop manufacturing, waste minimization, and improved material recovery processes. Nevertheless, the lack of standardized sustainability metrics and real-time LCA models limits the full exploitation of these benefits. AM offers significant potential for enhancing material efficiency and decentralized production. However, critical barriers persist, including high energy consumption, the recyclability of AM materials, and material degradation. To effectively integrate AM into circular systems, advancements in sustainable feedstocks, AI-driven design optimization, and automated end-of-life processing techniques are imperative. The utilization of sustainable materials, encompassing bio-based polymers, biodegradable composites, and engineered mycelium structures, is of paramount importance in the context of closing material loops. Concurrently, the industry continues to grapple with challenges pertaining to scalability, durability, and compatibility with prevailing manufacturing processes. The advent of innovations in nanotechnology-enhanced materials and AI-driven material selection holds immense potential in surmounting these impediments.
Despite the significant progress that has been made, future research must advance towards more rigorous and integrated methodologies to evaluate the real-world implementation of Industry 4.0 technologies in sustainable manufacturing environments. It is imperative to conduct longitudinal and mixed-method studies that can provide robust, context-sensitive insights into these transitions. A primary objective will be the formulation of comparative multi-case studies across diverse industrial sectors, with a particular emphasis on SMEs and high-impact value chains. These studies should integrate process tracing and realist evaluation approaches to elucidate the causal mechanisms underlying both successful and unsuccessful digital transformation pathways.
Furthermore, the integration of digital LCA models with real-time data streams sourced from IoT-enabled sensors, using platforms such as cloud-based Manufacturing Execution Systems (MES), will be vital. This dynamic coupling will enable near real-time monitoring of environmental performance indicators, thus enhancing precision and responsiveness in sustainability assessments.
Furthermore, it is recommended that subsequent research employ agent-based modeling techniques to simulate the adoption of circular economy practices fueled by Industry 4.0 technologies under diverse socioeconomic scenarios. These simulations should be enriched through participatory foresight workshops. Such workshops should include industry actors, policymakers, and supply chain partners. Together, they should co-create realistic and viable transition pathways. The integration of digital twin infrastructures with industrial symbiosis platforms, underpinned by semantic interoperability and ontology-based data integration frameworks, offers promising avenues for advanced coordination and decision-making across interconnected industrial ecosystems. The integration of digital LCA models with real-time data streams sourced from IoT-enabled sensors, using platforms such as cloud-based MES, will be vital. This dynamic coupling has the potential to facilitate the real-time monitoring of environmental performance indicators, thereby enhancing the precision and responsiveness of sustainability assessments.
Another critical area of inquiry pertains to the intersection of additive manufacturing, bio-based materials, and AI-powered decision support systems within circular economy loops. The employment of design science research methodologies will be instrumental in the iterative development and validation of decision-support tools that optimize material and resource flows, while effectively balancing trade-offs between economic, environmental, and social performance metrics.
The advancement of industrial symbiosis represents a significant opportunity to concurrently enhance sustainability and economic efficiency. The capacity of companies to exchange materials, energy, and by-products—repurposing waste streams from one sector as valuable inputs for another—has the potential to significantly reduce landfill waste, minimize resource extraction, and reduce production costs. Nevertheless, further research is necessary to effectively scale these models. Such research must address systemic enablers, including the development of robust regulatory frameworks, the standardization of waste classification, and the implementation of incentives for collaboration. Digital platforms and IoT-based monitoring architectures will also be essential to facilitate real-time tracking, ensure traceability, and enable seamless coordination across multiple industries.
Limitations of the Study
Notwithstanding the exhaustive nature of this systematic review and its contribution to the understanding of sustainable manufacturing trends, several limitations must be acknowledged. First and foremost, the study relies exclusively on previously published scientific monographs and peer-reviewed articles as primary data sources. While this approach ensures a certain degree of academic rigor, it may not encompass emerging, unpublished, or regionally specific practices that have yet to be documented in the literature. Consequently, the exclusive reliance on published monographs and articles constitutes an inadequate contribution to the formulation of a valuable article, as it curtails the diversity and immediacy of the knowledge base considered.
Furthermore, while the PRISMA methodology is widely accepted and systematic for literature reviews, it does possess inherent limitations. Specifically, PRISMA does not evaluate the methodological quality or practical relevance of the selected studies, placing the burden of assessment on the researchers themselves. This approach carries the potential for bias, particularly when the selected articles exhibit substantial heterogeneity in terms of methodology, data collection approaches, and industrial contexts.
Furthermore, the generalizability of the findings is constrained by the limited number of articles included in the final analysis (n = 15). While the selection of articles was based on factors such as citation count and relevance, this criterion may inadvertently favor older or more established research, potentially overlooking innovative but less-cited studies published more recently. Furthermore, the underrepresentation of certain technologies and sustainable manufacturing strategies can be attributed to their novelty and the limited number of comprehensive empirical validations available.
These limitations underscore the necessity for additional empirical research and the incorporation of a more extensive and diverse array of data sources in subsequent studies. The necessity of triangulating literature-based insights with field-level evidence is also underscored, as this approach is instrumental in developing more robust and context-sensitive conclusions.
Conceptualization, S.P.; methodology, S.P.; validation, E.M.R., J.A. and B.d.A.; formal analysis, S.P.; investigation, S.P.; resources, S.P.; data curation, S.P. and E.M.R.; writing—original draft preparation, S.P.; writing—review and editing, S.P., E.M.R., J.A. and B.d.A.; visualization, S.P.; supervision, E.M.R.; project administration, E.M.R. All authors have read and agreed to the published version of the manuscript.
No new data were created or analyzed in this study.
The authors are grateful for the support of the Industrial Production and Manufacturing Engineering (IPME) Research Group, the Innovation and Teaching Group for Industrial Technologies in Productive Environments (TIA Plus UNED), and the Master of Manufacturing Advanced Engineering.
The authors declare no conflicts of interest.
Footnotes
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Figure 1 Literature search strategy based on Blanco et al. [
Figure 2 Terms and synonyms entered in this search. The asterisk (*) serves as an operator that captures any letters that follow it.
Figure 3 Flow chart of the process of selection of the documents found in the search.
Figure 4 Main research areas of the articles found in the search.
Figure 5 Date of publication of the documents selected from the search results.
Inclusion and exclusion criteria used in the search.
| Inclusion/Exclusion Criteria | Feature |
|---|---|
| Publication period | From 1 January 2019 to 1 November 2024 |
| Type of study | Articles: journals, reviews, and conference proceedings |
| Keywords and synonyms | See |
| Information sources | Web of Science (WoS) |
| Databases in WoS | Option ‘All databases’ |
| Language of publication | English |
| Publication mode | Exclusively open access |
| Quality criteria required | Peer-reviewed articles included in WoS. Journal articles limited to Q1–Q2 |
| Quality criteria reviewed | Reviewed by journal impact factor and journal citations reports |
Main analysis of data from chosen search documents. The symbol ‘X’ indicates that the documents considered refer to or contain content relevant to the specified category.
| Documents | Number of | Publication Type | State of the Art | Process | Experiments | Country | Publication Year |
|---|---|---|---|---|---|---|---|
| [ | 198 | Q1 | X | India | 2020 | ||
| [ | 198 | Q1 | X | India | 2020 | ||
| [ | 208 | Q1 | X | Austria | 2020 | ||
| [ | 198 | Q1 | X | India | 2020 | ||
| [ | 243 | Q1 | X | X | India | 2020 | |
| [ | 157 | Q2 | X | France | 2019 | ||
| [ | 151 | Q2 | X | Italy | 2019 | ||
| [ | 169 | Q2 | X | Taiwan | 2021 | ||
| [ | 125 | Q2 | X | Portugal | 2019 | ||
| [ | 136 | Q1 | X | India | 2020 | ||
| [ | 178 | Q1 | X | Denmark | 2020 | ||
| [ | 224 | Q1 | X | Ireland | 2020 | ||
| [ | 304 | Q2 | X | Saudi Arabia | 2020 | ||
| [ | 135 | Q1 | X | United Kingdom | 2020 | ||
| [ | 162 | Q1 | X | Portugal | 2020 |
Analysis of key strategy themes from chosen search documents. The symbol ‘X’ indicates that the documents considered refer to or contain content relevant to the specified category.
| Documents | Industry 4.0 | Circular Economy | Environmental | Additive | Sustainable Materials | Life Cycle | Small and Medium-Sized Enterprises |
|---|---|---|---|---|---|---|---|
| [ | X | X | X | X | X | X | |
| [ | X | X | X | X | |||
| [ | X | X | |||||
| [ | X | ||||||
| [ | X | X | X | X | X | X | |
| [ | X | ||||||
| [ | X | X | X | ||||
| [ | X | ||||||
| [ | X | X | X | X | |||
| [ | X | X | X | X | |||
| [ | X | X | X | X | X | X | |
| [ | X | X | X | X | X | ||
| [ | X | X | X | ||||
| [ | X | X | |||||
| [ | X | X | X |
Sustainability impact assessment of the key technologies and strategies identified in the reviewed literature.
| Technology | Environmental Impact | Economic Impact | Social Impact |
|---|---|---|---|
| Industry 4.0 | Enables real-time monitoring and energy optimization; reduces emissions and resource consumption. | Improves productivity and operational efficiency. Enables data-driven decision-making. | Transforms workforce dynamics, but requires upskilling and digital literacy training. |
| Circular | Promotes reuse, recycling, and reduced resource extraction; mitigates environmental degradation. | Reduces input costs through reuse and remanufacturing and enables circular business models. | Promotes responsible consumption and the creation of green jobs. Encourages stakeholder collaboration. |
| AM | Reduces waste and transportation emissions through localized production and enables efficient use of materials. | Reduces inventory and logistics costs; supports mass customization and on-demand production. | Creates local jobs and supports the development of digital manufacturing skills. |
| Sustainable | Replaces conventional materials with biodegradable or bio-based alternatives, reducing environmental footprint. | Potentially high cost, but leads to long-term savings from reduced resource consumption and environmental compliance. | Publicly favored. It promotes consumer awareness and responsible material use. |
| LCA | Supports holistic assessment of environmental impacts across product lifecycle stages. | Enables cost-effective environmental planning and resource efficiency strategies. | Raises awareness of sustainability in product design and policy; supports informed decision-making. |
| Industrial | Minimizes waste by enabling resource sharing between industries. It also supports closed-loop systems. | Reduces raw material costs and creates synergies and new business opportunities. | Encourages inter-organizational collaboration; supports regional job growth. |
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