The technological arsenal behind this shift is formidable. Artificial intelligence, the Internet of Things, digital twins, extended reality, and blockchain are converging inside metaverse-style platforms to create persistent, immersive, and interoperable digital representations of factories. According to the editorial, manufacturing systems that undergo this transformation gain new possibilities for optimizing production, systems, and services through enhanced collaboration capabilities. The promised benefits are concrete: reduced waste, increased throughput, and more effective workforce training. Yet the same powerful tools bring equally concrete problems, including security risks, compatibility headaches, and the substantial costs of both initial transformation and ongoing utilization of digital technologies.

One of the most striking findings highlighted in the editorial concerns small and medium enterprises. Rahamaddula and colleagues, in a study cited within the research topic, observed that while large enterprises have already begun their digital transformation, SMEs are often left behind. This gap matters enormously, the authors argue, because SMEs form a large percentage of the manufacturing capability of many countries, and losing the benefits of digitalization and smart manufacturing can impose significant costs on national economies. The main obstacle identified was not a lack of ambition but uncertainty itself: the difficulty of judging the cost-benefit balance of digital transformation when the payoff is unclear and the investment is not.

To attack that uncertainty, the researchers proposed a readiness assessment tool built on factors recognized by experts as contributing to the readiness level of an SME. The tool was applied to practical use cases, giving companies a structured way to gauge whether their organization, infrastructure, and workforce can absorb metaverse-era technologies before committing scarce capital. The editorial notes that generalizing such readiness assessment and digital system mapping tools is one of the key future directions for the field, a step that could turn a bespoke research exercise into a standard diagnostic for the manufacturing mainstream.

Collaboration emerged as the second great challenge in the research collected under this topic. Magas and colleagues highlighted the difficulty of data transfer between different domains, a problem that becomes acute as factories stitch together machines, software layers, and partners that were never designed to talk to each other. Robust system mapping that uses ontologies, formal descriptions of concepts and their relationships, could solve this problem, but the study found that building such mappings proved a significant challenge, especially for inexperienced practitioners who lack the specialized vocabulary and modeling skills that ontology engineering demands.

The proposed remedy is characteristically metaverse-shaped: the technologies of the industrial metaverse and their interoperability can be used to establish platforms of ontology standards, creating collaborative tools that support ontology framework application, enhance system resilience, and ensure smooth cross-domain operations throughout the unique life cycle of every domain. In other words, the same immersive and networked infrastructure that lets engineers walk through a virtual factory can also serve as the shared semantic ground on which heterogeneous systems exchange meaning. The editorial frames this as a genuine opportunity, arguing that digital transformation provides a path toward understanding extended and complex systems that would otherwise remain opaque.

Two further contributions shift the focus from obstacles to opportunities. Mourtzis examined the possibilities that digital twins open up for human-machine interaction. When traditional manufacturing systems undergo digital transformation to become cyber-physical systems, maintaining a human-in-the-loop approach often proves a challenge, as automation layers tend to push operators out of the decision cycle. Industrial metaverse platforms offer a solution by immersing humans directly into cyber-physical system operations, facilitating greater system understanding and collaboration, streamlining communications, and promoting system adaptability, which in turn feeds sustainability and resilience.

Aheleroff and colleagues, meanwhile, argued that Industry 5.0 does not replace Industry 4.0 but cooperates with it, utilizing enhanced versions of existing technologies that can boost system sustainability and resilience when operated around the pillar of human-centricity. Their analysis suggests that the collaboration of humans with advanced technologies adds significant value by enabling the utilization of the scalability offered by Industry 4.0 while maintaining high flexibility in production and quality in products. This is the technical heart of the mass personalization story: as market demands push manufacturers from Mass Customization toward Mass Personalization, the complexity burden grows relentlessly, and only the combined leverage of digital technologies and human judgment can absorb it without sacrificing efficiency.

The editorial is candid that deeper engagement with digital transformation keeps surfacing hard problems. Significant challenges discovered in the research include security, privacy, financial stability, standardization, and regulation. These are not incidental friction points; they are structural conditions that determine whether a factory can trust an immersive digital replica with production-critical decisions, whether workers’ data gathered in virtual environments stays protected, and whether small firms can finance the transition without betting their survival on unproven returns. Standardization in particular recurs throughout the collected studies as the precondition for the cross-domain collaboration that the metaverse vision promises.

Taken together, the research topic showcases several opportunities for digital transformation and the industrial metaverse to promote Industry 5.0 goals such as resilience and sustainability, opportunities that rely heavily on the immense potential of advanced digital technologies for data transfer, optimization, and collaboration. But such powerful tools proved understandably challenging to use, mostly due to their cost, complexity, and the uncertainty of their impact. The future directions laid out in the editorial, generalizing readiness assessment and digital system mapping tools, pursuing standardization to facilitate collaboration, and exploring novel application possibilities for system performance optimization, sketch a roadmap for turning an ambitious vision into factory-floor practice. For manufacturers weighing the leap into the industrial metaverse, the message is measured: the technology is ready to deliver human-centered, sustainable, and resilient production, but only for organizations that plan for the costs, the standards, and the people as carefully as they plan for the software.

Subject of Research: Digital transformation of manufacturing through the industrial metaverse for Industry 5.0

Article Title: Editorial: Editor’s challenge in digital manufacturing – digital transformation of manufacturing through industrial metaverse: opportunities and challenges for industry 5.0

Article References: Editorial: Editor’s challenge in digital manufacturing – digital transformation of manufacturing through industrial metaverse: opportunities and challenges for industry 5.0. (n.d.). https://doi.org/10.3389/fmtec.2025.1754316

Image Credits: AI Generated

DOI: 10.3389/fmtec.2025.1754316

Keywords: Industry 5.0, industrial metaverse, digital manufacturing, digital twin, cyber-physical systems, human-machine interaction, SMEs, digital transformation, sustainability, resilience, mass personalization, interoperability