## 2 Methods  
The documents that were taken into consideration in this review were collected from the Scopus database, a universally renowned source for scholarly bibliography. Scopus consists of an extensive amount of scientifically reliable and impactful publications and provides enriched information such as citation statics, etc. Scopus was selected for its comprehensive coverage of high-impact, peer-reviewed research and robust bibliometric tools, ensuring data reliability. While some studies from other databases may be excluded, Scopus provides strong quality control and citation tracking, making it ideal for analyzing MaaS research trends. To ensure an unbiased and meaningful selection, the following inclusion criteria were applied:  
* Relevance to MaaS: Only publications directly focusing on manufacturing-as-a-service (MaaS) were considered, identified through titles, abstracts, and keywords. * Peer-reviewed sources: Preference was given to scientifically reliable, peer-reviewed papers with strong methodologies, empirical findings, or theoretical contributions. * Renowned academic institutions: Publications originating from established research centers and universities were prioritized. * Database source: The Scopus database was selected for its comprehensive and high-quality scholarly coverage. * Time frame: The search covered the last 20 years to ensure an updated and relevant dataset. * Language criterion: Only English-language publications were included to maintain consistency and accessibility. * Document types: The final selection consisted of proceedings papers (42 papers, 52%)--the most dominant category; journal articles (37 papers, 46%)--providing in-depth analyses; and letters (2 papers, 2%)--offering concise contributions. This filtering process ensures a rigorous and impartial selection, maintaining a clear focus on MaaS research while enabling a systematic and data-driven literature review. The thematic categorization of the selected publications was based on a comprehensive review of the literature, ensuring a structured and meaningful classification. The three categories, \"MaaS Theoretical Approach\", \"MaaS Architectures\", and \"Data Innovations\", were chosen based on recurring research themes and the core contributions of each study. Previous literature reviews have primarily focused on conceptual frameworks, technological implementations, and data-driven advancements in MaaS. This classification allows for a clear differentiation between foundational theories, system architectures, and data-centric innovations, ensuring a systematic and comprehensive analysis of the field. By adopting this approach, we aim to highlight the evolution of MaaS research, facilitating a deeper understanding of its principles, technological enablers, and future potential. Disciplinary mapping plays a significant role in bibliometrics, offering knowledge relevant to the evolution of science. There are plenty of software tools accessible for bibliometric analysis, such as VOSviewer (version 1.6.20), CiteSpace, and GraphPad Prism. In this current review, VOSviewer [34] was utilized due to its user-friendly GUI and elevated capabilities related to co-occurrence and co-citation analysis, among others. VOSviewer was used to compose co-citation and keyword co-occurrence networks. Compared now to other available tools, VOSviewer was used due to convenience of its specialized capabilities and conformity with the objectives of this research. This tool provides excellent visually intuitive and detailed bibliometric maps, which are essential to generate co-occurrence and co-citation patterns. Since VOSviewer manages extended datasheets effectively, its accuracy in the representation of complex bibliometric connections is proven, making it a preferred tool for exploring keyword trends and author synergies. In comparison with CiteSpace, a proper application for temporal analysis, VOSviewer provides a more efficient, user-friendly interface with which users are easily familiarized and can immediately extract useful data.