Manufacturing as a Service: A Survey on Enabling Flexible, Sustainable, and Intelligent Production Through Digital Transformation
Manufacturing as a Service (MaaS) has emerged as a transformative paradigm at the intersection of Industry 4.0 and servitization, enabling flexible, sustainable, and intelligent production through on-demand provisioning of manufacturing resources. By leveraging cyber–physical systems, the Industrial Internet of Things, cloud/edge computing, artificial intelligence, digital twins, and data spaces, MaaS platforms decouple production capacity from asset ownership and orchestrate distributed manufacturing ecosystems in a service-oriented manner. This survey provides a structured, expert-driven review of the MaaS landscape, covering its conceptual foundations, stakeholder ecosystem, and introducing a reference architecture structured around data management, modeling, and decision-making suites. We analyze enabling technologies such as data spaces, asset administration shell, knowledge graphs, intent-based servitization, AI-driven prediction, and formal modeling approaches including linear, discrete-event, and hybrid systems. Furthermore, we examine optimization, planning and scheduling, digital twins, cloud manufacturing orchestration, and Zero-X evaluation frameworks targeting zero defects, zero downtime, zero waste, and zero emissions. Finally, we identify key open challenges related to scalability, interoperability, trust, data sovereignty, small–medium enterprise adoption, and circularity, outlining future research directions toward robust and trustworthy MaaS ecosystems.
Authors
- Aris Leivadeas (ORCID: https://orcid.org/0000-0002-2996-6824)
- Dimitrios Spatharakis (ORCID: https://orcid.org/0000-0002-0157-7173)
- Seán McLoone (ORCID: https://orcid.org/0000-0002-3016-6197)
- Tan Hou (ORCID: https://orcid.org/0000-0001-9958-8921)
- John Violos (ORCID: https://orcid.org/0000-0003-4219-3915)
- Felicien Ihirwe (ORCID: https://orcid.org/0000-0002-4463-6268)
- Symeon Papavassiliou (ORCID: https://orcid.org/0000-0002-9459-318X)
- Chao Gu (ORCID: https://orcid.org/0000-0001-8687-3870)
- Josefa Mula (ORCID: https://orcid.org/0000-0002-8447-3387)
- Raphaël M. Jungers (ORCID: https://orcid.org/0000-0002-7789-0940)
- Bart Meyers (ORCID: https://orcid.org/0000-0001-9566-8297)
- Ioannis Dimolitsas (ORCID: https://orcid.org/0000-0003-2679-3400)
- Carol Habib (ORCID: https://orcid.org/0000-0001-5454-567X)
- Nathalie Mitton (ORCID: https://orcid.org/0000-0002-8817-6275)
- Dimitrios Dechouniotis (ORCID: https://orcid.org/0000-0002-8984-9064)
- Lydia Mavraidi (ORCID: https://orcid.org/0009-0001-2339-8045)
- Blanca Guerrero (ORCID: https://orcid.org/0000-0002-8284-501X)
- Yuchen Zhang (ORCID: https://orcid.org/0000-0003-3835-9900)
- Rafael Marín-Pérez (ORCID: https://orcid.org/0000-0002-8521-1864)
- Νικόλαος Αθανασόπουλος (ORCID: https://orcid.org/0000-0002-0845-6163)
- Alejandro Arias-Jiménez (ORCID: https://orcid.org/0009-0008-5393-7127)
- Christoforos Vardakis
- Mo Ringbe Saynbe (ORCID: https://orcid.org/0009-0005-6042-1506)
- Takoua Jradi
- Farzana Haque Chowdhury
Institutions
- Queen's University Belfast (GB)
- University of Thessaly (GR)
- University of Peloponnese (GR)
- National Technical University of Athens (GR)
- Flanders Make (Belgium) (BE)
- Universitat Politècnica de València (ES)
- UCLouvain (BE)
- École de Technologie Supérieure (CA)
Publication Details
- Journal
- Journal of Manufacturing and Materials Processing
- Published
- 2026-11-05
- DOI
- https://doi.org/10.3390/jmmp10110488
- Primary Topic
- Digital Transformation in Industry
- Type
- article
- Field-Weighted Citation Impact
- 0.00