The RAASCEMAN Approach: Resilient and Adaptive Supply Chains for Capability-based Manufacturing as a Service Networks
Abstract The Manufacturing-as-a-Service (MaaS) model has been proposed by the research community and has been given significant attention by the industry as it holds the promise for agility and resilience of production networks. However, there are significant challenges (such as unforeseen events) that should be overcome for successful implementation of the MaaS model. The objective of this work is to enable companies to mitigate both short- and medium-term unforeseen events and to support them to participate in a dynamic MaaS network. To address these needs, five research objectives are suggested and discussed: 1) actionable propositions for adapting supply chains or internal production; 2) dynamic supply chain generation; 3) building trust in MaaS networks; 4) dynamic planning and scheduling of production processes; 5) dynamic assembly and disassembly. Moreover, a novel digital platform for implementing and integrating these objectives is presented. This paper presents the architectural foundations and methodological framework; empirical validation through two industrial pilots—one from the automotive domain (Continental, CZ) and one from the bicycle industry (Aska, BE)—is ongoing, with the validation methodology and target metrics defined herein. The work takes place in the context of the research and innovation action (RIA) project RAASCEMAN (Resilient and Adaptive Supply Chains for Capability-based Manufacturing as a Service Networks), funded by the Horizon Europe program.
Authors
- Jakub Hamerník
- Evangelos Xanthakis (ORCID: https://orcid.org/0000-0002-3858-5564)
- Tatjana Legler (ORCID: https://orcid.org/0000-0002-7297-0845)
- Bart Meyers (ORCID: https://orcid.org/0000-0001-9566-8297)
- Jesko Hermann (ORCID: https://orcid.org/0009-0004-4015-8205)
- Vasilis Siatras (ORCID: https://orcid.org/0000-0001-7378-5601)
- Pavel Burget (ORCID: https://orcid.org/0000-0002-4787-8182)
- Kunal Suri
- Achim Wagner
- Julian Groß
- Patrick Kremser
- Kosmas Alexopoulos
- Aleksandr Sidorenko
Institutions
- University of Kaiserslautern (DE)
- University of Patras (GR)
- Commissariat à l'Énergie Atomique et aux Énergies Alternatives (FR)
- Université Paris-Saclay (FR)
- German Research Centre for Artificial Intelligence (DE)
- Laboratoire d'Intégration des Systèmes et des Technologies (FR)
- Ortotika (Czechia) (CZ)
- Flanders Make (Belgium) (BE)
- INTRASOFT International (Luxembourg) (LU)
- Institute of Informatics of the Slovak Academy of Sciences (SK)
- Czech Technical University in Prague (CZ)
- University of Applied Sciences Kaiserslautern (DE)
Publication Details
- Journal
- Journal of Intelligent Manufacturing
- Published
- 2026-03-04
- DOI
- https://doi.org/10.1007/s10845-026-02828-0
- Primary Topic
- Supply Chain Resilience and Risk Management
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- University of Patras
- European Commission