ISM2: Interpretive structural modelling methodology in the context of in-space manufacturing for a strategic space project guideline
Year: 2025
Type: article
Abstract: In-space manufacturing (ISM) presents unique challenges due to its complexity, resource constraints, and the need for strategic planning. A structured guideline is essential for ensuring the success of ISM projects. This study presents the ISM 2 as the instantiation of the interpretive structural modeling methodology for in-space manufacturing, to provide a strategic framework for ISM by identifying and prioritizing key determinants for successful implementation. The study first conducted a content-centric literature review and engaged a focus group of academic researchers and industry experts to identify 20 critical determinants of ISM. It then applied interpretive structural modeling (ISM) to determine the optimal sequence of these determinants. An interpretive model and a logic knowledge base matrix were also used to develop a structured guideline for ISM projects, based on their driving and dependence power. The proposed guideline enhances the understanding of ISM determinants, enabling stakeholders to develop strategic roadmaps to implement in-space manufacturing projects effectively. • ISM 2 provides a structured strategic roadmap for in-space manufacturing (ISM) projects. • 23 Key determinants for successful ISM implementation were identified and prioritized. • Interpretive Structural Modeling clarifies interdependencies among ISM success factors. • The methodology integrates insights from academia and space industry experts. • Results emphasize the importance of modularity, logistics, and sustainability in ISM.
Source: Acta Astronautica
Authors: Chiara Giuseppina De Marco, Silvia Colabianchi, Francesco Costantino
Institution: Sapienza University of Rome
Language: English
Subfield: Astronomy and Astrophysics
Field: Physics and Astronomy
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $3,350
Funder: European Commission
Awards: G482427013, G661115845
OpenAlex ID: W6921745073
