Abdoune, FarahFarahAbdouneOsman, MohamedMohamedOsmanBasarir, FezaFezaBasarirFilik, HalitHalitFilikNoaptes, MihaiMihaiNoaptesCelik, AhterAhterCelikArtan, Ulas CanUlas CanArtanDa Cunha, CatherineCatherineDa Cunha2026-08-262026-08-262026-0712th International Conference on Control, Decision and Information Technologies, CoDIT 2026https://hdl.handle.net/11420/64509In Manufacturing-as-a-Service (MaaS) environments, disruptions such as machine breakdowns or supplier failures require rapid reorchestration of production across distributed internal and external resources. This task is challenging because recovery options must satisfy multiple operational constraints, including capacity, capability compatibility, lead time, cost, and managerial policies. While existing literature addresses service selection, optimization, simulation, and multi-criteria evaluation, the formal generation of feasible reorchestration scenarios under MaaS constraints remains insufficiently structured. This paper proposes a rule-based methodological framework for generating and prioritizing feasible reorchestration scenarios in MaaS disruption contexts. The approach combines disruption-response mapping, scenario construction rules, feasibility filtering, and multi-criteria prioritization based on operational performance indicators. A representative MaaS case study is used to validate the methodology under internal, external, and hybrid response configurations. The results show that the proposed method can systematically construct feasible recovery scenarios and transparently prioritize them according to decision-maker preferences.enCloud manufacturingDecision-supportDigital enterpriseManufacturing-as-a-serviceReorchestrationServitizationTechnology::658: General ManagamentConference Paper10.1109/CoDIT70676.2026.11631253